diff --git a/README.md b/README.md
index 58ca490..98de0f7 100644
--- a/README.md
+++ b/README.md
@@ -1,12 +1,50 @@
 # H5Cloud - Cloud-Optimized Access of Hierarchical ICESat-2 Photon Data
 
 ## Quickstart
+
 Launch on [CryoCloud](https://cryointhecloud.com). Hosted on AWS US West2 region.
 Requires [CryoCloud user account](https://book.cryointhecloud.com/content/Getting_Started.html).
 
 [![CryoCloud JupyterHub](https://img.shields.io/badge/launch-CryoCloud-lightblue?logo=jupyter)](https://hub.cryointhecloud.com/hub/user-redirect/git-pull?repo=https%3A%2F%2Fgithub.com%2FICESAT-2HackWeek%2Fh5cloud&urlpath=lab%2Ftree%2Fh5cloud%2Fnotebooks%2Fformat-preprocessing-times.ipynb&branch=main)
 
+## How to use
+
+Create a config (or use an existing config) in `h5cloud/configs`. Each config defines a set of files which should be from the same collection but from different processing pipelines.
+
+```yaml
+collection: "atl03"
+group: "/gt1l/heights"
+variable: "h_ph"
+lat_group: "lat_ph"
+lon_group: "lon_ph"
+# create
+files:
+  original:
+    link: "s3://is2-cloud-experiments/h5cloud/atl03/average/original/ATL03_20191225111315_13680501_006_01.h5"
+    processing: null
+  repack_page_4gb:
+    link: "s3://is2-cloud-experiments/h5cloud/atl03/average/repacked/ATL03_20191225111315_13680501_006_01.h5"
+    processing: "h5repack -S PAGE -G 4000000"
+```
+
+Then when you run the test:
+
+```python
+from h5cloud import TestConfig
+from h5cloud.tests import H5pyArrSubsetMean
+
+tc = TestConfig.init(yaml_file="h5cloud/file_configs/atl03.yml" bucket="eodc-scratch", directory="h5cloud-tests/test-results")
+h5py_arr_subset_test = H5pyArrSubsetMean(tc)
+og_result = h5py_arr_subset_test.run('orginal')
+repacked_result = h5py_arr_subset_test.run('repack_page_4gb')
+print(f"Original: {og_result}")
+print(f"Repacked: {repacked_result}")
+```
+
+Results will also be stored in the bucket and directory passed in the TestConfg initialization.
+
 ## Collaborators
+
 Aimee Barciauskas, Development Seed <br>
 Andy Barrett, NSIDC <br>
 Wei Ji, Development Seed <br>
@@ -19,12 +57,14 @@ Rachel Wegener, University of Maryland, College Park <br>
 JP Swinski, NASA/GSFC <br>
 
 ## The Problem
+
 ICESat-2 photon-data is formatted as HDF5 files, which provide many advantages for scientific applications including being self-describing and able to store heterogenous data.
 However, ICESat-2 granules are frequently over a larger spatial extent than is needed for scientific workflows, meaning users must read in the full ATL03 HDF5 file to geolocate the data, then subset to a given area of interest. Applications like EarthData and NSIDC data portals have simplified this process for users by allowing them to provide a bounding box and only returning the subset data. Still, because HDF5 files are serialized, the original ATL03 H5 file must be read fully into memory by the cloud provider.
 
 This is in contrast to raster data, where cloud-optimized GeoTIFFs are organized internally such that it is easy to access only a specific subset of the total area using HTTP GET range requests. A similar capability for ICESat-2 along-track photon data would provide measurable read performance improvements for cloud data providers and local data users alike. The current aims of this Hackweek group are to benchmark current methods of accessing/subsetting ATL03 data from a public cloud data source (AWS S3), investigate methods of repacking photon data, and determine how libraries like [kerchunk](https://fsspec.github.io/kerchunk/) can be used for more efficient requesting of data from specific along-track locations.
 
 ## Sample Data
+
 ATL03 files used for testing were selected to maximize baseline ATL03 filesize, and are available at [s3://is2-cloud-experiments](s3://is2-cloud-experiments).
 
 ## Benchmark table
@@ -36,16 +76,18 @@ Notebooks exist in the [`notebooks/`](./notebooks/) folder for generating those
 | **Library/File Format**                | **Original HDF4** | **h5repack** | **kerchunk original** | **kerchunk repacked** | **GeoParquet** | **Flatgeobuf** |
 | -------------------------------------- | ----------------- | ------------ | --------------------- | --------------------- | -------------- | -------------- |
 | 1a - h5py                              |                   |              |                       | n/a                   | n/a            | n/a            |
-| 1b - gedi\_subsetter H5DataFrame       |                   |              |                       | n/a                   | n/a            | n/a            |
+| 1b - gedi_subsetter H5DataFrame        |                   |              |                       | n/a                   | n/a            | n/a            |
 | 2 - xarray via h5netcdf engine         |                   |              |                       |                       | n/a            | n/a            |
 | 3 - h5coro                             |                   |              |                       | n/a                   | n/a            | n/a            |
 | 4a - geopandas via pyogrio/GDAL driver |                   | n/a          | n/a                   | n/a                   |                |                |
 | 4b - geopandas via parquet driver      |                   | n/a          | n/a                   | n/a                   |                | n/a            |
 
 Key:
+
 - n/a = Not applicable as the file format is not supported by library.
 
 ## Resources
+
 - [ICESat-2 Hackweek Data Access Tutorials](https://icesat-2-2023.hackweek.io/tutorials/data-access-and-format/index.html)
 - [SlideRule](https://github.com/ICESat2-SlideRule)
 - [gedi-subsetter](https://github.com/MAAP-Project/gedi-subsetter)
@@ -59,13 +101,16 @@ Key:
 ## Folders
 
 ### `contributors`
+
 Each team member has it's own folder under contributors, where he/she can
 work on their contribution. Having a dedicated folder for one-self helps to
 prevent conflicts when merging with master.
 
 ### `notebooks`
+
 Notebooks that are considered delivered results for the project should go in
 here.
 
 ### `scripts`
+
 Helper utilities that are shared with the team
diff --git a/h5cloud/file_configs/ATL03_006.yaml b/h5cloud/file_configs/ATL03_006.yaml
new file mode 100644
index 0000000..6a2149c
--- /dev/null
+++ b/h5cloud/file_configs/ATL03_006.yaml
@@ -0,0 +1,32 @@
+collection: ATL03
+files:
+  kerchunk:
+    input_file: original
+    link: s3://nasa-veda-scratch/eodc_hdf5_experiments/ATL03___006/kerchunk___ATL03_20181014000347_02350101_006_02.json
+    processing: "def generate_json_reference(in_filename, out_filename):\n    so =\
+      \ dict(mode=\"rb\", default_fill_cache=False, default_cache_type=\"first\")\n\
+      \    with fs_read.open(in_filename, **so) as infile:     \n        h5chunks\
+      \ = SingleHdf5ToZarr(in_filename)\n        suffix = out_filename.split(\".\"\
+      )[-1]\n        out_filename = out_filename.replace(suffix, 'json')\n       \
+      \ with open(out_filename, 'w') as outfile:\n            outfile.write(json.dumps(h5chunks.translate()))\n\
+      \        return out_filename\n"
+  kerchunk_repacked_page_4mb:
+    input_file: repacked_page_4mb
+    link: s3://nasa-veda-scratch/eodc_hdf5_experiments/ATL03___006/kerchunk_repacked_page_4mb___ATL03_20181014000347_02350101_006_02.json
+    processing: "def generate_json_reference(in_filename, out_filename):\n    so =\
+      \ dict(mode=\"rb\", default_fill_cache=False, default_cache_type=\"first\")\n\
+      \    with fs_read.open(in_filename, **so) as infile:     \n        h5chunks\
+      \ = SingleHdf5ToZarr(in_filename)\n        suffix = out_filename.split(\".\"\
+      )[-1]\n        out_filename = out_filename.replace(suffix, 'json')\n       \
+      \ with open(out_filename, 'w') as outfile:\n            outfile.write(json.dumps(h5chunks.translate()))\n\
+      \        return out_filename\n"
+  original:
+    input_file: null
+    link: s3://nasa-veda-scratch/eodc_hdf5_experiments/ATL03___006/original/ATL03_20181014000347_02350101_006_02.h5
+    procssing: null
+  repacked_page_4mb:
+    input_file: original
+    link: s3://nasa-veda-scratch/eodc_hdf5_experiments/ATL03___006/repacked_page_4mb___ATL03_20181014000347_02350101_006_02.h5
+    processing: h5repack -S PAGE -G 4000000
+group: /gt1r/heights
+variable: h_ph
diff --git a/h5cloud/file_configs/ATL08_006.yaml b/h5cloud/file_configs/ATL08_006.yaml
new file mode 100644
index 0000000..6991cd7
--- /dev/null
+++ b/h5cloud/file_configs/ATL08_006.yaml
@@ -0,0 +1,32 @@
+collection: ATL08
+files:
+  kerchunk:
+    input_file: original
+    link: s3://nasa-veda-scratch/eodc_hdf5_experiments/ATL08___006/kerchunk___ATL08_20181014001049_02350102_006_02.json
+    processing: "def generate_json_reference(in_filename, out_filename):\n    so =\
+      \ dict(mode=\"rb\", default_fill_cache=False, default_cache_type=\"first\")\n\
+      \    with fs_read.open(in_filename, **so) as infile:     \n        h5chunks\
+      \ = SingleHdf5ToZarr(in_filename)\n        suffix = out_filename.split(\".\"\
+      )[-1]\n        out_filename = out_filename.replace(suffix, 'json')\n       \
+      \ with open(out_filename, 'w') as outfile:\n            outfile.write(json.dumps(h5chunks.translate()))\n\
+      \        return out_filename\n"
+  kerchunk_repacked_page_4mb:
+    input_file: repacked_page_4mb
+    link: s3://nasa-veda-scratch/eodc_hdf5_experiments/ATL08___006/kerchunk_repacked_page_4mb___ATL08_20181014001049_02350102_006_02.json
+    processing: "def generate_json_reference(in_filename, out_filename):\n    so =\
+      \ dict(mode=\"rb\", default_fill_cache=False, default_cache_type=\"first\")\n\
+      \    with fs_read.open(in_filename, **so) as infile:     \n        h5chunks\
+      \ = SingleHdf5ToZarr(in_filename)\n        suffix = out_filename.split(\".\"\
+      )[-1]\n        out_filename = out_filename.replace(suffix, 'json')\n       \
+      \ with open(out_filename, 'w') as outfile:\n            outfile.write(json.dumps(h5chunks.translate()))\n\
+      \        return out_filename\n"
+  original:
+    input_file: null
+    link: s3://nasa-veda-scratch/eodc_hdf5_experiments/ATL08___006/original/ATL08_20181014001049_02350102_006_02.h5
+    procssing: null
+  repacked_page_4mb:
+    input_file: original
+    link: s3://nasa-veda-scratch/eodc_hdf5_experiments/ATL08___006/repacked_page_4mb___ATL08_20181014001049_02350102_006_02.h5
+    processing: h5repack -S PAGE -G 4000000
+group: /gt1l/land_segments
+variable: dem_h
diff --git a/h5cloud/file_configs/GPM_3IMERGHHE_06.yaml b/h5cloud/file_configs/GPM_3IMERGHHE_06.yaml
new file mode 100644
index 0000000..23e16e0
--- /dev/null
+++ b/h5cloud/file_configs/GPM_3IMERGHHE_06.yaml
@@ -0,0 +1,32 @@
+collection: GPM_3IMERGHHE
+files:
+  kerchunk:
+    input_file: original
+    link: s3://nasa-veda-scratch/eodc_hdf5_experiments/GPM_3IMERGHHE___06/kerchunk___3B-HHR-E.MS.MRG.3IMERG.20000601-S000000-E002959.0000.V06B.json
+    processing: "def generate_json_reference(in_filename, out_filename):\n    so =\
+      \ dict(mode=\"rb\", default_fill_cache=False, default_cache_type=\"first\")\n\
+      \    with fs_read.open(in_filename, **so) as infile:     \n        h5chunks\
+      \ = SingleHdf5ToZarr(in_filename)\n        suffix = out_filename.split(\".\"\
+      )[-1]\n        out_filename = out_filename.replace(suffix, 'json')\n       \
+      \ with open(out_filename, 'w') as outfile:\n            outfile.write(json.dumps(h5chunks.translate()))\n\
+      \        return out_filename\n"
+  kerchunk_repacked_page_4mb:
+    input_file: repacked_page_4mb
+    link: s3://nasa-veda-scratch/eodc_hdf5_experiments/GPM_3IMERGHHE___06/kerchunk_repacked_page_4mb___3B-HHR-E.MS.MRG.3IMERG.20000601-S000000-E002959.0000.V06B.json
+    processing: "def generate_json_reference(in_filename, out_filename):\n    so =\
+      \ dict(mode=\"rb\", default_fill_cache=False, default_cache_type=\"first\")\n\
+      \    with fs_read.open(in_filename, **so) as infile:     \n        h5chunks\
+      \ = SingleHdf5ToZarr(in_filename)\n        suffix = out_filename.split(\".\"\
+      )[-1]\n        out_filename = out_filename.replace(suffix, 'json')\n       \
+      \ with open(out_filename, 'w') as outfile:\n            outfile.write(json.dumps(h5chunks.translate()))\n\
+      \        return out_filename\n"
+  original:
+    input_file: null
+    link: s3://nasa-veda-scratch/eodc_hdf5_experiments/GPM_3IMERGHHE___06/original/3B-HHR-E.MS.MRG.3IMERG.20000601-S000000-E002959.0000.V06B.HDF5
+    procssing: null
+  repacked_page_4mb:
+    input_file: original
+    link: s3://nasa-veda-scratch/eodc_hdf5_experiments/GPM_3IMERGHHE___06/repacked_page_4mb___3B-HHR-E.MS.MRG.3IMERG.20000601-S000000-E002959.0000.V06B.HDF5
+    processing: h5repack -S PAGE -G 4000000
+group: Grid
+variable: precipitationCal
diff --git a/h5cloud/file_configs/OMVFPITMET_003.yaml b/h5cloud/file_configs/OMVFPITMET_003.yaml
new file mode 100644
index 0000000..a015f85
--- /dev/null
+++ b/h5cloud/file_configs/OMVFPITMET_003.yaml
@@ -0,0 +1,32 @@
+collection: OMVFPITMET
+files:
+  kerchunk:
+    input_file: original
+    link: s3://nasa-veda-scratch/eodc_hdf5_experiments/OMVFPITMET___003/kerchunk___OMI-Aura_ANC-OMVFPITMET_2004m1001t000305-o01132_v003-2018m1015t140716.json
+    processing: "def generate_json_reference(in_filename, out_filename):\n    so =\
+      \ dict(mode=\"rb\", default_fill_cache=False, default_cache_type=\"first\")\n\
+      \    with fs_read.open(in_filename, **so) as infile:     \n        h5chunks\
+      \ = SingleHdf5ToZarr(in_filename)\n        suffix = out_filename.split(\".\"\
+      )[-1]\n        out_filename = out_filename.replace(suffix, 'json')\n       \
+      \ with open(out_filename, 'w') as outfile:\n            outfile.write(json.dumps(h5chunks.translate()))\n\
+      \        return out_filename\n"
+  kerchunk_repacked_page_4mb:
+    input_file: repacked_page_4mb
+    link: s3://nasa-veda-scratch/eodc_hdf5_experiments/OMVFPITMET___003/kerchunk_repacked_page_4mb___OMI-Aura_ANC-OMVFPITMET_2004m1001t000305-o01132_v003-2018m1015t140716.json
+    processing: "def generate_json_reference(in_filename, out_filename):\n    so =\
+      \ dict(mode=\"rb\", default_fill_cache=False, default_cache_type=\"first\")\n\
+      \    with fs_read.open(in_filename, **so) as infile:     \n        h5chunks\
+      \ = SingleHdf5ToZarr(in_filename)\n        suffix = out_filename.split(\".\"\
+      )[-1]\n        out_filename = out_filename.replace(suffix, 'json')\n       \
+      \ with open(out_filename, 'w') as outfile:\n            outfile.write(json.dumps(h5chunks.translate()))\n\
+      \        return out_filename\n"
+  original:
+    input_file: null
+    link: s3://nasa-veda-scratch/eodc_hdf5_experiments/OMVFPITMET___003/original/OMI-Aura_ANC-OMVFPITMET_2004m1001t000305-o01132_v003-2018m1015t140716.nc4
+    procssing: null
+  repacked_page_4mb:
+    input_file: original
+    link: s3://nasa-veda-scratch/eodc_hdf5_experiments/OMVFPITMET___003/repacked_page_4mb___OMI-Aura_ANC-OMVFPITMET_2004m1001t000305-o01132_v003-2018m1015t140716.nc4
+    processing: h5repack -S PAGE -G 4000000
+group: /
+variable: PS
diff --git a/h5cloud/file_configs/SNDRSNIML2CCPRETN_2.yaml b/h5cloud/file_configs/SNDRSNIML2CCPRETN_2.yaml
new file mode 100644
index 0000000..fadb8d1
--- /dev/null
+++ b/h5cloud/file_configs/SNDRSNIML2CCPRETN_2.yaml
@@ -0,0 +1,32 @@
+collection: SNDRSNIML2CCPRETN
+files:
+  kerchunk:
+    input_file: original
+    link: s3://nasa-veda-scratch/eodc_hdf5_experiments/SNDRSNIML2CCPRETN___2/kerchunk___SNDR.SNPP.CRIMSS.20120120T1254.m06.g130.L2_CLIMCAPS_RET_NSR.std.v02_28.G.200409132855.json
+    processing: "def generate_json_reference(in_filename, out_filename):\n    so =\
+      \ dict(mode=\"rb\", default_fill_cache=False, default_cache_type=\"first\")\n\
+      \    with fs_read.open(in_filename, **so) as infile:     \n        h5chunks\
+      \ = SingleHdf5ToZarr(in_filename)\n        suffix = out_filename.split(\".\"\
+      )[-1]\n        out_filename = out_filename.replace(suffix, 'json')\n       \
+      \ with open(out_filename, 'w') as outfile:\n            outfile.write(json.dumps(h5chunks.translate()))\n\
+      \        return out_filename\n"
+  kerchunk_repacked_page_4mb:
+    input_file: repacked_page_4mb
+    link: s3://nasa-veda-scratch/eodc_hdf5_experiments/SNDRSNIML2CCPRETN___2/kerchunk_repacked_page_4mb___SNDR.SNPP.CRIMSS.20120120T1254.m06.g130.L2_CLIMCAPS_RET_NSR.std.v02_28.G.200409132855.json
+    processing: "def generate_json_reference(in_filename, out_filename):\n    so =\
+      \ dict(mode=\"rb\", default_fill_cache=False, default_cache_type=\"first\")\n\
+      \    with fs_read.open(in_filename, **so) as infile:     \n        h5chunks\
+      \ = SingleHdf5ToZarr(in_filename)\n        suffix = out_filename.split(\".\"\
+      )[-1]\n        out_filename = out_filename.replace(suffix, 'json')\n       \
+      \ with open(out_filename, 'w') as outfile:\n            outfile.write(json.dumps(h5chunks.translate()))\n\
+      \        return out_filename\n"
+  original:
+    input_file: null
+    link: s3://nasa-veda-scratch/eodc_hdf5_experiments/SNDRSNIML2CCPRETN___2/original/SNDR.SNPP.CRIMSS.20120120T1254.m06.g130.L2_CLIMCAPS_RET_NSR.std.v02_28.G.200409132855.nc
+    procssing: null
+  repacked_page_4mb:
+    input_file: original
+    link: s3://nasa-veda-scratch/eodc_hdf5_experiments/SNDRSNIML2CCPRETN___2/repacked_page_4mb___SNDR.SNPP.CRIMSS.20120120T1254.m06.g130.L2_CLIMCAPS_RET_NSR.std.v02_28.G.200409132855.nc
+    processing: h5repack -S PAGE -G 4000000
+group: /
+variable: surf_temp
diff --git a/h5cloud/file_configs/atl03.yml b/h5cloud/file_configs/atl03.yml
new file mode 100644
index 0000000..874a49f
--- /dev/null
+++ b/h5cloud/file_configs/atl03.yml
@@ -0,0 +1,13 @@
+collection: "atl03__006"
+group: "/gt1l/heights"
+variable: "h_ph"
+lat_group: "lat_ph"
+lon_group: "lon_ph"
+# create
+files:
+  original:
+    link: "s3://is2-cloud-experiments/h5cloud/atl03/average/original/ATL03_20191225111315_13680501_006_01.h5"
+    processing: null
+  repack_page_4gb:
+    link: "s3://is2-cloud-experiments/h5cloud/atl03/average/repacked/ATL03_20191225111315_13680501_006_01.h5"
+    processing: "h5repack -S PAGE -G 4000000"
diff --git a/h5cloud/test_config.py b/h5cloud/test_config.py
new file mode 100644
index 0000000..7e67d72
--- /dev/null
+++ b/h5cloud/test_config.py
@@ -0,0 +1,34 @@
+import yaml
+from pydantic import Field, BaseModel
+from typing import Dict, Optional
+
+class FileConfig(BaseModel):
+    link: str
+    processing: Optional[str] = None
+
+class TestConfig(BaseModel):
+    results_bucket: str
+    results_directory: str
+    collection: str
+    group: str
+    variable: str
+    lat_group: Optional[str] = None
+    lon_group: Optional[str] = None
+    files: Dict[str, FileConfig]
+        
+    def load_from_yaml(yaml_file: str, results_bucket: str, results_directory: str):
+        """
+        Load the YAML configuration from the specified file and create a TestCollectionFiles object.
+        """
+        try:
+            with open(yaml_file, 'r') as file:
+                data = yaml.safe_load(file)
+                return TestConfig(results_bucket=results_bucket, results_directory=results_directory, **data)
+        except FileNotFoundError:
+            print(f"Error: The file {yaml_file} was not found.")
+        except yaml.YAMLError as exc:
+            print(f"Error in YAML formatting: {exc}")
+        except Exception as e:
+            print(f"An error occurred: {e}")
+
+        return None
\ No newline at end of file
diff --git a/h5tests/README.md b/h5cloud/tests/README.md
similarity index 100%
rename from h5tests/README.md
rename to h5cloud/tests/README.md
diff --git a/h5tests/h5_data_frame_arr_mean.py b/h5cloud/tests/h5_data_frame_arr_mean.py
similarity index 100%
rename from h5tests/h5_data_frame_arr_mean.py
rename to h5cloud/tests/h5_data_frame_arr_mean.py
diff --git a/h5cloud/tests/h5coro_arr_mean.py b/h5cloud/tests/h5coro_arr_mean.py
new file mode 100644
index 0000000..0fa94b2
--- /dev/null
+++ b/h5cloud/tests/h5coro_arr_mean.py
@@ -0,0 +1,24 @@
+from .h5test import H5Test, timer_decorator
+import numpy as np
+import subprocess
+
+try:
+    import h5coro
+except:
+    completed_process = subprocess.run([
+        'mamba', 'install', '-c', 'conda-forge', 'h5coro', '--yes'
+    ])
+    import h5coro
+
+from h5coro import h5coro, s3driver, filedriver
+h5coro.config(errorChecking=True, verbose=False, enableAttributes=False)
+    
+class H5CoroArrMean(H5Test):
+    @timer_decorator
+    def run(self, file_format: str):
+        tc = self.test_config
+        final_h5coro_array = []
+        file = tc.files[file_format]
+        h5obj = h5coro.H5Coro(file.link.replace("s3://", ""), s3driver.S3Driver)
+        h5obj.readDatasets(datasets=[f'{tc.group}/{tc.variable}'], block=True)
+        return h5obj[f'{tc.group}/{tc.variable}'].values.mean()
diff --git a/h5tests/h5coro_subset_arr_mean.py b/h5cloud/tests/h5coro_subset_arr_mean.py
similarity index 100%
rename from h5tests/h5coro_subset_arr_mean.py
rename to h5cloud/tests/h5coro_subset_arr_mean.py
diff --git a/h5cloud/tests/h5py_arr_mean.py b/h5cloud/tests/h5py_arr_mean.py
new file mode 100644
index 0000000..7f56049
--- /dev/null
+++ b/h5cloud/tests/h5py_arr_mean.py
@@ -0,0 +1,12 @@
+from .h5test import H5Test, timer_decorator
+import h5py
+
+class H5pyArrMean(H5Test):
+    @timer_decorator
+    def run(self, file_format: str, io_params: dict = {}):
+        tc = self.test_config
+        file = tc.files[file_format]        
+        final_h5py_array = []
+        with h5py.File(self.s3_fs.open(file.link, 'rb', **io_params.get('fsspec_params', {})), 'r', **io_params.get('h5py_params', {})) as h5obj:
+            data = h5obj[f'{tc.group}/{tc.variable}'][:].flatten()
+        return data.mean()
diff --git a/h5cloud/tests/h5py_arr_subset_mean.py b/h5cloud/tests/h5py_arr_subset_mean.py
new file mode 100644
index 0000000..2ba9649
--- /dev/null
+++ b/h5cloud/tests/h5py_arr_subset_mean.py
@@ -0,0 +1,44 @@
+import os
+import sys
+
+from .h5test import H5Test, timer_decorator
+import h5py
+import numpy as np
+sys.path.append(os.path.abspath('..'))
+from helpers.geospatial import get_subset_region, get_subset_indices
+
+class H5pyArrSubsetMean(H5Test):
+    
+    def __init__(self, data_format, geometry=None):
+        """
+        geometry : path to geojson file containing geometry
+                   **Could be list containing [lonmin, lonmax, latmin, latmax]**
+        """
+        super().__init__(data_format)
+        self.bounds = get_subset_region(geometry)
+        
+    @timer_decorator
+    def run(self, file_format: str):
+        final_h5py_array = []   
+        tc = self.test_config
+        file = tc.files[file_format]
+        with h5py.File(self.s3_fs.open(file.link, 'rb')) as f:
+            lat = f[f'{tc.group}/{tc.lat_group}'][:]
+            lon = f[f'{tc.group}/{tc.lon_group}'][:]
+    
+            idx_start, idx_end = get_subset_indices(lat, lon, self.bounds)
+            
+            # Leaving this code here so that we can create a DataFrame or
+            # Dataset at a later date.  Suggest creating dict which can be 
+            # passsed to xarray or (geo)pandas
+            # lat[idx_start:idx_end])
+            # lon[idx_start:idx_end])
+
+            data = f[f'{tc.group}/{tc.variable}'][idx_start:idx_end]
+            # Need to test if using concatenate is faster
+            final_h5py_array = np.insert(
+                final_h5py_array,
+                len(final_h5py_array),
+                data, axis=None
+            )
+        return np.mean(final_h5py_array)    
\ No newline at end of file
diff --git a/h5tests/h5test.py b/h5cloud/tests/h5test.py
similarity index 78%
rename from h5tests/h5test.py
rename to h5cloud/tests/h5test.py
index 74bb4de..a3e3d3a 100644
--- a/h5tests/h5test.py
+++ b/h5cloud/tests/h5test.py
@@ -6,10 +6,10 @@
 import os
 import s3fs
 import sys
-
 current = os.path.abspath('..')
 sys.path.append(current)
-from helpers.links import S3Links
+from ..test_config import TestConfig
+# from helpers.links import S3Links
 
 def generate_timestamp():
     return datetime.now().strftime('%Y-%m-%d-%H%M%S')
@@ -25,31 +25,30 @@ def wrapper(self, *args, **kwargs):
         execution_time = end_time - start_time
         # Call the store method here
         if self.store_results:
-            results_key = f"{generate_timestamp()}_{self.name}_{self.data_format}_results.csv"
+            data_format = args[0]
+            results_key = f"{generate_timestamp()}_{self.name}_{data_format}_results.csv"
             s3_key = f"{self.results_directory}/{results_key}"
-            self.store(run_time=execution_time, result=result, bucket=self.bucket, s3_key=s3_key)
+            self.store(run_time=execution_time, result=result, bucket=self.results_bucket, s3_key=s3_key, data_format=data_format)
         return result, execution_time
     return wrapper
 
 class H5Test:
-    def __init__(self, data_format: str, files=None, store_results=True):
+    def __init__(self, test_config: TestConfig, store_results=True):
         self.name = self.__class__.__name__
-        self.data_format = data_format
-        if files:
-            self.files = files
-        else:
-            self.files = S3Links().get_links_by_format(data_format)
+        self.test_config = test_config
         self.s3_client = boto3.client('s3')  # Ensure AWS credentials are configured
         self.s3_fs = s3fs.S3FileSystem(anon=False)
+        self.results = []
         self.store_results = store_results
-        self.bucket = "nasa-cryo-scratch"
-        self.results_directory = "h5cloud/benchmark_results"        
+        self.results_bucket = test_config.results_bucket
+        self.results_directory = test_config.results_directory
 
     @timer_decorator
-    def run(self):
+    # file format should match one of the options for files in the test_config
+    def run(self, file_format: str):
         raise NotImplementedError("The run method has not been implemented")
 
-    def store(self, run_time: float, result: str, bucket: str, s3_key: str):
+    def store(self, run_time: float, result: str, bucket: str, s3_key: str, data_format: str):
         """
         Store test results to an S3 bucket as a CSV file.
 
@@ -62,13 +61,13 @@ def store(self, run_time: float, result: str, bucket: str, s3_key: str):
         csv_buffer = StringIO()
         csv_writer = csv.writer(csv_buffer)
         csv_writer.writerow(['Name', 'Data Format', 'Run Time', 'Result'])  # Headers
-        csv_writer.writerow([self.name, self.data_format, run_time, result])
+        csv_writer.writerow([self.name, data_format, run_time, result])
 
         # Reset the buffer's position to the beginning
         csv_buffer.seek(0)
 
         # Upload the CSV to S3
-        self.s3_client.put_object(Bucket=bucket, Key=s3_key, Body=csv_buffer.getvalue())
+        return self.s3_client.put_object(Bucket=bucket, Key=s3_key, Body=csv_buffer.getvalue())
 
 ## Example subclass
 # class SampleTest(H5Test):
diff --git a/h5tests/single-test.ipynb b/h5cloud/tests/single-test.ipynb
similarity index 100%
rename from h5tests/single-test.ipynb
rename to h5cloud/tests/single-test.ipynb
diff --git a/h5cloud/tests/xarray_arr_mean.py b/h5cloud/tests/xarray_arr_mean.py
new file mode 100644
index 0000000..564ca90
--- /dev/null
+++ b/h5cloud/tests/xarray_arr_mean.py
@@ -0,0 +1,29 @@
+from .h5test import H5Test, timer_decorator
+import fsspec
+import xarray as xr
+import numpy as np
+
+class XarrayArrMean(H5Test):
+    def open_reference_ds(self, file: str, io_params: dict = {}):
+        fs = fsspec.filesystem(
+            'reference', 
+            fo=file, 
+            remote_protocol='s3', 
+            remote_options=dict(anon=False), 
+            skip_instance_cache=True,
+            **io_params.get('fsspec_params', {})
+        )
+        return xr.open_dataset(fs.get_mapper(""), engine='zarr', consolidated=False, group=self.test_config.group, cache=False)
+
+    @timer_decorator
+    def run(self, file_format: str, io_params: dict = {}):
+        tc = self.test_config
+        file = tc.files[file_format]        
+        if 'kerchunk' in file_format:
+            xrds = self.open_reference_ds(file=file.link)
+        else:
+            file_opener = self.s3_fs.open(file.link, **io_params.get('fsspec_params', {}))
+            xrds = xr.open_dataset(file_opener, group=tc.group, engine='h5netcdf', **io_params.get('h5py_params', {}), cache=False)
+        data = xrds[tc.variable]
+        xrds.close()
+        return float(data.mean().values)
diff --git a/h5tests/h5coro_arr_mean.py b/h5tests/h5coro_arr_mean.py
deleted file mode 100644
index 58b3f76..0000000
--- a/h5tests/h5coro_arr_mean.py
+++ /dev/null
@@ -1,27 +0,0 @@
-from .h5test import H5Test, timer_decorator
-import numpy as np
-import subprocess
-
-try:
-    import h5coro
-except:
-    completed_process = subprocess.run([
-        'mamba', 'install', '-c', 'conda-forge', 'h5coro', '--yes'
-    ])
-    import h5coro
-
-from h5coro import h5coro, s3driver, filedriver
-h5coro.config(errorChecking=True, verbose=False, enableAttributes=False)
-    
-class H5CoroArrMean(H5Test):
-    @timer_decorator
-    def run(self):
-        group = '/gt1l/heights'
-        variable = 'h_ph'        
-        final_h5coro_array = []
-        for file in self.files:
-            h5obj = h5coro.H5Coro(file.replace("s3://", ""), s3driver.S3Driver)
-            output = h5obj.readDatasets(datasets=[f'{group}/{variable}'], block=True)
-            data = h5obj[f'{group}/{variable}'].values
-            final_h5coro_array = np.insert(final_h5coro_array, len(final_h5coro_array), data, axis=None)
-        return np.mean(final_h5coro_array)
diff --git a/h5tests/h5py_arr_mean.py b/h5tests/h5py_arr_mean.py
deleted file mode 100644
index 7c35407..0000000
--- a/h5tests/h5py_arr_mean.py
+++ /dev/null
@@ -1,21 +0,0 @@
-from .h5test import H5Test, timer_decorator
-import h5py
-import numpy as np
-
-class H5pyArrMean(H5Test):
-    @timer_decorator
-    def run(self):
-        final_h5py_array = []  
-        # TODO: Do we need to make this configurable or consistent?
-        group = '/gt1l/heights'
-        variable = 'h_ph'        
-        for file in self.files:
-            with h5py.File(self.s3_fs.open(file, 'rb')) as f:
-                data = f[f'{group}/{variable}'][:]
-                # Need to test if using concatenate is faster
-                final_h5py_array = np.insert(
-                    final_h5py_array,
-                    len(final_h5py_array),
-                    data, axis=None
-                )
-        return np.mean(final_h5py_array)
diff --git a/h5tests/h5py_arr_subset_mean.py b/h5tests/h5py_arr_subset_mean.py
deleted file mode 100644
index e8ceeea..0000000
--- a/h5tests/h5py_arr_subset_mean.py
+++ /dev/null
@@ -1,49 +0,0 @@
-import os
-import sys
-
-from .h5test import H5Test, timer_decorator
-import h5py
-import numpy as np
-
-current = os.path.abspath('..')
-sys.path.append(current)
-from helpers.geospatial import get_subset_region, get_subset_indices
-
-class H5pyArrSubsetMean(H5Test):
-    
-    def __init__(self, data_format, geometry=None):
-        """
-        geometry : path to geojson file containing geometry
-                   **Could be list containing [lonmin, lonmax, latmin, latmax]**
-        """
-        super().__init__(data_format)
-        self.bounds = get_subset_region(geometry)
-        
-    @timer_decorator
-    def run(self):
-        final_h5py_array = []  
-        # TODO: Do we need to make this configurable or consistent?
-        group = '/gt1l/heights'
-        variable = 'h_ph'        
-        for file in self.files:
-            with h5py.File(self.s3_fs.open(file, 'rb')) as f:
-                
-                lat = f[f'{group}/lat_ph'][:]
-                lon = f[f'{group}/lon_ph'][:]
-        
-                idx_start, idx_end = get_subset_indices(lat, lon, self.bounds)
-                
-                # Leaving this code here so that we can create a DataFrame or
-                # Dataset at a later date.  Suggest creating dict which can be 
-                # passsed to xarray or (geo)pandas
-                # lat[idx_start:idx_end])
-                # lon[idx_start:idx_end])
-
-                data = f[f'{group}/{variable}'][idx_start:idx_end]
-                # Need to test if using concatenate is faster
-                final_h5py_array = np.insert(
-                    final_h5py_array,
-                    len(final_h5py_array),
-                    data, axis=None
-                )
-        return np.mean(final_h5py_array)    
\ No newline at end of file
diff --git a/h5tests/xarray_arr_mean.py b/h5tests/xarray_arr_mean.py
deleted file mode 100644
index 0c1fc92..0000000
--- a/h5tests/xarray_arr_mean.py
+++ /dev/null
@@ -1,31 +0,0 @@
-from .h5test import H5Test, timer_decorator
-import fsspec
-import xarray as xr
-import numpy as np
-
-class XarrayArrMean(H5Test):
-    def open_reference_ds(self, file):
-        fs = fsspec.filesystem(
-            'reference', 
-            fo=file, 
-            remote_protocol='s3', 
-            remote_options=dict(anon=False), 
-            skip_instance_cache=True
-        )
-        return xr.open_dataset(fs.get_mapper(""), engine='zarr', consolidated=False, group='gt1l/heights')
-
-    @timer_decorator
-    def run(self):
-        group = '/gt1l/heights'
-        variable = 'h_ph'
-        if 'kerchunk' in self.data_format:
-            datasets = [self.open_reference_ds(file) for file in self.files]
-            h_ph_values = []
-            for dataset in datasets:
-                h_ph_values = np.append(h_ph_values, dataset['h_ph'].values)
-            return np.mean(h_ph_values)
-        else:
-            s3_fileset = [self.s3_fs.open(file) for file in self.files]
-            xrds = xr.open_mfdataset(s3_fileset, group=group, combine='by_coords', engine='h5netcdf')
-            h_ph_values = xrds['h_ph']
-            return float(np.mean(h_ph_values).values)
diff --git a/helpers/geospatial.py b/helpers/geospatial.py
index c5bd57d..397ae5b 100644
--- a/helpers/geospatial.py
+++ b/helpers/geospatial.py
@@ -4,7 +4,7 @@
 import geopandas as gpd
 import numpy as np
 
-geojson_path = '/home/jovyan/h5cloud/helpers/antarctic_aoi.geojson'
+geojson_path = f"{os.path.abspath('helpers')}/antarctic_aoi.geojson"
 
 def get_subset_region(geometry=None):
     """Returns bounds from geojson or list
diff --git a/notebooks/replicate-results-research/01-check-co-hdf5-cmr.ipynb b/notebooks/replicate-results-research/01-check-co-hdf5-cmr.ipynb
new file mode 100644
index 0000000..1bc8e97
--- /dev/null
+++ b/notebooks/replicate-results-research/01-check-co-hdf5-cmr.ipynb
@@ -0,0 +1,648 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "874786c0-3eea-4e92-87a1-b5fe99a563f2",
+   "metadata": {},
+   "source": [
+    "# 01 - Evaluate NASA HDF5 and NetCDF files for cloud-optimized-ness\n",
+    "\n",
+    "This report includes only files which inclue a data format attribute value of \"NetCDF\" or \"HDF\". There are other formats which include HDF or NetCDF:\n",
+    "\n",
+    "* netCDF4-zipped3\n",
+    "* netCDF-3 - HDF-EOS22\n",
+    "* netCDF-4 - ASCII4\n",
+    "* netCDF-4 - netCDF-3\n",
+    "* HDF4 - netCDF-4\n",
+    "\n",
+    "But they are very small in number (25) compared with the total of NetCDF and HDF tagged collections (1530 and 958, respectively)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "f01a3483-ed3e-43f2-be41-c57fc0a3f286",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import boto3\n",
+    "import earthaccess\n",
+    "import json\n",
+    "import os\n",
+    "import pandas as pd\n",
+    "from pathlib import Path\n",
+    "import re\n",
+    "import requests\n",
+    "import subprocess"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "54f9ab4a-bd01-4236-9250-d7011c50db90",
+   "metadata": {},
+   "source": [
+    "# List all cloud-hosted NetCDF and HDF5 collections in Earthdata Cloud"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "fdc1de05-c793-475a-ae56-cdeecc48588d",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Status Code: 200\n",
+      "Adding 2000 collections\n",
+      "Status Code: 200\n",
+      "Adding 508 collections\n",
+      "CPU times: user 154 ms, sys: 52.5 ms, total: 206 ms\n",
+      "Wall time: 7.68 s\n"
+     ]
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "# URL to which the POST request is sent\n",
+    "search_url = 'https://cmr.earthdata.nasa.gov/search/collections.json'\n",
+    "max_page_size = 2000 # the limit\n",
+    "collections = []\n",
+    "page_num = 1\n",
+    "while True:\n",
+    "    # taken from search.eartndata.nasa.gov\n",
+    "    form_data = f\"cloud_hosted=true&has_granules_or_cwic=true&include_granule_counts=true&include_has_granules=true&page_num={page_num}&page_size={max_page_size}&granule_data_format_h[]=HDF&granule_data_format_h[]=NetCDF&sort_key[]=has_granules_or_cwic&sort_key[]=-usage_score\"\n",
+    "    \n",
+    "    # Headers specifying the content type (important if the server expects form data)\n",
+    "    headers = {\n",
+    "        'Content-Type': 'application/x-www-form-urlencoded'\n",
+    "    }\n",
+    "    \n",
+    "    # Sending the POST request\n",
+    "    response = requests.post(search_url, data=form_data, headers=headers)\n",
+    "    \n",
+    "    # Print the status code and response text\n",
+    "    print(\"Status Code:\", response.status_code)\n",
+    "    collection_response_json = json.loads(response.text)\n",
+    "    collections_list = collection_response_json['feed']['entry']\n",
+    "    num_collections = len(collections_list)\n",
+    "    print(f\"Adding {num_collections} collections\")\n",
+    "    collections.extend(collections_list)\n",
+    "    if num_collections < max_page_size:\n",
+    "        break\n",
+    "    else:\n",
+    "        page_num += 1"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "90938efc-8321-4694-88f7-f69159d50f81",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2508\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(len(collections))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c8571261-68e5-4bfe-83a5-663800efa96f",
+   "metadata": {},
+   "source": [
+    "# Start a dask cluster so we can parallelize inspecting these files"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "d394d844-4b24-4f95-b29f-0874dfc3b76c",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "    <div style=\"width: 24px; height: 24px; background-color: #e1e1e1; border: 3px solid #9D9D9D; border-radius: 5px; position: absolute;\"> </div>\n",
+       "    <div style=\"margin-left: 48px;\">\n",
+       "        <h3 style=\"margin-bottom: 0px;\">Client</h3>\n",
+       "        <p style=\"color: #9D9D9D; margin-bottom: 0px;\">Client-b3448aca-0986-11ef-819b-b274688e4fb2</p>\n",
+       "        <table style=\"width: 100%; text-align: left;\">\n",
+       "\n",
+       "        <tr>\n",
+       "        \n",
+       "            <td style=\"text-align: left;\"><strong>Connection method:</strong> Cluster object</td>\n",
+       "            <td style=\"text-align: left;\"><strong>Cluster type:</strong> dask_gateway.GatewayCluster</td>\n",
+       "        \n",
+       "        </tr>\n",
+       "\n",
+       "        \n",
+       "            <tr>\n",
+       "                <td style=\"text-align: left;\">\n",
+       "                    <strong>Dashboard: </strong> <a href=\"/services/dask-gateway/clusters/prod.bdf8bdcb2da24df9a390b57bbd41dba9/status\" target=\"_blank\">/services/dask-gateway/clusters/prod.bdf8bdcb2da24df9a390b57bbd41dba9/status</a>\n",
+       "                </td>\n",
+       "                <td style=\"text-align: left;\"></td>\n",
+       "            </tr>\n",
+       "        \n",
+       "\n",
+       "        </table>\n",
+       "\n",
+       "        \n",
+       "            <button style=\"margin-bottom: 12px;\" data-commandlinker-command=\"dask:populate-and-launch-layout\" data-commandlinker-args='{\"url\": \"/services/dask-gateway/clusters/prod.bdf8bdcb2da24df9a390b57bbd41dba9/status\" }'>\n",
+       "                Launch dashboard in JupyterLab\n",
+       "            </button>\n",
+       "        \n",
+       "\n",
+       "        \n",
+       "            <details>\n",
+       "            <summary style=\"margin-bottom: 20px;\"><h3 style=\"display: inline;\">Cluster Info</h3></summary>\n",
+       "            <div style='background-color: #f2f2f2; display: inline-block; padding: 10px; border: 1px solid #999999;'>\n",
+       "  <h3>GatewayCluster</h3>\n",
+       "  <ul>\n",
+       "    <li><b>Name: </b>prod.bdf8bdcb2da24df9a390b57bbd41dba9\n",
+       "    <li><b>Dashboard: </b><a href='/services/dask-gateway/clusters/prod.bdf8bdcb2da24df9a390b57bbd41dba9/status' target='_blank'>/services/dask-gateway/clusters/prod.bdf8bdcb2da24df9a390b57bbd41dba9/status</a>\n",
+       "  </ul>\n",
+       "</div>\n",
+       "\n",
+       "            </details>\n",
+       "        \n",
+       "\n",
+       "    </div>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "<Client: 'tls://192.168.30.130:8786' processes=14 threads=14, memory=105.63 GiB>"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from dask_gateway import GatewayCluster, Gateway\n",
+    "import dask.bag as db\n",
+    "\n",
+    "gateway = Gateway()\n",
+    "clusters = gateway.list_clusters()\n",
+    "\n",
+    "# connect to an existing cluster - this is useful when the kernel shutdown in the middle of an interactive session\n",
+    "if clusters:\n",
+    "    cluster = gateway.connect(clusters[0].name)\n",
+    "else:\n",
+    "    options = gateway.cluster_options()\n",
+    "    # Set environment variables\n",
+    "    options.environment = {\n",
+    "        \"EARTHDATA_USERNAME\": os.environ['EARTHDATA_USERNAME'],\n",
+    "        \"EARTHDATA_PASSWORD\": os.environ['EARTHDATA_PASSWORD']\n",
+    "    }\n",
+    "    cluster = gateway.new_cluster(cluster_options=options)\n",
+    "\n",
+    "cluster.scale(16)\n",
+    "client = cluster.get_client()\n",
+    "client"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "c685e048-e3b3-4006-ae78-d307773feac7",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#cluster.close()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "03149eca-424e-462b-8b5c-232fd68ccf02",
+   "metadata": {},
+   "source": [
+    "# Define a function to download the files and run h5stat"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "c8096edc-4ecc-4c32-a900-7cc3e0e64a27",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def process_file(collection: dict):\n",
+    "    s3 = boto3.resource('s3')\n",
+    "    dataset_dict = {}\n",
+    "    earthaccess.login(strategy=\"environment\")\n",
+    "    short_name, version, data_center = collection['short_name'], collection['version_id'], collection['data_center']\n",
+    "    if data_center == 'NSIDC_CPRD':\n",
+    "        data_center = 'NSIDC'\n",
+    "    if data_center == 'LPCLOUD':\n",
+    "        data_center = 'LPDAAC'\n",
+    "    if data_center == 'POCLOUD':\n",
+    "        data_center = 'PODAAC'\n",
+    "    if data_center == 'OB_CLOUD':\n",
+    "        data_center = 'OBDAAC'\n",
+    "    if data_center == 'ORNL_CLOUD':\n",
+    "        data_center = 'ORNLDAAC'\n",
+    "    if data_center == 'GHRC_DAAC':\n",
+    "        data_center = 'GHRCDAAC'\n",
+    "\n",
+    "    try: \n",
+    "        daac_credentials = earthaccess.get_s3_credentials(daac=data_center)\n",
+    "    \n",
+    "        # get 1 result\n",
+    "        results = earthaccess.search_data(\n",
+    "            short_name=short_name,\n",
+    "            cloud_hosted=True,\n",
+    "            version=version,\n",
+    "            count=1\n",
+    "        )\n",
+    "        data_link = results[0].data_links(access=\"direct\")[0]\n",
+    "    \n",
+    "        source_session = boto3.Session(\n",
+    "            aws_access_key_id=daac_credentials['accessKeyId'],\n",
+    "            aws_secret_access_key=daac_credentials['secretAccessKey'],\n",
+    "            aws_session_token=daac_credentials['sessionToken']\n",
+    "        )\n",
+    "        source_s3 = source_session.client('s3')\n",
+    "        \n",
+    "        # Define the source bucket and key\n",
+    "        source_bucket_name = data_link.split('/')[2]\n",
+    "        source_key = data_link.split(source_bucket_name + '/')[1]\n",
+    "    \n",
+    "        filename = source_key.split('/')[-1]\n",
+    "\n",
+    "\n",
+    "        # Step 2: Download file, run h5stat and return results\n",
+    "        if os.path.exists(filename):\n",
+    "            print(f\"The {filename} already been downloaded.\")\n",
+    "        else:\n",
+    "            source_s3.download_file(source_bucket_name, source_key, filename)\n",
+    "        dataset_dict[filename] = {\n",
+    "            'collection': short_name,\n",
+    "            'version': version,\n",
+    "            'direct_link': data_link,\n",
+    "            'filename': filename,\n",
+    "            # note: just added this, not present in current version of output\n",
+    "            'data_center': data_center\n",
+    "        }    \n",
+    "        # Function to parse the h5stat output\n",
+    "        def parse_h5stat_output(output):\n",
+    "            # Regular expressions to find file space management strategy and page size\n",
+    "            fsm_strategy_pattern = r\"File space management strategy:\\s+(\\w+)\"\n",
+    "            page_size_pattern = r\"File space page size:\\s+(\\d+)\"\n",
+    "        \n",
+    "            # Search for file space management strategy\n",
+    "            fsm_strategy_match = re.search(fsm_strategy_pattern, output)\n",
+    "            fsm_strategy = fsm_strategy_match.group(1) if fsm_strategy_match else \"Not found\"\n",
+    "        \n",
+    "            # Search for file space page size\n",
+    "            page_size_match = re.search(page_size_pattern, output)\n",
+    "            page_size = page_size_match.group(1) if page_size_match else \"Not found\"\n",
+    "        \n",
+    "            return fsm_strategy, page_size\n",
+    "\n",
+    "        try:\n",
+    "            result = subprocess.run(['h5stat', filename], capture_output=True, text=True, check=True)\n",
+    "            output = result.stdout\n",
+    "        except subprocess.CalledProcessError as e:\n",
+    "            # print(f\"Failed to run h5stat: {e}, perhaps this file is not hdf5?\")\n",
+    "            output = \"\"\n",
+    "        \n",
+    "        fsm_strategy, page_size = parse_h5stat_output(output)\n",
+    "        dataset_dict[filename]['fsm_strategy'] = fsm_strategy\n",
+    "        dataset_dict[filename]['page_size'] = page_size\n",
+    "        os.remove(filename)\n",
+    "        return dataset_dict\n",
+    "    except Exception as e:\n",
+    "        return f\"Caught exception {e} while trying to process file from collection {short_name}, version {version}\"\n",
+    "    "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c699ad34-30db-489e-a9e4-3617b5b6887a",
+   "metadata": {},
+   "source": [
+    "# Run the function on Dask"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "c21935ab-5488-47a3-97b6-1e5b6dbbf631",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/srv/conda/envs/notebook/lib/python3.11/site-packages/distributed/client.py:3157: UserWarning: Sending large graph of size 11.66 MiB.\n",
+      "This may cause some slowdown.\n",
+      "Consider scattering data ahead of time and using futures.\n",
+      "  warnings.warn(\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: user 5.99 s, sys: 389 ms, total: 6.38 s\n",
+      "Wall time: 35min 4s\n"
+     ]
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "bag = db.from_sequence(collections, partition_size=1)\n",
+    "result = db.map(process_file, bag)\n",
+    "all_files = result.compute()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "affd9da0-7655-4662-8db1-0420a0a8e1ca",
+   "metadata": {},
+   "source": [
+    "And write the output."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "963e39aa-e0c9-47b8-bab3-9934bc14d6a1",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import json\n",
+    "with open('hdf_cmr_query_results.json', 'w+') as f:\n",
+    "    f.write(json.dumps(all_files))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "7e0be7fc-b5c5-4a3f-8659-78e969257f25",
+   "metadata": {},
+   "source": [
+    "# Plot paged aggregation and page size"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "531cfe29-0d42-4a6d-a669-80df770c956c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "data_json = json.loads(open('hdf_cmr_query_results.json', 'r').read())\n",
+    "# remove some which had errors\n",
+    "filtered_list = [list(item.values())[0] for item in data_json if isinstance(item, dict)]\n",
+    "df = pd.DataFrame(data=filtered_list)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 71,
+   "id": "872bbb46-d5d1-4d7d-ab59-d459ce5a54d0",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>collection</th>\n",
+       "      <th>version</th>\n",
+       "      <th>direct_link</th>\n",
+       "      <th>filename</th>\n",
+       "      <th>fsm_strategy</th>\n",
+       "      <th>page_size</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>ATL03</td>\n",
+       "      <td>006</td>\n",
+       "      <td>s3://nsidc-cumulus-prod-protected/ATLAS/ATL03/...</td>\n",
+       "      <td>ATL03_20181014000347_02350101_006_02.h5</td>\n",
+       "      <td>H5F_FSPACE_STRATEGY_FSM_AGGR</td>\n",
+       "      <td>4096</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>ATL08</td>\n",
+       "      <td>006</td>\n",
+       "      <td>s3://nsidc-cumulus-prod-protected/ATLAS/ATL08/...</td>\n",
+       "      <td>ATL08_20181014001049_02350102_006_02.h5</td>\n",
+       "      <td>H5F_FSPACE_STRATEGY_FSM_AGGR</td>\n",
+       "      <td>4096</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>AIRIBRAD</td>\n",
+       "      <td>005</td>\n",
+       "      <td>s3://gesdisc-cumulus-prod-protected/Aqua_AIRS_...</td>\n",
+       "      <td>AIRS.2002.08.30.225.L1B.AIRS_Rad.v5.0.0.0.G071...</td>\n",
+       "      <td>Not found</td>\n",
+       "      <td>Not found</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>OMVFPITMET</td>\n",
+       "      <td>003</td>\n",
+       "      <td>s3://gesdisc-cumulus-prod-protected/Aura_OMI_L...</td>\n",
+       "      <td>OMI-Aura_ANC-OMVFPITMET_2004m1001t000305-o0113...</td>\n",
+       "      <td>H5F_FSPACE_STRATEGY_FSM_AGGR</td>\n",
+       "      <td>4096</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>OMUFPITMET</td>\n",
+       "      <td>003</td>\n",
+       "      <td>s3://gesdisc-cumulus-prod-protected/Aura_OMI_L...</td>\n",
+       "      <td>OMI-Aura_ANC-OMUFPITMET_2004m1001t000305-o0113...</td>\n",
+       "      <td>H5F_FSPACE_STRATEGY_FSM_AGGR</td>\n",
+       "      <td>4096</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   collection version                                        direct_link  \\\n",
+       "0       ATL03     006  s3://nsidc-cumulus-prod-protected/ATLAS/ATL03/...   \n",
+       "1       ATL08     006  s3://nsidc-cumulus-prod-protected/ATLAS/ATL08/...   \n",
+       "2    AIRIBRAD     005  s3://gesdisc-cumulus-prod-protected/Aqua_AIRS_...   \n",
+       "3  OMVFPITMET     003  s3://gesdisc-cumulus-prod-protected/Aura_OMI_L...   \n",
+       "4  OMUFPITMET     003  s3://gesdisc-cumulus-prod-protected/Aura_OMI_L...   \n",
+       "\n",
+       "                                            filename  \\\n",
+       "0            ATL03_20181014000347_02350101_006_02.h5   \n",
+       "1            ATL08_20181014001049_02350102_006_02.h5   \n",
+       "2  AIRS.2002.08.30.225.L1B.AIRS_Rad.v5.0.0.0.G071...   \n",
+       "3  OMI-Aura_ANC-OMVFPITMET_2004m1001t000305-o0113...   \n",
+       "4  OMI-Aura_ANC-OMUFPITMET_2004m1001t000305-o0113...   \n",
+       "\n",
+       "                   fsm_strategy  page_size  \n",
+       "0  H5F_FSPACE_STRATEGY_FSM_AGGR       4096  \n",
+       "1  H5F_FSPACE_STRATEGY_FSM_AGGR       4096  \n",
+       "2                     Not found  Not found  \n",
+       "3  H5F_FSPACE_STRATEGY_FSM_AGGR       4096  \n",
+       "4  H5F_FSPACE_STRATEGY_FSM_AGGR       4096  "
+      ]
+     },
+     "execution_count": 71,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "f6a92a88-11a2-426c-9b00-487f17bb75f6",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "There are 2390 collections which were successfully downloaded.\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(f\"There are {len(df)} collections which were successfully downloaded.\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "34b80ffc-c335-40c1-9541-8b584b1b81aa",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "`h5stat` failed on 472 collections. These may not be hdf5.\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(f\"`h5stat` failed on {len(df[df['page_size'] == 'Not found'])} collections. These may not be hdf5.\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "82eb8bf4-2ef8-44da-90e5-02fdbc9321c1",
+   "metadata": {},
+   "source": [
+    "# Plot results "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "6ec46b13-c018-4dfb-a91a-dd5e84a1a22d",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "column_data = df['fsm_strategy']\n",
+    "plt.hist(column_data, bins=3, color='skyblue', alpha=0.7)\n",
+    "plt.title('File Space Management Strategy')\n",
+    "plt.xlabel('File Space Management Strategy')\n",
+    "plt.ylabel('Frequency')\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "3451eb6d-2a3b-43da-ba2e-0e1f3d0c8428",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "column_data = df['page_size']\n",
+    "plt.hist(column_data, bins=3, color='blue', alpha=0.7)\n",
+    "plt.title('Page Size')\n",
+    "plt.xlabel('Page Size')\n",
+    "plt.ylabel('Frequency')\n",
+    "plt.show()"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.8"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/notebooks/replicate-results-research/02-reformat.ipynb b/notebooks/replicate-results-research/02-reformat.ipynb
new file mode 100644
index 0000000..ac83e19
--- /dev/null
+++ b/notebooks/replicate-results-research/02-reformat.ipynb
@@ -0,0 +1,732 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "f4fb7c91-ed61-4b61-9e4f-15aae01b06be",
+   "metadata": {},
+   "source": [
+    "# 02 - Creating New Optimized Versions of High-Value NASA Datasets\n",
+    "\n",
+    "Below we build upon the work in check-co-hdf5-cmr.ipynb to build optimized versions of the data and a config file for testing with libraries. \n",
+    "\n",
+    "* repacked\n",
+    "* kerchunk original\n",
+    "* kerchunk repacked\n",
+    "\n",
+    "To simplify this evaluation, we only use datasets which VEDA Hub has access to (which is most of the most highly used data sets).\n",
+    "\n",
+    "Datasets skipped:\n",
+    "* if fsm_strategy and page_size were not found, likely this collection is not made up of valid HDF5 files\n",
+    "* oco2_L1aInSB_00018a_140703_B11000r_220105200708.h5 - compled data structure, not sure where to find data variables\n",
+    "* VNP03IMG.A2012019.0000.002.2020318135750.nc - don't have access to this bucket yet"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "62d23930-d0b4-4ba1-8e34-6122f5301e5c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import boto3\n",
+    "import fsspec\n",
+    "import inspect\n",
+    "import json\n",
+    "from kerchunk.hdf import SingleHdf5ToZarr\n",
+    "import pandas as pd\n",
+    "import subprocess\n",
+    "import yaml"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f1cfc980-5468-41af-b2f9-1684e0726813",
+   "metadata": {},
+   "source": [
+    "# Define reprocessing functions"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "9322745b-b308-4690-878c-b7f151dfa406",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "fs_read = fsspec.filesystem(\"s3\", anon=False)\n",
+    "\n",
+    "def generate_json_reference(in_filename, out_filename):\n",
+    "    so = dict(mode=\"rb\", default_fill_cache=False, default_cache_type=\"first\")\n",
+    "    with fs_read.open(in_filename, **so) as infile:     \n",
+    "        h5chunks = SingleHdf5ToZarr(in_filename)\n",
+    "        suffix = out_filename.split(\".\")[-1]\n",
+    "        out_filename = out_filename.replace(suffix, 'json')\n",
+    "        with open(out_filename, 'w') as outfile:\n",
+    "            outfile.write(json.dumps(h5chunks.translate()))\n",
+    "        return out_filename"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "d98ad515-2e2f-4a03-9909-b89651e5403c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "processing_options = {\n",
+    "    \"original\": {\n",
+    "        \"procssing\": None,\n",
+    "        \"input_file\": None,\n",
+    "        \"link\": None\n",
+    "    },\n",
+    "    \"repacked_page_4mb\": {\n",
+    "        \"processing\": \"h5repack -S PAGE -G 4000000\",\n",
+    "        \"input_file\": \"original\",\n",
+    "        \"link\": None\n",
+    "    },   \n",
+    "    \"kerchunk\": {\n",
+    "        \"processing\": generate_json_reference,\n",
+    "        \"input_file\": \"original\",\n",
+    "        \"link\": None\n",
+    "    },\n",
+    "    \"kerchunk_repacked_page_4mb\": {\n",
+    "        \"processing\": generate_json_reference,\n",
+    "        \"input_file\": \"repacked_page_4mb\",\n",
+    "        \"link\": None\n",
+    "    }\n",
+    "}"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "24c32020-d633-4dec-80db-b46312eff957",
+   "metadata": {},
+   "source": [
+    "# Open file with HDF5/NetCDF-4 collections"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "56b780f6-8072-47be-98a0-e29385ba2c91",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "data_json = json.loads(open('hdf_cmr_query_results.json', 'r').read())\n",
+    "# remove some which had errors\n",
+    "filtered_list = [list(item.values())[0] for item in data_json if isinstance(item, dict)]\n",
+    "df = pd.DataFrame(data=filtered_list)\n",
+    "df = df.set_index('filename')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "5a601fa5-bd11-4af9-b8a5-796586dc2566",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>collection</th>\n",
+       "      <th>version</th>\n",
+       "      <th>direct_link</th>\n",
+       "      <th>data_center</th>\n",
+       "      <th>fsm_strategy</th>\n",
+       "      <th>page_size</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>filename</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>ATL03_20181014000347_02350101_006_02.h5</th>\n",
+       "      <td>ATL03</td>\n",
+       "      <td>006</td>\n",
+       "      <td>s3://nsidc-cumulus-prod-protected/ATLAS/ATL03/...</td>\n",
+       "      <td>NSIDC</td>\n",
+       "      <td>H5F_FSPACE_STRATEGY_FSM_AGGR</td>\n",
+       "      <td>4096</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ATL08_20181014001049_02350102_006_02.h5</th>\n",
+       "      <td>ATL08</td>\n",
+       "      <td>006</td>\n",
+       "      <td>s3://nsidc-cumulus-prod-protected/ATLAS/ATL08/...</td>\n",
+       "      <td>NSIDC</td>\n",
+       "      <td>H5F_FSPACE_STRATEGY_FSM_AGGR</td>\n",
+       "      <td>4096</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>AIRS.2002.08.30.225.L1B.AIRS_Rad.v5.0.0.0.G07143184358.hdf</th>\n",
+       "      <td>AIRIBRAD</td>\n",
+       "      <td>005</td>\n",
+       "      <td>s3://gesdisc-cumulus-prod-protected/Aqua_AIRS_...</td>\n",
+       "      <td>GES_DISC</td>\n",
+       "      <td>Not found</td>\n",
+       "      <td>Not found</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>OMI-Aura_ANC-OMVFPITMET_2004m1001t000305-o01132_v003-2018m1015t140716.nc4</th>\n",
+       "      <td>OMVFPITMET</td>\n",
+       "      <td>003</td>\n",
+       "      <td>s3://gesdisc-cumulus-prod-protected/Aura_OMI_L...</td>\n",
+       "      <td>GES_DISC</td>\n",
+       "      <td>H5F_FSPACE_STRATEGY_FSM_AGGR</td>\n",
+       "      <td>4096</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>OMI-Aura_ANC-OMUFPITMET_2004m1001t000305-o01132_v003-2018m1015t140708.nc4</th>\n",
+       "      <td>OMUFPITMET</td>\n",
+       "      <td>003</td>\n",
+       "      <td>s3://gesdisc-cumulus-prod-protected/Aura_OMI_L...</td>\n",
+       "      <td>GES_DISC</td>\n",
+       "      <td>H5F_FSPACE_STRATEGY_FSM_AGGR</td>\n",
+       "      <td>4096</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>SNDR.SNPP.CRIMSS.20120120T1254.m06.g130.L2_CLIMCAPS_RET_NSR.std.v02_28.G.200409132855.nc</th>\n",
+       "      <td>SNDRSNIML2CCPRETN</td>\n",
+       "      <td>2</td>\n",
+       "      <td>s3://gesdisc-cumulus-prod-protected/SNPP_Sound...</td>\n",
+       "      <td>GES_DISC</td>\n",
+       "      <td>H5F_FSPACE_STRATEGY_FSM_AGGR</td>\n",
+       "      <td>4096</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>oco2_L1aInSB_00018a_140703_B11000r_220105200708.h5</th>\n",
+       "      <td>OCO2_L1aIn_Sample</td>\n",
+       "      <td>11r</td>\n",
+       "      <td>s3://gesdisc-cumulus-prod-protected/OCO2_DATA/...</td>\n",
+       "      <td>GES_DISC</td>\n",
+       "      <td>H5F_FSPACE_STRATEGY_FSM_AGGR</td>\n",
+       "      <td>4096</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2A23.19980101.00538.7.HDF</th>\n",
+       "      <td>TRMM_2A23</td>\n",
+       "      <td>7</td>\n",
+       "      <td>s3://gesdisc-cumulus-prod-protected/TRMM_L2/TR...</td>\n",
+       "      <td>GES_DISC</td>\n",
+       "      <td>Not found</td>\n",
+       "      <td>Not found</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3B-HHR-E.MS.MRG.3IMERG.20000601-S000000-E002959.0000.V06B.HDF5</th>\n",
+       "      <td>GPM_3IMERGHHE</td>\n",
+       "      <td>06</td>\n",
+       "      <td>s3://gesdisc-cumulus-prod-protected/GPM_L3/GPM...</td>\n",
+       "      <td>GES_DISC</td>\n",
+       "      <td>H5F_FSPACE_STRATEGY_FSM_AGGR</td>\n",
+       "      <td>4096</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>SNDR.SNPP.ATMS.20111210T0154.m06.g020.L1B.std.v03_15.G.210527141305.nc</th>\n",
+       "      <td>SNPPATMSL1B</td>\n",
+       "      <td>3</td>\n",
+       "      <td>s3://gesdisc-cumulus-prod-protected/SNPP_Sound...</td>\n",
+       "      <td>GES_DISC</td>\n",
+       "      <td>H5F_FSPACE_STRATEGY_FSM_AGGR</td>\n",
+       "      <td>4096</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>AIRS.2002.08.30.225.L2.CC.v6.0.7.0.G13201091521.hdf</th>\n",
+       "      <td>AIRI2CCF</td>\n",
+       "      <td>006</td>\n",
+       "      <td>s3://gesdisc-cumulus-prod-protected/Aqua_AIRS_...</td>\n",
+       "      <td>GES_DISC</td>\n",
+       "      <td>Not found</td>\n",
+       "      <td>Not found</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>VNP03IMG.A2012019.0000.002.2020318135750.nc</th>\n",
+       "      <td>VNP03IMG</td>\n",
+       "      <td>2</td>\n",
+       "      <td>s3://prod-lads/VNP03IMG/VNP03IMG.A2012019.0000...</td>\n",
+       "      <td>LAADS</td>\n",
+       "      <td>H5F_FSPACE_STRATEGY_FSM_AGGR</td>\n",
+       "      <td>4096</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>OMI-Aura_L2-OMOCLO_2004m1001t0003-o01132_v003-2014m0511t173655.he5</th>\n",
+       "      <td>OMOCLO</td>\n",
+       "      <td>003</td>\n",
+       "      <td>s3://gesdisc-cumulus-prod-protected/Aura_OMI_L...</td>\n",
+       "      <td>GES_DISC</td>\n",
+       "      <td>H5F_FSPACE_STRATEGY_FSM_AGGR</td>\n",
+       "      <td>4096</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>merg_1998010100_4km-pixel.nc4</th>\n",
+       "      <td>GPM_MERGIR</td>\n",
+       "      <td>1</td>\n",
+       "      <td>s3://gesdisc-cumulus-prod-protected/MERGED_IR/...</td>\n",
+       "      <td>GES_DISC</td>\n",
+       "      <td>H5F_FSPACE_STRATEGY_FSM_AGGR</td>\n",
+       "      <td>4096</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>oco2_L2ABPND_00958a_140906_B10003r_191217022608.h5</th>\n",
+       "      <td>OCO2_L2_ABand</td>\n",
+       "      <td>10r</td>\n",
+       "      <td>s3://gesdisc-cumulus-prod-protected/OCO2_DATA/...</td>\n",
+       "      <td>GES_DISC</td>\n",
+       "      <td>H5F_FSPACE_STRATEGY_FSM_AGGR</td>\n",
+       "      <td>4096</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3B42.19980101.00.7.HDF</th>\n",
+       "      <td>TRMM_3B42</td>\n",
+       "      <td>7</td>\n",
+       "      <td>s3://gesdisc-cumulus-prod-protected/TRMM_L3/TR...</td>\n",
+       "      <td>GES_DISC</td>\n",
+       "      <td>Not found</td>\n",
+       "      <td>Not found</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>SNDR.J1.ATMS.20171211T0254.m06.g030.L1B.std.v03_15.G.210526105607.nc</th>\n",
+       "      <td>SNDRJ1ATMSL1B</td>\n",
+       "      <td>3</td>\n",
+       "      <td>s3://gesdisc-cumulus-prod-protected/JPSS1_Soun...</td>\n",
+       "      <td>GES_DISC</td>\n",
+       "      <td>H5F_FSPACE_STRATEGY_FSM_AGGR</td>\n",
+       "      <td>4096</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>OMI-Aura_L2-OMMYDCLD_2004m1001t0003-o01132_v003-2018m0906t095826.he5</th>\n",
+       "      <td>OMMYDCLD</td>\n",
+       "      <td>003</td>\n",
+       "      <td>s3://gesdisc-cumulus-prod-protected/Aura_OMI_L...</td>\n",
+       "      <td>GES_DISC</td>\n",
+       "      <td>H5F_FSPACE_STRATEGY_FSM_AGGR</td>\n",
+       "      <td>4096</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1C21.19971208.00160.7.HDF</th>\n",
+       "      <td>TRMM_1C21</td>\n",
+       "      <td>7</td>\n",
+       "      <td>s3://gesdisc-cumulus-prod-protected/TRMM_L1/TR...</td>\n",
+       "      <td>GES_DISC</td>\n",
+       "      <td>Not found</td>\n",
+       "      <td>Not found</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>OMI-Aura_L2-OMBRO_2004m0826t2157-o00621_v003-2014m0331t182425.he5</th>\n",
+       "      <td>OMBRO</td>\n",
+       "      <td>003</td>\n",
+       "      <td>s3://gesdisc-cumulus-prod-protected/Aura_OMI_L...</td>\n",
+       "      <td>GES_DISC</td>\n",
+       "      <td>H5F_FSPACE_STRATEGY_FSM_AGGR</td>\n",
+       "      <td>4096</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                                           collection version  \\\n",
+       "filename                                                                        \n",
+       "ATL03_20181014000347_02350101_006_02.h5                         ATL03     006   \n",
+       "ATL08_20181014001049_02350102_006_02.h5                         ATL08     006   \n",
+       "AIRS.2002.08.30.225.L1B.AIRS_Rad.v5.0.0.0.G0714...           AIRIBRAD     005   \n",
+       "OMI-Aura_ANC-OMVFPITMET_2004m1001t000305-o01132...         OMVFPITMET     003   \n",
+       "OMI-Aura_ANC-OMUFPITMET_2004m1001t000305-o01132...         OMUFPITMET     003   \n",
+       "SNDR.SNPP.CRIMSS.20120120T1254.m06.g130.L2_CLIM...  SNDRSNIML2CCPRETN       2   \n",
+       "oco2_L1aInSB_00018a_140703_B11000r_220105200708.h5  OCO2_L1aIn_Sample     11r   \n",
+       "2A23.19980101.00538.7.HDF                                   TRMM_2A23       7   \n",
+       "3B-HHR-E.MS.MRG.3IMERG.20000601-S000000-E002959...      GPM_3IMERGHHE      06   \n",
+       "SNDR.SNPP.ATMS.20111210T0154.m06.g020.L1B.std.v...        SNPPATMSL1B       3   \n",
+       "AIRS.2002.08.30.225.L2.CC.v6.0.7.0.G13201091521...           AIRI2CCF     006   \n",
+       "VNP03IMG.A2012019.0000.002.2020318135750.nc                  VNP03IMG       2   \n",
+       "OMI-Aura_L2-OMOCLO_2004m1001t0003-o01132_v003-2...             OMOCLO     003   \n",
+       "merg_1998010100_4km-pixel.nc4                              GPM_MERGIR       1   \n",
+       "oco2_L2ABPND_00958a_140906_B10003r_191217022608.h5      OCO2_L2_ABand     10r   \n",
+       "3B42.19980101.00.7.HDF                                      TRMM_3B42       7   \n",
+       "SNDR.J1.ATMS.20171211T0254.m06.g030.L1B.std.v03...      SNDRJ1ATMSL1B       3   \n",
+       "OMI-Aura_L2-OMMYDCLD_2004m1001t0003-o01132_v003...           OMMYDCLD     003   \n",
+       "1C21.19971208.00160.7.HDF                                   TRMM_1C21       7   \n",
+       "OMI-Aura_L2-OMBRO_2004m0826t2157-o00621_v003-20...              OMBRO     003   \n",
+       "\n",
+       "                                                                                          direct_link  \\\n",
+       "filename                                                                                                \n",
+       "ATL03_20181014000347_02350101_006_02.h5             s3://nsidc-cumulus-prod-protected/ATLAS/ATL03/...   \n",
+       "ATL08_20181014001049_02350102_006_02.h5             s3://nsidc-cumulus-prod-protected/ATLAS/ATL08/...   \n",
+       "AIRS.2002.08.30.225.L1B.AIRS_Rad.v5.0.0.0.G0714...  s3://gesdisc-cumulus-prod-protected/Aqua_AIRS_...   \n",
+       "OMI-Aura_ANC-OMVFPITMET_2004m1001t000305-o01132...  s3://gesdisc-cumulus-prod-protected/Aura_OMI_L...   \n",
+       "OMI-Aura_ANC-OMUFPITMET_2004m1001t000305-o01132...  s3://gesdisc-cumulus-prod-protected/Aura_OMI_L...   \n",
+       "SNDR.SNPP.CRIMSS.20120120T1254.m06.g130.L2_CLIM...  s3://gesdisc-cumulus-prod-protected/SNPP_Sound...   \n",
+       "oco2_L1aInSB_00018a_140703_B11000r_220105200708.h5  s3://gesdisc-cumulus-prod-protected/OCO2_DATA/...   \n",
+       "2A23.19980101.00538.7.HDF                           s3://gesdisc-cumulus-prod-protected/TRMM_L2/TR...   \n",
+       "3B-HHR-E.MS.MRG.3IMERG.20000601-S000000-E002959...  s3://gesdisc-cumulus-prod-protected/GPM_L3/GPM...   \n",
+       "SNDR.SNPP.ATMS.20111210T0154.m06.g020.L1B.std.v...  s3://gesdisc-cumulus-prod-protected/SNPP_Sound...   \n",
+       "AIRS.2002.08.30.225.L2.CC.v6.0.7.0.G13201091521...  s3://gesdisc-cumulus-prod-protected/Aqua_AIRS_...   \n",
+       "VNP03IMG.A2012019.0000.002.2020318135750.nc         s3://prod-lads/VNP03IMG/VNP03IMG.A2012019.0000...   \n",
+       "OMI-Aura_L2-OMOCLO_2004m1001t0003-o01132_v003-2...  s3://gesdisc-cumulus-prod-protected/Aura_OMI_L...   \n",
+       "merg_1998010100_4km-pixel.nc4                       s3://gesdisc-cumulus-prod-protected/MERGED_IR/...   \n",
+       "oco2_L2ABPND_00958a_140906_B10003r_191217022608.h5  s3://gesdisc-cumulus-prod-protected/OCO2_DATA/...   \n",
+       "3B42.19980101.00.7.HDF                              s3://gesdisc-cumulus-prod-protected/TRMM_L3/TR...   \n",
+       "SNDR.J1.ATMS.20171211T0254.m06.g030.L1B.std.v03...  s3://gesdisc-cumulus-prod-protected/JPSS1_Soun...   \n",
+       "OMI-Aura_L2-OMMYDCLD_2004m1001t0003-o01132_v003...  s3://gesdisc-cumulus-prod-protected/Aura_OMI_L...   \n",
+       "1C21.19971208.00160.7.HDF                           s3://gesdisc-cumulus-prod-protected/TRMM_L1/TR...   \n",
+       "OMI-Aura_L2-OMBRO_2004m0826t2157-o00621_v003-20...  s3://gesdisc-cumulus-prod-protected/Aura_OMI_L...   \n",
+       "\n",
+       "                                                   data_center  \\\n",
+       "filename                                                         \n",
+       "ATL03_20181014000347_02350101_006_02.h5                  NSIDC   \n",
+       "ATL08_20181014001049_02350102_006_02.h5                  NSIDC   \n",
+       "AIRS.2002.08.30.225.L1B.AIRS_Rad.v5.0.0.0.G0714...    GES_DISC   \n",
+       "OMI-Aura_ANC-OMVFPITMET_2004m1001t000305-o01132...    GES_DISC   \n",
+       "OMI-Aura_ANC-OMUFPITMET_2004m1001t000305-o01132...    GES_DISC   \n",
+       "SNDR.SNPP.CRIMSS.20120120T1254.m06.g130.L2_CLIM...    GES_DISC   \n",
+       "oco2_L1aInSB_00018a_140703_B11000r_220105200708.h5    GES_DISC   \n",
+       "2A23.19980101.00538.7.HDF                             GES_DISC   \n",
+       "3B-HHR-E.MS.MRG.3IMERG.20000601-S000000-E002959...    GES_DISC   \n",
+       "SNDR.SNPP.ATMS.20111210T0154.m06.g020.L1B.std.v...    GES_DISC   \n",
+       "AIRS.2002.08.30.225.L2.CC.v6.0.7.0.G13201091521...    GES_DISC   \n",
+       "VNP03IMG.A2012019.0000.002.2020318135750.nc              LAADS   \n",
+       "OMI-Aura_L2-OMOCLO_2004m1001t0003-o01132_v003-2...    GES_DISC   \n",
+       "merg_1998010100_4km-pixel.nc4                         GES_DISC   \n",
+       "oco2_L2ABPND_00958a_140906_B10003r_191217022608.h5    GES_DISC   \n",
+       "3B42.19980101.00.7.HDF                                GES_DISC   \n",
+       "SNDR.J1.ATMS.20171211T0254.m06.g030.L1B.std.v03...    GES_DISC   \n",
+       "OMI-Aura_L2-OMMYDCLD_2004m1001t0003-o01132_v003...    GES_DISC   \n",
+       "1C21.19971208.00160.7.HDF                             GES_DISC   \n",
+       "OMI-Aura_L2-OMBRO_2004m0826t2157-o00621_v003-20...    GES_DISC   \n",
+       "\n",
+       "                                                                    fsm_strategy  \\\n",
+       "filename                                                                           \n",
+       "ATL03_20181014000347_02350101_006_02.h5             H5F_FSPACE_STRATEGY_FSM_AGGR   \n",
+       "ATL08_20181014001049_02350102_006_02.h5             H5F_FSPACE_STRATEGY_FSM_AGGR   \n",
+       "AIRS.2002.08.30.225.L1B.AIRS_Rad.v5.0.0.0.G0714...                     Not found   \n",
+       "OMI-Aura_ANC-OMVFPITMET_2004m1001t000305-o01132...  H5F_FSPACE_STRATEGY_FSM_AGGR   \n",
+       "OMI-Aura_ANC-OMUFPITMET_2004m1001t000305-o01132...  H5F_FSPACE_STRATEGY_FSM_AGGR   \n",
+       "SNDR.SNPP.CRIMSS.20120120T1254.m06.g130.L2_CLIM...  H5F_FSPACE_STRATEGY_FSM_AGGR   \n",
+       "oco2_L1aInSB_00018a_140703_B11000r_220105200708.h5  H5F_FSPACE_STRATEGY_FSM_AGGR   \n",
+       "2A23.19980101.00538.7.HDF                                              Not found   \n",
+       "3B-HHR-E.MS.MRG.3IMERG.20000601-S000000-E002959...  H5F_FSPACE_STRATEGY_FSM_AGGR   \n",
+       "SNDR.SNPP.ATMS.20111210T0154.m06.g020.L1B.std.v...  H5F_FSPACE_STRATEGY_FSM_AGGR   \n",
+       "AIRS.2002.08.30.225.L2.CC.v6.0.7.0.G13201091521...                     Not found   \n",
+       "VNP03IMG.A2012019.0000.002.2020318135750.nc         H5F_FSPACE_STRATEGY_FSM_AGGR   \n",
+       "OMI-Aura_L2-OMOCLO_2004m1001t0003-o01132_v003-2...  H5F_FSPACE_STRATEGY_FSM_AGGR   \n",
+       "merg_1998010100_4km-pixel.nc4                       H5F_FSPACE_STRATEGY_FSM_AGGR   \n",
+       "oco2_L2ABPND_00958a_140906_B10003r_191217022608.h5  H5F_FSPACE_STRATEGY_FSM_AGGR   \n",
+       "3B42.19980101.00.7.HDF                                                 Not found   \n",
+       "SNDR.J1.ATMS.20171211T0254.m06.g030.L1B.std.v03...  H5F_FSPACE_STRATEGY_FSM_AGGR   \n",
+       "OMI-Aura_L2-OMMYDCLD_2004m1001t0003-o01132_v003...  H5F_FSPACE_STRATEGY_FSM_AGGR   \n",
+       "1C21.19971208.00160.7.HDF                                              Not found   \n",
+       "OMI-Aura_L2-OMBRO_2004m0826t2157-o00621_v003-20...  H5F_FSPACE_STRATEGY_FSM_AGGR   \n",
+       "\n",
+       "                                                    page_size  \n",
+       "filename                                                       \n",
+       "ATL03_20181014000347_02350101_006_02.h5                  4096  \n",
+       "ATL08_20181014001049_02350102_006_02.h5                  4096  \n",
+       "AIRS.2002.08.30.225.L1B.AIRS_Rad.v5.0.0.0.G0714...  Not found  \n",
+       "OMI-Aura_ANC-OMVFPITMET_2004m1001t000305-o01132...       4096  \n",
+       "OMI-Aura_ANC-OMUFPITMET_2004m1001t000305-o01132...       4096  \n",
+       "SNDR.SNPP.CRIMSS.20120120T1254.m06.g130.L2_CLIM...       4096  \n",
+       "oco2_L1aInSB_00018a_140703_B11000r_220105200708.h5       4096  \n",
+       "2A23.19980101.00538.7.HDF                           Not found  \n",
+       "3B-HHR-E.MS.MRG.3IMERG.20000601-S000000-E002959...       4096  \n",
+       "SNDR.SNPP.ATMS.20111210T0154.m06.g020.L1B.std.v...       4096  \n",
+       "AIRS.2002.08.30.225.L2.CC.v6.0.7.0.G13201091521...  Not found  \n",
+       "VNP03IMG.A2012019.0000.002.2020318135750.nc              4096  \n",
+       "OMI-Aura_L2-OMOCLO_2004m1001t0003-o01132_v003-2...       4096  \n",
+       "merg_1998010100_4km-pixel.nc4                            4096  \n",
+       "oco2_L2ABPND_00958a_140906_B10003r_191217022608.h5       4096  \n",
+       "3B42.19980101.00.7.HDF                              Not found  \n",
+       "SNDR.J1.ATMS.20171211T0254.m06.g030.L1B.std.v03...       4096  \n",
+       "OMI-Aura_L2-OMMYDCLD_2004m1001t0003-o01132_v003...       4096  \n",
+       "1C21.19971208.00160.7.HDF                           Not found  \n",
+       "OMI-Aura_L2-OMBRO_2004m0826t2157-o00621_v003-20...       4096  "
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df[0:20]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "cca25207-fc9c-46a4-a3a4-ec2832b3a76b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "file_key = 'SNDR.SNPP.CRIMSS.20120120T1254.m06.g130.L2_CLIMCAPS_RET_NSR.std.v02_28.G.200409132855.nc'\n",
+    "file_data = df.loc[file_key]\n",
+    "short_name, version, direct_link = file_data.collection, file_data.version, file_data.direct_link\n",
+    "processing_options[\"original\"][\"link\"] = direct_link"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "fa6524d7-523d-4891-bb10-76c6c73b2ba5",
+   "metadata": {},
+   "source": [
+    "# Reprocess and upload\n",
+    "\n",
+    "For each reprocessing option, run the reprocessing option on the input file and then upload the file and it's processing to S3."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "550db8a7-4c57-4d93-a0c5-bd4a5a9de9b4",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Uploading original to s3://nasa-veda-scratch/eodc_hdf5_experiments/SNDRSNIML2CCPRETN___2/original/SNDR.SNPP.CRIMSS.20120120T1254.m06.g130.L2_CLIMCAPS_RET_NSR.std.v02_28.G.200409132855.nc\n",
+      "Processing h5repack -S PAGE -G 4000000 on s3://nasa-veda-scratch/eodc_hdf5_experiments/SNDRSNIML2CCPRETN___2/original/SNDR.SNPP.CRIMSS.20120120T1254.m06.g130.L2_CLIMCAPS_RET_NSR.std.v02_28.G.200409132855.nc\n",
+      "Processing complete, uploading file to s3://nasa-veda-scratch/eodc_hdf5_experiments/SNDRSNIML2CCPRETN___2/repacked_page_4mb___SNDR.SNPP.CRIMSS.20120120T1254.m06.g130.L2_CLIMCAPS_RET_NSR.std.v02_28.G.200409132855.nc\n",
+      "Uploading processing cmd to s3://nasa-veda-scratch/eodc_hdf5_experiments/SNDRSNIML2CCPRETN___2/repacked_page_4mb_processing.txt\n",
+      "\n",
+      "Processing <function generate_json_reference at 0x7f2c6e9d8c20> on s3://nasa-veda-scratch/eodc_hdf5_experiments/SNDRSNIML2CCPRETN___2/original/SNDR.SNPP.CRIMSS.20120120T1254.m06.g130.L2_CLIMCAPS_RET_NSR.std.v02_28.G.200409132855.nc\n",
+      "Processing complete, uploading file to s3://nasa-veda-scratch/eodc_hdf5_experiments/SNDRSNIML2CCPRETN___2/kerchunk___SNDR.SNPP.CRIMSS.20120120T1254.m06.g130.L2_CLIMCAPS_RET_NSR.std.v02_28.G.200409132855.json\n",
+      "Uploading processing cmd to s3://nasa-veda-scratch/eodc_hdf5_experiments/SNDRSNIML2CCPRETN___2/kerchunk_processing.txt\n",
+      "\n",
+      "Processing <function generate_json_reference at 0x7f2c6e9d8c20> on s3://nasa-veda-scratch/eodc_hdf5_experiments/SNDRSNIML2CCPRETN___2/repacked_page_4mb___SNDR.SNPP.CRIMSS.20120120T1254.m06.g130.L2_CLIMCAPS_RET_NSR.std.v02_28.G.200409132855.nc\n",
+      "Processing complete, uploading file to s3://nasa-veda-scratch/eodc_hdf5_experiments/SNDRSNIML2CCPRETN___2/kerchunk_repacked_page_4mb___SNDR.SNPP.CRIMSS.20120120T1254.m06.g130.L2_CLIMCAPS_RET_NSR.std.v02_28.G.200409132855.json\n",
+      "Uploading processing cmd to s3://nasa-veda-scratch/eodc_hdf5_experiments/SNDRSNIML2CCPRETN___2/kerchunk_repacked_page_4mb_processing.txt\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "destination_bucket_name = 'nasa-veda-scratch'\n",
+    "destination_directory = f'eodc_hdf5_experiments/{short_name}___{version}'\n",
+    "s3_resource = boto3.resource('s3')\n",
+    "s3_client = boto3.client('s3')\n",
+    "for processing_option, processing_data in processing_options.items():\n",
+    "    if processing_option == 'original':   \n",
+    "        # Just copy the file\n",
+    "        print(f\"Uploading original to s3://{destination_bucket_name}/{destination_directory}/original/{file_key}\")\n",
+    "        source_bucket = direct_link.split(\"/\")[2]\n",
+    "        copy_source = {\n",
+    "            'Bucket': source_bucket,\n",
+    "            'Key': direct_link.split(f\"{source_bucket}/\")[-1]\n",
+    "        } \n",
+    "        s3_client.copy(copy_source, destination_bucket_name, f\"{destination_directory}/original/{file_key}\")\n",
+    "        processing_options['original']['link'] = f\"s3://{destination_bucket_name}/{destination_directory}/original/{file_key}\"\n",
+    "    else:\n",
+    "        processing_cmd = processing_data['processing']\n",
+    "        output_file = f\"{processing_option}___{file_key}\"\n",
+    "        input_file = processing_options[processing_data[\"input_file\"]][\"link\"]\n",
+    "        print(f\"Processing {processing_cmd} on {input_file}\")\n",
+    "        if type(processing_cmd) == str:\n",
+    "            cp_result = subprocess.run([\"aws\", \"s3\", \"cp\", direct_link, file_key], capture_output=True, text=True, check=True)\n",
+    "            processing_cmd_str = f\"{processing_cmd} {file_key} {output_file}\"\n",
+    "            process_result = subprocess.run(processing_cmd_str.split(\" \"), capture_output=True, text=True)\n",
+    "            # Check if there was an error\n",
+    "            if process_result.returncode != 0:\n",
+    "                print(\"Error:\", process_result.stderr)            \n",
+    "        elif callable(processing_cmd) == True:\n",
+    "            output_file = processing_cmd(input_file, output_file)\n",
+    "            processing_cmd_str = inspect.getsource(processing_cmd)\n",
+    "            # set it to a string so we can use it for test configuration later\n",
+    "            processing_options[processing_option]['processing'] = processing_cmd_str\n",
+    "        print(f\"Processing complete, uploading file to s3://{destination_bucket_name}/{destination_directory}/{output_file}\")\n",
+    "        destination_bucket = s3_resource.Bucket(destination_bucket_name)\n",
+    "        destination_bucket.upload_file(output_file,  f\"{destination_directory}/{output_file}\")\n",
+    "        processing_options[processing_option][\"link\"] = f\"s3://{destination_bucket_name}/{destination_directory}/{output_file}\"\n",
+    "        print(f\"Uploading processing cmd to s3://{destination_bucket_name}/{destination_directory}/{processing_option}_processing.txt\\n\")\n",
+    "        s3_client.put_object(\n",
+    "            Bucket=destination_bucket_name,\n",
+    "            Key=f\"{destination_directory}/{processing_option}_processing.txt\",\n",
+    "            Body=processing_cmd_str\n",
+    "        )"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "1199ff75-43fd-4ffd-bd6d-6d84fb2388d8",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'original': {'procssing': None,\n",
+       "  'input_file': None,\n",
+       "  'link': 's3://nasa-veda-scratch/eodc_hdf5_experiments/SNDRSNIML2CCPRETN___2/original/SNDR.SNPP.CRIMSS.20120120T1254.m06.g130.L2_CLIMCAPS_RET_NSR.std.v02_28.G.200409132855.nc'},\n",
+       " 'repacked_page_4mb': {'processing': 'h5repack -S PAGE -G 4000000',\n",
+       "  'input_file': 'original',\n",
+       "  'link': 's3://nasa-veda-scratch/eodc_hdf5_experiments/SNDRSNIML2CCPRETN___2/repacked_page_4mb___SNDR.SNPP.CRIMSS.20120120T1254.m06.g130.L2_CLIMCAPS_RET_NSR.std.v02_28.G.200409132855.nc'},\n",
+       " 'kerchunk': {'processing': 'def generate_json_reference(in_filename, out_filename):\\n    so = dict(mode=\"rb\", default_fill_cache=False, default_cache_type=\"first\")\\n    with fs_read.open(in_filename, **so) as infile:     \\n        h5chunks = SingleHdf5ToZarr(in_filename)\\n        suffix = out_filename.split(\".\")[-1]\\n        out_filename = out_filename.replace(suffix, \\'json\\')\\n        with open(out_filename, \\'w\\') as outfile:\\n            outfile.write(json.dumps(h5chunks.translate()))\\n        return out_filename\\n',\n",
+       "  'input_file': 'original',\n",
+       "  'link': 's3://nasa-veda-scratch/eodc_hdf5_experiments/SNDRSNIML2CCPRETN___2/kerchunk___SNDR.SNPP.CRIMSS.20120120T1254.m06.g130.L2_CLIMCAPS_RET_NSR.std.v02_28.G.200409132855.json'},\n",
+       " 'kerchunk_repacked_page_4mb': {'processing': 'def generate_json_reference(in_filename, out_filename):\\n    so = dict(mode=\"rb\", default_fill_cache=False, default_cache_type=\"first\")\\n    with fs_read.open(in_filename, **so) as infile:     \\n        h5chunks = SingleHdf5ToZarr(in_filename)\\n        suffix = out_filename.split(\".\")[-1]\\n        out_filename = out_filename.replace(suffix, \\'json\\')\\n        with open(out_filename, \\'w\\') as outfile:\\n            outfile.write(json.dumps(h5chunks.translate()))\\n        return out_filename\\n',\n",
+       "  'input_file': 'repacked_page_4mb',\n",
+       "  'link': 's3://nasa-veda-scratch/eodc_hdf5_experiments/SNDRSNIML2CCPRETN___2/kerchunk_repacked_page_4mb___SNDR.SNPP.CRIMSS.20120120T1254.m06.g130.L2_CLIMCAPS_RET_NSR.std.v02_28.G.200409132855.json'}}"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "processing_options"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ff1a1aa6-3f10-47a2-9802-81e6dbca38e7",
+   "metadata": {},
+   "source": [
+    "# Find a group and variable to test"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "f7d598d2-dcae-4420-a0a8-e54d162e38a7",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import h5py\n",
+    "h5file = h5py.File(file_key)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "497759ff-aa27-49e9-97c1-81e53b8077fe",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<KeysViewHDF5 ['air_pres', 'air_pres_h2o', 'air_pres_h2o_nsurf', 'air_pres_lay', 'air_pres_lay_bnds', 'air_pres_lay_nsurf', 'air_pres_nsurf', 'air_temp', 'air_temp_dof', 'air_temp_err', 'air_temp_qc', 'asc_flag', 'asc_node_local_solar_time', 'asc_node_lon', 'asc_node_tai93', 'atrack', 'attitude', 'attitude_lbl', 'aux', 'ave_kern', 'bnds_1d', 'ch4_dof', 'ch4_mmr_midtrop', 'ch4_mmr_midtrop_err', 'ch4_mmr_midtrop_qc', 'cld_frac', 'cld_frac_err', 'cld_frac_qc', 'cld_lay', 'cld_lay_lbl', 'cld_top_pres', 'cld_top_pres_err', 'cld_top_pres_qc', 'cld_top_temp', 'cld_top_temp_err', 'cld_top_temp_qc', 'co2_dof', 'co_dof', 'co_mmr_midtrop', 'co_mmr_midtrop_err', 'co_mmr_midtrop_qc', 'fov', 'fov_land_frac', 'fov_lat', 'fov_lat_bnds', 'fov_lon', 'fov_lon_bnds', 'fov_obs_id', 'fov_poly', 'fov_surf_alt', 'fov_surf_alt_sdev', 'gp_hgt', 'gp_hgt_err', 'gp_hgt_qc', 'h2o_liq_mol_lay', 'h2o_liq_mol_lay_err', 'h2o_liq_mol_lay_qc', 'h2o_liq_tot', 'h2o_liq_tot_err', 'h2o_liq_tot_qc', 'h2o_vap_dof', 'h2o_vap_tot', 'h2o_vap_tot_err', 'h2o_vap_tot_qc', 'hno3_dof', 'ir_precip_est_24hr', 'ir_precip_est_24hr_err', 'ir_precip_est_24hr_qc', 'land_frac', 'lat', 'lat_bnds', 'lat_geoid', 'local_solar_time', 'lon', 'lon_bnds', 'lon_geoid', 'mean_anom_wrt_equat', 'mol_lay', 'mw', 'mw_cld_phase', 'mw_surf_class', 'n2o_dof', 'num_cld', 'num_cld_qc', 'o3_dof', 'o3_mmr', 'o3_mmr_err', 'o3_mmr_qc', 'o3_tot', 'o3_tot_err', 'o3_tot_qc', 'obs_id', 'obs_time_tai93', 'obs_time_utc', 'rel_hum', 'rel_hum_err', 'rel_hum_qc', 'sat_alt', 'sat_att', 'sat_azi', 'sat_pos', 'sat_range', 'sat_sol_azi', 'sat_sol_zen', 'sat_vel', 'sat_zen', 'scan_mid_time', 'so2_dof', 'sol_azi', 'sol_zen', 'solar_beta_angle', 'spatial', 'spatial_lbl', 'spec_hum', 'spec_hum_err', 'spec_hum_qc', 'spec_hum_sat_ice', 'spec_hum_sat_ice_err', 'spec_hum_sat_ice_qc', 'spec_hum_sat_liq', 'spec_hum_sat_liq_err', 'spec_hum_sat_liq_qc', 'subsat_lat', 'subsat_lon', 'sun_glint_dist', 'sun_glint_lat', 'sun_glint_lon', 'surf_air_temp', 'surf_air_temp_err', 'surf_air_temp_qc', 'surf_alt', 'surf_alt_sdev', 'surf_freq_mw', 'surf_gp_hgt', 'surf_gp_hgt_err', 'surf_gp_hgt_qc', 'surf_ir_emis', 'surf_ir_emis_err', 'surf_ir_emis_qc', 'surf_ir_refl', 'surf_ir_refl_qc', 'surf_ir_wnum', 'surf_ir_wnum_cnt', 'surf_mw_emis', 'surf_mw_emis_err', 'surf_mw_emis_qc', 'surf_rel_hum', 'surf_rel_hum_err', 'surf_rel_hum_qc', 'surf_spec_hum', 'surf_spec_hum_err', 'surf_spec_hum_qc', 'surf_spec_hum_sat_ice', 'surf_spec_hum_sat_ice_err', 'surf_spec_hum_sat_ice_qc', 'surf_spec_hum_sat_liq', 'surf_spec_hum_sat_liq_err', 'surf_spec_hum_sat_liq_qc', 'surf_temp', 'surf_temp_dof', 'surf_temp_err', 'surf_temp_qc', 'surf_wnum_ir', 'tpause_gp_hgt', 'tpause_gp_hgt_qc', 'tpause_pres', 'tpause_pres_qc', 'tpause_temp', 'tpause_temp_qc', 'utc_tuple', 'utc_tuple_lbl', 'view_ang', 'xtrack']>"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# tunnel down through \n",
+    "h5file.keys()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "c951b7fc-de9d-4445-96fb-37b56e810385",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "group = '/'\n",
+    "variable = 'surf_temp'"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "23990582-efbd-45fe-afb7-450568012ce8",
+   "metadata": {},
+   "source": [
+    "# Create tests object"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "a26d9cec-cb84-436b-883f-4f373effd5c5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "test_dict = {\n",
+    "    \"collection\": short_name,\n",
+    "    \"group\": group,\n",
+    "    \"variable\": variable,\n",
+    "    \"files\": processing_options\n",
+    "}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "d3e3ad09-7f57-41e8-bbaf-bb77c80bc50d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Write the dictionary to a file\n",
+    "with open (f'../../h5cloud/file_configs/{short_name}_{version}.yaml', 'w') as file:\n",
+    "    yaml.dump(test_dict, file, default_flow_style=False)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "c96db127-d4d6-4e6f-884b-5f8a43874383",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "ATL03_006.yaml\t       GSSTF_NCEP_3.yaml\t     OMVFPITMET_003.yaml\n",
+      "ATL08_006.yaml\t       LPRM_AMSR2_D_SOILM3_001.yaml  SNDRSNIML2CCPRETN_2.yaml\n",
+      "GPM_3IMERGHHE_06.yaml  OMUFPITMET_003.yaml\t     atl03.yml\n"
+     ]
+    }
+   ],
+   "source": [
+    "!ls ../../h5cloud/file_configs/"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.8"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/notebooks/replicate-results-research/03-run-tests-ATL03.ipynb b/notebooks/replicate-results-research/03-run-tests-ATL03.ipynb
new file mode 100644
index 0000000..439ee0c
--- /dev/null
+++ b/notebooks/replicate-results-research/03-run-tests-ATL03.ipynb
@@ -0,0 +1,288 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "19bcc8ae-7f82-4acc-9522-d1240c242c14",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import sys\n",
+    "import os\n",
+    "\n",
+    "# Get the current working directory\n",
+    "current_dir = os.getcwd()\n",
+    "\n",
+    "# Navigate two directories up from the current directory\n",
+    "module_path = os.path.abspath(os.path.join(current_dir, '..', '..'))\n",
+    "\n",
+    "# Add this path to sys.path\n",
+    "if module_path not in sys.path:\n",
+    "    sys.path.append(module_path)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "e15343cc-8110-406b-8347-c99a8f0592e2",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from h5cloud.test_config import TestConfig\n",
+    "from h5cloud.tests.h5py_arr_mean import H5pyArrMean\n",
+    "from h5cloud.tests.h5coro_arr_mean import H5CoroArrMean\n",
+    "from h5cloud.tests.xarray_arr_mean import XarrayArrMean\n",
+    "import matplotlib.pyplot as plt"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "998dedf3-9129-4700-87f8-de53df8efe94",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "tc = TestConfig.load_from_yaml(\n",
+    "    yaml_file=\"../../h5cloud/file_configs/ATL03_006.yaml\",\n",
+    "    results_bucket=\"nasa-veda-scratch\",\n",
+    "    results_directory=\"h5cloud-results\"\n",
+    ")\n",
+    "results = {}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "f724aa6c-966a-41a1-9e62-9639becd9e70",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "fsspec_params = {\n",
+    "    # \"skip_instance_cache\": True\n",
+    "    \"cache_type\": \"blockcache\",  # or \"first\" with enough space\n",
+    "    \"block_size\": 8*1024*1024 # could be bigger\n",
+    "}\n",
+    "driver_kwds = { # only recent versions of xarray and h5netcdf allow this correctly\n",
+    "    \"page_buf_size\": 32*1024*1024, # this one only works in repacked files\n",
+    "    \"rdcc_nbytes\": 8*1024*1024 # this one is to read the chunks \n",
+    "}\n",
+    "io_params = {\n",
+    "    \"fsspec_params\": fsspec_params,\n",
+    "    \"h5py_params\": { \"driver_kwds\": driver_kwds }\n",
+    "}"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "57709b4b-0ea0-4489-8b5d-1434edd95644",
+   "metadata": {},
+   "source": [
+    "# H5Py Array Mean"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "f59b23dc-dbca-455c-91ad-c3b9f0e53527",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "h5py_arr_test = H5pyArrMean(tc, store_results=False)\n",
+    "results['h5py_arr_test'] = {}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "3cc33911-4ee5-464a-94d1-ea49abb4dfd4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "for file_format, file in tc.files.items():\n",
+    "    # run test on file\n",
+    "    if 'kerchunk' not in file_format:\n",
+    "        results['h5py_arr_test'][file_format] = h5py_arr_test.run(file_format)\n",
+    "        results['h5py_arr_test'][f\"{file_format}_wparams\"] = h5py_arr_test.run(file_format=file_format, io_params=io_params)\n",
+    "    "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "daf84f7a-65c3-4fd7-837b-e970bce76106",
+   "metadata": {},
+   "source": [
+    "# H5Coro Array Mean"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "196ac55e-d6af-40d4-a2c3-e7d030e788ee",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "h5coro_arr_test = H5CoroArrMean(tc, store_results=False)\n",
+    "results['h5coro_arr_test'] = {}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "e81afb70-0ed9-4bd4-aa7b-8a2a0726fedb",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "for file_format, file in tc.files.items():\n",
+    "    # run test on file\n",
+    "    if 'kerchunk' not in file_format:\n",
+    "        results['h5coro_arr_test'][file_format] = h5coro_arr_test.run(file_format)\n",
+    "    "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "499ab253-e512-47f8-a178-426b502547df",
+   "metadata": {},
+   "source": [
+    "# Xarray Array Mean"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "296c3883-c948-4c82-9dd8-6f288cbd69bb",
+   "metadata": {},
+   "source": [
+    "Note: it does seem like the first time tests are run a cache is created, despite efforts to pass cache=False and ds.close()."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "bd91d1e0-0406-478f-a32f-4c6b001b5018",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "xr_arr_test = XarrayArrMean(tc, store_results=False)\n",
+    "results['xr_arr_test'] = {}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "id": "96d56a68-2082-4264-b1f5-161c77d34f4e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "for file_format, file in tc.files.items():\n",
+    "    results['xr_arr_test'][file_format] = xr_arr_test.run(file_format)\n",
+    "    if file_format != 'original':\n",
+    "        results['xr_arr_test'][f\"{file_format}_wparams\"] = xr_arr_test.run(file_format=file_format, io_params=io_params)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "id": "e0ba8c9f-18ea-419d-aac8-ac3bae976ff2",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'kerchunk': (-35.0549430847168, 0.9401414394378662),\n",
+       " 'kerchunk_wparams': (-35.0549430847168, 0.6296565532684326),\n",
+       " 'kerchunk_repacked_page_4mb': (-35.0549430847168, 0.9950292110443115),\n",
+       " 'kerchunk_repacked_page_4mb_wparams': (-35.0549430847168, 0.8351221084594727),\n",
+       " 'original': (-35.0549430847168, 40.353511333465576),\n",
+       " 'repacked_page_4mb': (-35.0549430847168, 5.341959238052368),\n",
+       " 'repacked_page_4mb_wparams': (-35.0549430847168, 2.1982955932617188)}"
+      ]
+     },
+     "execution_count": 23,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "results['xr_arr_test'] "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "id": "fc495706-4d30-4973-a7b4-3b5324b77525",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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PAMh1Jg8iyjuZEO/NdE1ERN88Z2dn7Nq1K18XbejZsycuXLiA+/fv55gTloiosHCYARERfbbU1FRERUXh4sWL2L17N5YtW8YgS0RfFMMsERF9tpiYGDRp0gQlSpTAiBEjMGbMmBzrZGZm5rjcbXYymQyampqFVqNCofjkZX2z5lAmIvXDYQZERFSoWrZsiYiIiA8ur1ChAu7fv19oj+/s7IyNGzd+dB2+FRKpL4ZZIiIqVLdu3UJCQsIHl2tra+c6vVVBuX///ifnLM6aV5mI1A/DLBERERGpLV40gYiIiIjU1jc34l2hUODff/+FgYFBgV/ykIiIiIj+OyEEEhISUKZMmRyX2n7fNxdm//33X5QrV07VZRARERHRJzx69Ahly5b96DrfXJjNul78o0eP8nSpTCIiIiL6suLj41GuXDkpt33MNxdms4YWlChRgmGWiIiIqAjLy5BQngBGRERERGqLYZaIiIiI1JZKw2xAQACsra2lr/wbN26MQ4cOfXSbiIgI2NraQkdHBxUrVkRgYOAXqpaIiIiIihqVhtmyZctiwYIFiIyMRGRkJBwcHNC1a1f89ddfua5/7949ODo6wt7eHtHR0fDx8YG7uztCQ0O/cOVEREREVBQUuSuAmZiYYPHixRg6dGiOZRMnTsS+fftw48YNqc3V1RVXrlzB+fPn87T/+Ph4GBoa4s2bNzwBjIiIiKgIyk9eKzJjZjMzM7Ft2zYkJiaicePGua5z/vx5tGvXTqmtffv2iIyMRHp6eq7bpKamIj4+XulGRERERF8HlYfZa9euoXjx4tDW1oarqyt2796NmjVr5rpubGwszMzMlNrMzMyQkZGBFy9e5LrN/PnzYWhoKN14wQQiIiKir4fKw2y1atXwxx9/4MKFCxg5ciScnJxw/fr1D67//nxjWaMkPjQPmbe3N968eSPdHj16VHDFExEREZFKqfyiCcWKFUPlypUBAHZ2drh06RJWrFiBNWvW5FjX3NwcsbGxSm3Pnj2DlpYWSpYsmev+tbW1oa2tXfCFExEREZHKqbxn9n1CCKSmpua6rHHjxjh27JhS29GjR2FnZwe5XP4lyiMiIiKiIkSlYdbHxwdnzpzB/fv3ce3aNUyePBmnTp1C//79AbwbIjBo0CBpfVdXVzx48ACenp64ceMGgoKCsGHDBowfP15VT4GIiIiIVEilwwyePn2KgQMHIiYmBoaGhrC2tsbhw4fRtm1bAEBMTAwePnworW9lZYWDBw9i3Lhx8Pf3R5kyZbBy5Ur07NlTVU+BiEjtWU46oOoSqJDcX9BJ1SUQFboiN89sYeM8s0REyhhmv14Ms6Su1HKeWSIiIiKi/GKYJSIiIiK1xTBLRERERGqLYZaIiIiI1BbDLBERERGpLZVfAexbwbOFv048U5iIiEi12DNLRERERGqLYZaIiIiI1BbDLBERERGpLYZZIiIiIlJbDLNEREREpLYYZomIiIhIbTHMEhEREZHaYpglIiIiIrXFMEtEREREaothloiIiIjUFsMsEREREakthlkiIiIiUlsMs0RERESkthhmiYiIiEhtMcwSERERkdpimCUiIiIitcUwS0RERERqi2GWiIiIiNQWwywRERERqS2GWSIiIiJSWwyzRERERKS2GGaJiIiISG0xzBIRERGR2mKYJSIiIiK1xTBLRERERGqLYZaIiIiI1BbDLBERERGpLYZZIiIiIlJbDLNEREREpLYYZomIiIhIbTHMEhEREZHaYpglIiIiIrXFMEtEREREakulYXb+/PmoX78+DAwMYGpqim7duuHWrVsf3ebUqVOQyWQ5bjdv3vxCVRMRERFRUaHSMBsREQE3NzdcuHABx44dQ0ZGBtq1a4fExMRPbnvr1i3ExMRItypVqnyBiomIiIioKNFS5YMfPnxY6X5wcDBMTU1x+fJlNG/e/KPbmpqawsjIqBCrIyIiIqKirkiNmX3z5g0AwMTE5JPr2tjYwMLCAq1bt0Z4ePgH10tNTUV8fLzSjYiIiIi+DkUmzAoh4OnpiWbNmqF27dofXM/CwgJr165FaGgowsLCUK1aNbRu3RqnT5/Odf358+fD0NBQupUrV66wngIRERERfWEqHWaQ3ejRo3H16lWcPXv2o+tVq1YN1apVk+43btwYjx49wpIlS3IdmuDt7Q1PT0/pfnx8PAMtERER0VeiSPTMjhkzBvv27UN4eDjKli2b7+0bNWqE27dv57pMW1sbJUqUULoRERER0ddBpT2zQgiMGTMGu3fvxqlTp2BlZfVZ+4mOjoaFhUUBV0dERERERZ1Kw6ybmxu2bNmCvXv3wsDAALGxsQAAQ0ND6OrqAng3TODJkyfYtGkTAMDX1xeWlpaoVasW0tLS8PPPPyM0NBShoaEqex5EREREpBoqDbMBAQEAgJYtWyq1BwcHw9nZGQAQExODhw8fSsvS0tIwfvx4PHnyBLq6uqhVqxYOHDgAR0fHL1U2ERERERURKh9m8CkhISFK9728vODl5VVIFRERERGROikSJ4AREREREX0OhlkiIiIiUlsMs0RERESkthhmiYiIiEhtMcwSERERkdpimCUiIiIitcUwS0RERERqi2GWiIiIiNQWwywRERERqS2GWSIiIiJSWwyzRERERKS2GGaJiIiISG0xzBIRERGR2mKYJSIiIiK1xTBLRERERGqLYZaIiIiI1BbDLBERERGpLYZZIiIiIlJbDLNEREREpLYYZomIiIhIbTHMEhEREZHaYpglIiIiIrXFMEtEREREaothloiIiIjUFsMsEREREakthlkiIiIiUlsMs0RERESkthhmiYiIiEhtMcwSERERkdpimCUiIiIitcUwS0RERERqi2GWiIiIiNQWwywRERERqa3/HGbj4+OxZ88e3LhxoyDqISIiIiLKs3yH2R9++AGrVq0CACQnJ8POzg4//PADrK2tERoaWuAFEhERERF9SL7D7OnTp2Fvbw8A2L17N4QQeP36NVauXIk5c+YUeIFERERERB+S7zD75s0bmJiYAAAOHz6Mnj17Qk9PD506dcLt27cLvEAiIiIiog/Jd5gtV64czp8/j8TERBw+fBjt2rUDALx69Qo6OjoFXiARERER0Ydo5XeDsWPHon///ihevDgqVKiAli1bAng3/KBOnToFXR8RERER0Qflu2d21KhROH/+PIKCgnD27FloaLzbRcWKFfM9Znb+/PmoX78+DAwMYGpqim7duuHWrVuf3C4iIgK2trbQ0dFBxYoVERgYmN+nQURERERfgc+amsvOzg7du3dH8eLFpbZOnTqhadOm+dpPREQE3NzccOHCBRw7dgwZGRlo164dEhMTP7jNvXv34OjoCHt7e0RHR8PHxwfu7u6cSYGIiIjoG5SnYQaenp553uGyZcvyvO7hw4eV7gcHB8PU1BSXL19G8+bNc90mMDAQ5cuXh6+vLwCgRo0aiIyMxJIlS9CzZ88c66empiI1NVW6Hx8fn+f6iIiIiKhoy1OYjY6OVrp/+fJlZGZmolq1agCAv//+G5qamrC1tf1Pxbx58wYApNkScnP+/HnppLMs7du3x4YNG5Ceng65XK60bP78+Zg5c+Z/qouIiIiIiqY8hdnw8HDp52XLlsHAwAAbN26EsbExgHczGQwePFiaf/ZzCCHg6emJZs2aoXbt2h9cLzY2FmZmZkptZmZmyMjIwIsXL2BhYaG0zNvbW6lnOT4+HuXKlfvsOomIiIio6Mj3bAZLly7F0aNHpSALAMbGxpgzZw7atWuHn3766bMKGT16NK5evYqzZ89+cl2ZTKZ0XwiRazsAaGtrQ1tb+7NqIiIiIqKiLd8ngMXHx+Pp06c52p89e4aEhITPKmLMmDHYt28fwsPDUbZs2Y+ua25ujtjY2ByPraWlhZIlS37W4xMRERGResp3mO3evTsGDx6MXbt24fHjx3j8+DF27dqFoUOHokePHvnalxACo0ePRlhYGE6ePAkrK6tPbtO4cWMcO3ZMqe3o0aOws7PLMV6WiIiIiL5u+Q6zgYGB6NSpEwYMGIAKFSqgQoUK6N+/Pzp27IjVq1fna19ubm74+eefsWXLFhgYGCA2NhaxsbFITk6W1vH29sagQYOk+66urnjw4AE8PT1x48YNBAUFYcOGDRg/fnx+nwoRERERqbl8j5nV09PD6tWrsXjxYty5cwdCCFSuXBn6+vr5fvCAgAAAkK4iliU4OBjOzs4AgJiYGDx8+FBaZmVlhYMHD2LcuHHw9/dHmTJlsHLlylyn5SIiIiKir1u+w2wWfX19WFtb/6cHzzpx62NCQkJytLVo0QJRUVH/6bGJiIiISP3lO8wmJiZiwYIFOHHiBJ49ewaFQqG0/O7duwVWHBERERHRx+Q7zLq4uCAiIgIDBw6EhYVFrtNhERERERF9CfkOs4cOHcKBAwfQtGnTwqiHiIiIiCjP8j2bgbGx8UcvN0tERERE9KXkO8zOnj0b06ZNQ1JSUmHUQ0RERESUZ591Ods7d+7AzMwMlpaWOS5UwFkGiIiIiOhLyXeY7datWyGUQURERESUf/kOs9OnTy+MOoiIiIiI8u2zL5pw+fJl3LhxAzKZDDVr1oSNjU1B1kVERERE9En5DrPPnj1Dnz59cOrUKRgZGUEIgTdv3qBVq1bYtm0bSpcuXRh1EhERERHlkO/ZDMaMGYP4+Hj89ddfiIuLw6tXr/Dnn38iPj4e7u7uhVEjEREREVGu8t0ze/jwYRw/fhw1atSQ2mrWrAl/f3+0a9euQIsjIiIiIvqYfPfMKhSKHNNxAYBcLodCoSiQooiIiIiI8iLfYdbBwQEeHh74999/pbYnT55g3LhxaN26dYEWR0RERET0MfkOs6tWrUJCQgIsLS1RqVIlVK5cGVZWVkhISICfn19h1EhERERElKt8j5ktV64coqKicOzYMdy8eRNCCNSsWRNt2rQpjPqIiIiIiD7os+eZbdu2Ldq2bVuQtRARERER5Uu+hxm4u7tj5cqVOdpXrVqFsWPHFkRNRERERER5ku8wGxoaiqZNm+Zob9KkCXbt2lUgRRERERER5UW+w+zLly9haGiYo71EiRJ48eJFgRRFRERERJQX+Q6zlStXxuHDh3O0Hzp0CBUrViyQooiIiIiI8iLfJ4B5enpi9OjReP78ORwcHAAAJ06cwNKlS+Hr61vQ9RERERERfVC+w+yQIUOQmpqKuXPnYvbs2QAAS0tLBAQEYNCgQQVeIBERERHRh3zW1FwjR47EyJEj8fz5c+jq6qJ48eIFXRcRERER0Sfle8wsAGRkZOD48eMICwuDEAIA8O+//+Lt27cFWhwRERER0cfku2f2wYMH6NChAx4+fIjU1FS0bdsWBgYGWLRoEVJSUhAYGFgYdRIRERER5ZDvnlkPDw/Y2dnh1atX0NXVldq7d++OEydOFGhxREREREQfk++e2bNnz+LcuXMoVqyYUnuFChXw5MmTAiuMiIiIiOhT8t0zq1AokJmZmaP98ePHMDAwKJCiiIiIiIjyIt9htm3btkrzycpkMrx9+xbTp0+Ho6NjQdZGRERERPRR+R5msHz5crRq1Qo1a9ZESkoK+vXrh9u3b6NUqVLYunVrYdRIRERERJSrfIfZMmXK4I8//sC2bdtw+fJlKBQKDB06FP3791c6IYyIiIiIqLB91kUTdHV1MXjwYAwePLig6yEiIiIiyrN8j5nduHEjDhw4IN338vKCkZERmjRpggcPHhRocUREREREH5PvMDtv3jxpOMH58+exatUqLFq0CKVKlcK4ceMKvEAiIiIiog/J9zCDR48eoXLlygCAPXv2oFevXhg+fDiaNm2Kli1bFnR9REREREQflO+e2eLFi+Ply5cAgKNHj6JNmzYAAB0dHSQnJxdsdUREREREH5Hvntm2bdvCxcUFNjY2+Pvvv9GpUycAwF9//QVLS8uCro+IiIiI6IPy3TPr7++Pxo0b4/nz5wgNDUXJkiUBAJcvX0bfvn3zta/Tp0+jS5cuKFOmDGQyGfbs2fPR9U+dOgWZTJbjdvPmzfw+DSIiIiL6CuS7Z9bIyAirVq3K0T5z5sx8P3hiYiLq1q2LwYMHo2fPnnne7tatWyhRooR0v3Tp0vl+bCIiIiJSf581z2xB6dixIzp27Jjv7UxNTWFkZFTwBRERERGRWsn3MIOiwMbGBhYWFmjdujXCw8M/um5qairi4+OVbkRERET0dVCrMGthYYG1a9ciNDQUYWFhqFatGlq3bo3Tp09/cJv58+fD0NBQupUrV+4LVkxEREREhUmlwwzyq1q1aqhWrZp0v3Hjxnj06BGWLFmC5s2b57qNt7c3PD09pfvx8fEMtERERERfCbXqmc1No0aNcPv27Q8u19bWRokSJZRuRERERPR1yHeYffr0KQYOHIgyZcpAS0sLmpqaSrcvLTo6GhYWFl/8cYmIiIhI9fI9zMDZ2RkPHz7E1KlTYWFhAZlM9tkP/vbtW/zzzz/S/Xv37uGPP/6AiYkJypcvD29vbzx58gSbNm0CAPj6+sLS0hK1atVCWloafv75Z4SGhiI0NPSzayAiIiIi9ZXvMHv27FmcOXMG33///X9+8MjISLRq1Uq6nzW21cnJCSEhIYiJicHDhw+l5WlpaRg/fjyePHkCXV1d1KpVCwcOHICjo+N/roWIiIiI1E++w2y5cuUghCiQB2/ZsuVH9xUSEqJ038vLC15eXgXy2ERERESk/vI9ZtbX1xeTJk3C/fv3C6EcIiIiIqK8y3fP7I8//oikpCRUqlQJenp6kMvlSsvj4uIKrDgiIiIioo/Jd5j19fUthDKIiIiIiPIv32HWycmpMOogIiIiIsq3PIXZ+Ph46WID8fHxH12XFyUgIiIioi8lT2HW2NgYMTExMDU1hZGRUa5zywohIJPJkJmZWeBFEhERERHlJk9h9uTJkzAxMQEAhIeHF2pBRERERER5lacw26JFi1x/JiIiIiJSpXzPM0tEREREVFQwzBIRERGR2mKYJSIiIiK1xTBLRERERGrrs8JsRkYGjh8/jjVr1iAhIQEA8O+//+Lt27cFWhwRERER0cfk+wpgDx48QIcOHfDw4UOkpqaibdu2MDAwwKJFi5CSkoLAwMDCqJOIiIiIKId898x6eHjAzs4Or169gq6urtTevXt3nDhxokCLIyIiIiL6mHz3zJ49exbnzp1DsWLFlNorVKiAJ0+eFFhhRERERESfku+eWYVCkeslax8/fgwDA4MCKYqIiIiIKC/yHWbbtm0LX19f6b5MJsPbt28xffp0ODo6FmRtREREREQfle9hBsuXL0erVq1Qs2ZNpKSkoF+/frh9+zZKlSqFrVu3FkaNRERERES5yneYLVOmDP744w9s3boVUVFRUCgUGDp0KPr37690QhgRERERUWHLd5gFAF1dXQwZMgRDhgwp6HqIiIiIiPLss8LskydPcO7cOTx79gwKhUJpmbu7e4EURkQfZjnpgKpLoEJyf0EnVZdARKRW8h1mg4OD4erqimLFiqFkyZKQyWTSMplMxjBLRERERF9MvsPstGnTMG3aNHh7e0ND47OuhktEREREVCDynUaTkpLQp08fBlkiIiIiUrl8J9KhQ4di586dhVELEREREVG+5HuYwfz589G5c2ccPnwYderUgVwuV1q+bNmyAiuOiIiIiOhj8h1m582bhyNHjqBatWoAkOMEMCIiIiKiLyXfYXbZsmUICgqCs7NzIZRDRERERJR3+R4zq62tjaZNmxZGLURERERE+ZLvMOvh4QE/P7/CqIWIiIiIKF/yPczg4sWLOHnyJPbv349atWrlOAEsLCyswIojIiIiIvqYfIdZIyMj9OjRozBqISIiIiLKl8+6nC0RERERUVHAy3gRERERkdrKU89svXr1cOLECRgbG8PGxuaj88lGRUUVWHFERERERB+TpzDbtWtXaGtrAwC6detWmPUQEREREeVZnsLs9OnTMWTIEKxYsQLTp08v7JqIiIiIiPIkz2NmN27ciOTk5MKshYiIiIgoX/IcZoUQBf7gp0+fRpcuXVCmTBnIZDLs2bPnk9tERETA1tYWOjo6qFixIgIDAwu8LiIiIiJSD/mazeBjJ359jsTERNStWxerVq3K0/r37t2Do6Mj7O3tER0dDR8fH7i7uyM0NLRA6yIiIiIi9ZCveWarVq36yUAbFxeX5/117NgRHTt2zPP6gYGBKF++PHx9fQEANWrUQGRkJJYsWYKePXvmeT9ERERE9HXIV5idOXMmDA0NC6uWTzp//jzatWun1Na+fXts2LAB6enpOS6tCwCpqalITU2V7sfHxxd6nURERET0ZeQrzPbp0wempqaFVcsnxcbGwszMTKnNzMwMGRkZePHiBSwsLHJsM3/+fMycOfNLlUhEREREX1Cex8wW9HjZz/V+HVknpn2oPm9vb7x580a6PXr0qNBrJCIiIqIvI889s4Uxm0F+mZubIzY2Vqnt2bNn0NLSQsmSJXPdRltbW7rgAxERERF9XfIcZhUKRWHWkSeNGzfGr7/+qtR29OhR2NnZ5TpeloiIiIi+bvmamqugvX37Fn/88Qf++OMPAO+m3vrjjz/w8OFDAO+GCAwaNEha39XVFQ8ePICnpydu3LiBoKAgbNiwAePHj1dF+URERESkYvk6AaygRUZGolWrVtJ9T09PAICTkxNCQkIQExMjBVsAsLKywsGDBzFu3Dj4+/ujTJkyWLlyJaflIiIiIvpGqTTMtmzZ8qNjcUNCQnK0tWjRAlFRUYVYFRERERGpC5UOMyAiIiIi+i8YZomIiIhIbTHMEhEREZHaYpglIiIiIrXFMEtEREREaothloiIiIjUFsMsEREREakthlkiIiIiUlsMs0RERESkthhmiYiIiEhtMcwSERERkdpimCUiIiIitcUwS0RERERqi2GWiIiIiNSWlqoLICIioq+L5aQDqi6BCsH9BZ1UXUKu2DNLRERERGqLYZaIiIiI1BbDLBERERGpLYZZIiIiIlJbDLNEREREpLYYZomIiIhIbTHMEhEREZHaYpglIiIiIrXFMEtEREREaothloiIiIjUFsMsEREREakthlkiIiIiUlsMs0RERESkthhmiYiIiEhtMcwSERERkdpimCUiIiIitcUwS0RERERqi2GWiIiIiNQWwywRERERqS2GWSIiIiJSWwyzRERERKS2GGaJiIiISG0xzBIRERGR2mKYJSIiIiK1pfIwu3r1alhZWUFHRwe2trY4c+bMB9c9deoUZDJZjtvNmze/YMVEREREVFSoNMxu374dY8eOxeTJkxEdHQ17e3t07NgRDx8+/Oh2t27dQkxMjHSrUqXKF6qYiIiIiIoSlYbZZcuWYejQoXBxcUGNGjXg6+uLcuXKISAg4KPbmZqawtzcXLppamp+oYqJiIiIqChRWZhNS0vD5cuX0a5dO6X2du3a4bfffvvotjY2NrCwsEDr1q0RHh7+0XVTU1MRHx+vdCMiIiKir4PKwuyLFy+QmZkJMzMzpXYzMzPExsbmuo2FhQXWrl2L0NBQhIWFoVq1amjdujVOnz79wceZP38+DA0NpVu5cuUK9HkQERERkepoqboAmUymdF8IkaMtS7Vq1VCtWjXpfuPGjfHo0SMsWbIEzZs3z3Ubb29veHp6Svfj4+MZaImIiIi+EirrmS1VqhQ0NTVz9MI+e/YsR2/txzRq1Ai3b9/+4HJtbW2UKFFC6UZEREREXweVhdlixYrB1tYWx44dU2o/duwYmjRpkuf9REdHw8LCoqDLIyIiIiI1oNJhBp6enhg4cCDs7OzQuHFjrF27Fg8fPoSrqyuAd0MEnjx5gk2bNgEAfH19YWlpiVq1aiEtLQ0///wzQkNDERoaqsqnQUREREQqotIw++OPP+Lly5eYNWsWYmJiULt2bRw8eBAVKlQAAMTExCjNOZuWlobx48fjyZMn0NXVRa1atXDgwAE4Ojqq6ikQERERkQqp/ASwUaNGYdSoUbkuCwkJUbrv5eUFLy+vL1AVEREREakDlV/OloiIiIjoczHMEhEREZHaYpglIiIiIrXFMEtEREREaothloiIiIjUFsMsEREREakthlkiIiIiUlsMs0RERESkthhmiYiIiEhtMcwSERERkdpimCUiIiIitcUwS0RERERqi2GWiIiIiNQWwywRERERqS2GWSIiIiJSWwyzRERERKS2GGaJiIiISG0xzBIRERGR2mKYJSIiIiK1xTBLRERERGqLYZaIiIiI1BbDLBERERGpLYZZIiIiIlJbDLNEREREpLYYZomIiIhIbTHMEhEREZHaYpglIiIiIrXFMEtEREREaothloiIiIjUFsMsEREREakthlkiIiIiUlsMs0RERESkthhmiYiIiEhtMcwSERERkdpimCUiIiIitcUwS0RERERqi2GWiIiIiNQWwywRERERqS2GWSIiIiJSWyoPs6tXr4aVlRV0dHRga2uLM2fOfHT9iIgI2NraQkdHBxUrVkRgYOAXqpSIiIiIihqVhtnt27dj7NixmDx5MqKjo2Fvb4+OHTvi4cOHua5/7949ODo6wt7eHtHR0fDx8YG7uztCQ0O/cOVEREREVBSoNMwuW7YMQ4cOhYuLC2rUqAFfX1+UK1cOAQEBua4fGBiI8uXLw9fXFzVq1ICLiwuGDBmCJUuWfOHKiYiIiKgo0FLVA6elpeHy5cuYNGmSUnu7du3w22+/5brN+fPn0a5dO6W29u3bY8OGDUhPT4dcLs+xTWpqKlJTU6X7b968AQDEx8f/16eQL4rUpC/6ePRlfOnjKAuPp6+XKo4pHk9fL75GUUH6ksdT1mMJIT65rsrC7IsXL5CZmQkzMzOldjMzM8TGxua6TWxsbK7rZ2Rk4MWLF7CwsMixzfz58zFz5swc7eXKlfsP1RO9Y+ir6groa8NjigoSjycqSKo4nhISEmBoaPjRdVQWZrPIZDKl+0KIHG2fWj+39ize3t7w9PSU7isUCsTFxaFkyZIffRz6PPHx8ShXrhwePXqEEiVKqLocUnM8nqig8ZiigsTjqfAIIZCQkIAyZcp8cl2VhdlSpUpBU1MzRy/ss2fPcvS+ZjE3N891fS0tLZQsWTLXbbS1taGtra3UZmRk9PmFU56UKFGCf9hUYHg8UUHjMUUFicdT4fhUj2wWlZ0AVqxYMdja2uLYsWNK7ceOHUOTJk1y3aZx48Y51j969Cjs7OxyHS9LRERERF83lc5m4OnpifXr1yMoKAg3btzAuHHj8PDhQ7i6ugJ4N0Rg0KBB0vqurq548OABPD09cePGDQQFBWHDhg0YP368qp4CEREREamQSsfM/vjjj3j58iVmzZqFmJgY1K5dGwcPHkSFChUAADExMUpzzlpZWeHgwYMYN24c/P39UaZMGaxcuRI9e/ZU1VOg92hra2P69Ok5hnYQfQ4eT1TQeExRQeLxVDTIRF7mPCAiIiIiKoJUfjlbIiIiIqLPxTBLRERERGqLYZaIiIiI1BbDLBERERGpLYZZyjOeK0hERERFDcMsfdL48eNx+vRpyGQyBloiIiIqUhhm6aOuX7+OyMhIjBs3DhcuXGCgpf9MoVCougQiog/ia5T6YZilj6pZsyZmzZoFKysrjBo1ioGW/hOFQgENjXcvO4GBgVi7dq2KKyJ1l1vwyMzMVEEl9DXI/hp1//591RZDecYwSx+UFVibN2+OMWPGMNDSf5b1JuHl5YX58+fj+fPniImJUXFVpK5SUlKkY+ru3bt4+PAh0tPToampqeLKSB1lD7IzZ87EDz/8gIsXL6q4KsoLhln6IJlMJvVwtGjRgoGWCoS/vz+Cg4Oxe/duTJ48GRYWFqouidTMlClTkJGRAR0dHQCAj48PWrZsiaZNm6JmzZrYuXMnXr16peIqSd1kBdlJkyYhMDAQEydOhLm5eY71+L5X9DDMUg7Zv7bL3sPRsmVLuLm5MdDSZ0tPT8fly5cxevRo1KtXD7du3cLmzZvRpEkTODo64uzZs6oukYq4P/74A+vWrUObNm0AAEeOHMG6deuwfPlybNiwAQ4ODhg5ciQ2btyIpKQkFVdL6ub333/Hjh07sGPHDvTs2RNmZmZ4+vQpjhw5gidPngB419FDRYtMMIlQNtm/ZgkKCsL58+eho6ODevXqYfDgwQCAEydOYPXq1bh//z78/f3RqFEjVZZMRZgQIscL//Dhw7F//37Mnj0bwcHBMDAwgLW1NY4fP45ixYrh3Llz0jFI9L709HSEh4djwoQJMDQ0RM+ePaGhoYExY8ZI60ybNg0rVqzAwYMH0bRp01yPQ6LcHDp0CCNGjMC9e/fwxx9/YOfOndi9ezfu37+PVq1awd/fH5UqVVJ1mfQevmOQkqwQMXHiREyZMgUaGhpITk7GtGnTMGvWLABA69at4ebmhooVK6JXr17466+/VFkyFVEKhUIKEMnJyVL7hAkT0KxZM8yYMQOdOnXC3LlzsXDhQsyaNQu6urpISEhQVclUxAkhIJfL4eDggEWLFiElJQXjxo3Dy5cvAbwbQwsAs2bNQpMmTbBw4UIA7Emj3OV28mDjxo2RkpKCunXrom3btnj16hVmz56NK1euIDw8HNeuXVNBpfQpWqougIqekJAQhIaGYvfu3WjYsCG2bNmCn3/+GfPnz8ebN2+wdOlSODg4ICUlBVWrVkX16tVVXTIVQVkfjJYsWYJjx47B0tISPXr0QPv27bFjxw48f/4cpUuXBvAupKxcuRKmpqYwNDRUZdlURGX1rgohoKWlhVatWmHGjBmYOnUqdu7cCR8fH+jo6CA9PR1yuRxVqlTBo0ePVF02FVHZv4U8f/48DAwMULx4cVhaWuL333/H5s2bYWtri+bNm8PAwADp6emwtbWFlhZjU1HEYQakRKFQYMGCBZDJZPD29savv/6KQYMGYcqUKUhNTcWUKVMwY8YMTJs2TWm7zMxMnkFMOaxcuRKzZ8/GkCFDcOTIERgYGKBr164YP348ACA+Ph4nTpxAQEAAnj59isjISMjlcn4tTEqyB4/U1FRkZmZCT08PqampiIiIgJubG4yNjXHixAnI5XIUK1YMzZs3R8WKFbFp0yYVV09FmZeXFzZt2oSMjAzY2trCxcUFvXv3lpanpqYiPj4egwcPxtOnT3HhwgW+1xVBDLPfuNxCQ1JSEv7991/o6+ujXbt2cHJywvjx43Hp0iW0adMGCQkJWLp0KcaNG6eiqqmoyh46gHdnnTdo0AD/+9//EBMTg9mzZyMqKgq9evXC+PHjcfPmTaxfvx5PnjzB5s2boaWlhYyMDPZ+UK5mz56N06dPIzk5GRMmTEDXrl2RmZmJkydPws3NDYmJiahYsSKqVKmCCxcu4MqVK/xwREqyHwuXL1/GkCFDsH79ejx48ACHDh3C+fPn4e3tjYEDByIjIwObNm3C+vXrAQARERGQy+XsvCmCOGb2G5Z9TOPr16+RkZEBANDT00PlypVx8+ZNZGZmon///gAAbW1tdOnSBfv27YO7u7vK6qaiSQghBdkDBw7gyJEj+Oeff2BiYgIAsLCwwOTJk1GvXj2EhoZi5cqVqF69OiZPnowtW7ZAS0sLmZmZDLKUK39/fwQEBKBRo0YoV64cunfvjuXLl0NTUxMODg7w9/dHlSpVcO7cObi7u+PPP/+EXC5HRkYGgywBUH7PA4C0tDQ0atQI9evXR69eveDp6YkWLVpg3rx5+OWXX6ClpYW6deuiT58+OHPmjHQ8McgWPXzX+EZlDx5z5sxBREQEXr9+jUmTJsHe3h6mpqYoXrw4Hj16hO3bt6N3796YNGkSjI2N0alTJ2kOWv5RE6Dc2+Hp6YmgoCBoaWnhzZs3MDExQbNmzQAA3333HSZPnowFCxbA19cXpqam6NOnj7QPHk+U5f1efi0tLaxatQo9evQAADRs2BA//fQThBDw9PREq1atkJSUBEtLS9SpUwcaGhpQKBT8cESSrONp/vz5OHv2LDQ0NKCnpyctr1WrFkaPHg2ZTIZ58+YhJSUFQ4cOha2tLQDww3ZRJuibk5mZKf3s5+cnTExMxKJFi0SnTp1EhQoVxPTp08Xjx49FRkaGmDRpktDX1xeWlpbCxsZGpKWlCSGEUCgUqiqfirB///1XtGrVSkRFRYmrV6+KKVOmiCpVqggfHx+l9R48eCCWLFkiMjIyVFQpFWXZX1/CwsLE+vXrRatWrcT27duV1lu+fLnQ1NQUy5YtE0IIpeOJxxZlyf6et3DhQlGyZEkxYsQI0bJlSyGTycT69euV1v/rr79Enz59RN++fb90qfSZGGa/YdeuXRNubm7i4MGDUtusWbNE9erVxdSpU0VcXJxIT08XV69eFUeOHJHeHNLT01VVMhVhvr6+omnTpqJ///4iOTlZCCFEbGysmD17tqhRo4aYPHlyrtsxdFB22YOst7e3kMvlws7OTshkMuHi4iKePXumtP6KFSuETCYTW7du/dKlkpr5448/xIoVK8SxY8eEEO8+VE+YMEEYGBiIoKAgpXXv3r2rFIKpaGN/+Tdi8uTJ6NGjh/R1yf79+zFgwADo6emhc+fO0npTp04FAGzZsgUaGhoYMmQI6tSpgzp16gDg1yyUu7S0NGhoaODBgwd4+/atdJlRMzMzDBs2DDKZDNu2bcObN2/g5+entC2HFlB22U/OiYqKwunTp1GtWjWEhYVh2LBhKFOmDDw8PKSx2O7u7rCwsED37t1VWTYVcefOnYO9vT0MDAywfft2AED58uXh4eEBDQ0NjB07FhoaGnBycgIAWFlZAcg53IWKJv6GvgGRkZF49OgR6tatK7V17twZgwcPRlxcHM6cOaN0HfOpU6diwIABWLlyJY4ePaq0LwYPAv7v2uRZ/xYrVgz9+vXDjBkzcPv2bbi5uUnrZgVaR0dHxMXF8fLH9EFZx4a/vz/mzZuH4sWLw87ODsbGxhg6dCjWrVuH2bNnY8WKFUqvWb1795ZmwiDKjbW1NZYsWYK0tDRER0dL7d999x3GjBkDNzc3DB48GAcPHlTajkFWTai2Y5i+lKyv7nbu3Kk0rGDUqFHCyspKrF69Wrx69Uppm+DgYH4FTDlk/+rt2bNnIj4+XqSmpgohhHj58qVYs2aNKFWqlBgzZozSdnFxcdJxyDHXlF18fLzS/YCAAKGvry8qVKggrl27prRsw4YNQlNTU4wdOzbHdkRCiA8OD3j9+rWYN2+ekMlkIjAwUGnZgwcPxOrVqzmMTk0xzH7lsv6oMzMzxZ07d0T16tVFt27dxIkTJ6R1hg8fLipVqiRWr14tXr9+nWMfDLSUJfubxIIFC0STJk2Era2tcHR0FC9evBBCvAuta9euFaVLlxYeHh459sEgS9lt2bJF/PDDDyIyMlKpffv27cLMzEyMGTNG/PPPP0rLVq5cKZo0acJjiXLI/hp16NAhsXPnTvHzzz9LbUlJSWLOnDlCJpOJNWvW5LoPBlr1wzD7Fcv+Qp/188GDB0WzZs1Ez549xfHjx6XlI0aMEFWrVhWLFy8WCQkJX7xWUi8+Pj7CzMxMbNiwQezevVvUqFFD1KhRQ9y7d08I8S7Qrlu3TshkMrF8+XKV1kpF16tXr0TNmjVFxYoVxfDhw0VUVJTS8uDgYPHdd9+JcePGiTt37igtYy8/vS/7sTBp0iRRoUIFYW1tLSwsLETnzp1FbGysEOJdoJ07d67Q0tISS5cuVVW5VIAYZr9S2f+ot23bJkaNGiV92jx06JBo3LhxjkD7ww8/iN69e/PNgXLIfkwcPnxYfP/99+LMmTNCCCH27dsnDA0NRfny5UXZsmWlQPvixQuxd+9e9uzTB2VmZopOnTqJbt26CTs7O+Hk5CQuXryotM66detE2bJlxU8//SRu3bqltIyvVZSbRYsWCXNzc3Hp0iUhhBCBgYFCJpOJNm3aiH///VcIIURycrKYOHGiaNq0KY+jrwDD7Fco+9cs58+fF127dhXfffedmDlzphQssgJtr169lIYcZG3LP27Kkv14Sk5OFlevXhUzZ84UQrw7jkqVKiX8/f3F9evXhZmZmahdu7b4+++/lfbBr+3ofVmvMWPGjBEHDx4UBw4cEDY2NmL48OEiMjJSuLi4SOuGhIQITU1NsXLlSlWVS0VY9teo58+fi4EDB4qdO3cKIYTYs2ePMDQ0FLNmzRKWlpaibdu24vHjx0IIIVJTU9nD/5VgmP2KeXp6ipYtW4ru3buLSpUqibJly4pJkyZJweLw4cOiWbNmolWrVkrj1Ti3HmXJ/gI/fvx44ezsLIQQIiYmRqSnp4v27dtLF0R4+/atsLe3F8WKFROdO3dWSb2kfpYtWyZGjRolhBAiNDRU1KtXT5QqVUqUL19eukiLEEIcOHCAvfyUw/sX2BBCiN27d4tnz56JS5cuCSsrK7Fq1SohxLtjTSaTCRsbG2mM//v7IPXEOSe+IiLblEdhYWEICQnB4sWLsXPnTly/fh3du3fHsWPHMH36dGRkZKB9+/aYMGECqlatChsbG2lbTkVCgPIlasPDw3Hs2DEMHz4cAGBubo7nz5/j77//RtOmTQEA6enpKFOmDM6ePYu9e/eqrG5SD1mvV+bm5rh69SoAoEePHnjx4gXS0tLQtGlT3Lx5U1rf0dERmpqayMzMVEm9VPRkf42aN28e+vbti3/++Qddu3ZF6dKlce7cOdSsWRP9+vUDABgYGGDIkCGoUaMGjIyMpP1k7YPUF1PLV2DYsGG4c+eO0h/kkydPYGpqiho1akBTUxPFihXDjBkzUL16dQQGBmL27NnIyMjA//73P/j7+0vXMSfKknU87d69Gz///DNatGiBxo0bS3N5WlhY4LvvvsPEiROxdetWdOvWDY8fP4atrS2PJ/qkrOPL3t4eZmZmSExMRJ06dVClShUsWrQId+7cwdSpU3H79m2l7TjXNWXJOoYuXbqEx48f49ChQ6hcubLUfuPGDTx48ABGRkZ4+/Ytfv31V9SuXRu//PILPxh9ZRhm1dzvv/+OYsWKoXz58krtJUuWhEwmw+PHjwG8u4qJiYkJpkyZAplMhkOHDmH+/PkQQkhvDuyRpfclJCRg5cqV2Lp1K27dugUASpPTL1myBCVLlsSCBQugp6eH8PBwKcjyeKK80NTUxLlz51CqVCmYmJhgx44dGDFiBEaMGIGSJUuiUqVKqi6RirDdu3dj2LBhOHHiBCpUqAAAUkh1d3fHkydPUKlSJdja2uLu3bsYPXq0tC0/GH09ZELwcjzqLuurluDgYNSrVw9169bFo0ePYGtriw4dOsDPzw+GhoYAgOjoaMydOxclS5ZEdHQ0du7cKb0AEGX/2i7Lv//+C09PT5w/fx4+Pj4YMWJEjm1iYmJgYWEBmUyGjIwMXvKY8mXu3Lm4desWFi9eDDMzsxzL+eGIPuT06dNYsmQJjh49isDAQDg7OwN4F2g1NTVx+/Zt/PLLLzAyMsLo0aOhpaUlLaOvB8OsGktPT4dcLgcA/P3333BxcUFSUhKCgoJgbW2Ns2fPol27dujcuTN++OEHWFpaYsqUKahSpQqmTJkCCwsLbNq0CQMGDFDxM6GiIHtgSEtLg1wul4Lt48ePMXr0aLx+/RpDhgzBoEGDACDHmwJDB32OuLg46OrqQldXFwCPI8rdh46LyMhIzJ49GzExMfD29kb37t0B5Hx9AsAP218phtmvwIIFC2BnZ4fExERs2LABz549w9q1a2FtbY3IyEgMHz4cr169QmZmJr777jucPHkSCoUCTZo0wbJly9C6dWtVPwVSsexvEr6+vtIYtEGDBqFdu3YoV64cHjx4AHd3d8THx2PIkCEYOHCgiqsmom9F9teoK1eu4O3btyhdujSqVq0KADh37hyWL1+OFy9eYOzYsejWrVuO7ejrxTCrhrL/ce7YsQP9+vVDdHQ06tSpgyNHjmDFihWIi4uTAm1cXBzevHmDxMRE1KpVCzKZDD4+PtiyZQvOnj2LsmXLqvgZUVHh7e2N9evX46effsKDBw9w8eJFWFtbY+rUqahYsSIePHiAcePG4e+//8aSJUvQoUMHVZdMRVBuASK3ISxEeZH92PHx8cHevXvx5MkT2Nra4vvvv8fSpUsBAGfPnsWKFSvw8uVLDBs2DH379lVl2fQF8eOKGsp6kwgNDUVSUhICAgJQp04dAED79u3h4eEBExMTjBgxAteuXYOJiQmsrKxQu3ZtXLt2DT/88AM2bNiAPXv2MMiSZOvWrdi1axcOHz6MSZMmoWfPnrhy5QouXbqEKVOm4P79+6hQoQKWLFmCzp07o23btqoumYqg7EH2+vXruHnzJu7du/fJIJu9X4V9LJRd1rEzd+5cBAUFYdWqVXjw4AEsLS2xbt06DB06FADQrFkzjB07FsC7nlr6hnzZaW2poDx69EgUL15cyGQyMXv2bCGEUJpQ/PDhw6Jz586iYsWK0uVFhXg32f28efPE9evXv3TJVMSFhYWJqVOnCiHeXTXHxMREBAYGCl9fX1GiRAkxcOBAcfPmTaVtOIk9ZZd98vmpU6eKmjVriurVq4uSJUuKhQsXiufPn39yuxUrVkgX4iDK8ueff4qGDRuKw4cPCyGEOHbsmNDX1xc//vijqFy5shg+fLi07pUrV3jxn28Mw6yayO0P8/Tp0+L7778XDRs2FMnJyUII5cuG7tmzR/z00085AgevdkLZj4GsnxMTE0VsbKx48eKFaNiwoVi0aJHUXqlSJVG+fHkxbdq0HNsTvW/+/PmiVKlS4tSpUyIjI0O4uLgIHR0dce3atRzrZj+W1qxZI/T09MSWLVu+ZLmkJtavXy+ePn0qTp8+LczNzcW6deuEEEJ07dpVyOVy0a1bN6X1GWi/HTylTw1k/9pu7969iImJgVwuh729PVauXImhQ4eia9euOHLkiDQHqJaWFrp27YquXbsCUD6rk+PWvm3Zj6fExESkp6fDyMgIenp60NPTw5UrV/Dvv/+iUaNGAN5dgKN+/fro0KGDdNIXjyH6kIyMDPz+++9YtGgRWrRogbCwMISGhmLZsmWoXbu29Pok3nWmSMfimjVr4OXlhc2bN6NHjx4qfhakSh86aStrOMHcuXPRo0cPaVaVmjVrIj4+Ht99953Stjzx69vB37QayPqDHD9+PFxcXPDLL7/Aw8MDzs7OuHTpEjZs2IA7d+6gY8eOACDNo5cd59SjLFnH08yZM+Hg4IB69ephxIgROHv2LABAX18fJUuWxL59+3DmzBmMGzcOaWlpGDRoEK/sRTmI98a3vnnzBhcvXkTNmjVx5swZODk5Yd68eRg5ciRSUlIwdepU3LhxAzKZTDoW165dCy8vLwQFBTHIfuOyh9Hjx49j165duHz5Ml69eiWtc/fuXdy9exfFihWDQqHA7du30bdvX/j5+fE16lul4p5hyqOdO3cKCwsLERkZKRQKhXj16pVwcXERLVu2FGvWrBFnzpwRZcuWFQ0aNFB1qVREZf/KbcmSJaJkyZJi0aJFYsWKFaJatWqiVatWIiwsTAghxIwZM0Tt2rXFd999J5o2bSrS0tKEEBxeQB+WdYwIIaTXJj09PREUFCS1P336VLRs2VL6eliId2NkdXR0RGho6Betl4o2Ly8vYWBgICpVqiSKFSsmevXqJfbv3y+EECIgIEDUrVtXODg4iCZNmoiaNWtKw+n4GvVtYs+smrh79y7Kly8Pa2trCCFgZGSEOXPmwNjYGGFhYWjWrBk2btwIc3NzfiqlXGX1dkRGRkJTUxPr1q3DhAkT4O7ujhMnTkBHRwe+vr54/vw5pk+fjj179uDw4cM4ffo05HI5MjIyOLyAJNlfZ5YvX46+fftKvWeNGzfG3bt3YW9vj969ewMAXr16hcGDB0OhUGDw4MHStvHx8QgODmaP7DdOZOvhv3jxIvbu3YuDBw/i6tWrOHjwIBITE7Fq1SpcvHgR/fr1g4uLC8qWLYvvv/8eV65cgaamJjIzM/ka9Y3iPLNFnPj/8+stW7YMmzZtwrlz56Cvry+NO4uMjESDBg1w5coVaXougBNF0/8R2eZovHDhApo0aQIACAkJwaBBg6Tx1LGxsahZsyZ8fHwwfvx4pX3w8o+UXfbXl99++w1Hjx7FrFmzMHLkSPj6+kIul2PWrFnYs2cP3r59i0qVKuHly5fSeFq5XM5jinK1ZMkSxMTESNNOZjl37hw8PT3RoEED+Pn55XiP45W9vm1MO0VcVgjp0KED/vzzTyxZsgQApD/azMxM1KpVC3p6ekrbMchSlqxj6PXr12jUqBFWrlwJfX19REVFAYA0xszc3ByNGzfG48ePc+yDoYOyy3p9mThxIgYMGIDk5GR06NABQUFBcHJygkKhwLRp07B06VI4Ozujbt26GDp0KC5evCj18vOYIgA5vkm8fv06li9fjqioKMTHx0vtTZs2hbOzM4KCgvDs2TOlHlghBIPst06FQxwon0JCQoRcLhc//fSTOHfunLh+/bro2LGjsLe35xQk9FG7du0SzZs3Fy9fvhQZGRli+fLlQkNDQ8yfP19aJy0tTdSqVUtMnjxZhZWSujh9+rQwMjISERERQoh30wIeOHBAGBgYiP79+0vTBb6PcxNTbn755Rfp5ylTpggNDQ0REhKidLwcOHBA1K5dW8TExKiiRCrC+FFGjTg5OaF48eIYM2YMtm7dCj09PZiamuLUqVNS7xp7ZAnIOcwkPT0d6enpOHfuHLp06YJhw4ZBCIEJEybg9OnTqFChAmJiYqBQKDB9+nQVVk7qIiEhASVKlJCGN2lqasLR0REbNmzAjz/+iJIlS2LOnDkwMDBQGurCHll63+PHjzF58mTcunULM2fOxOzZs5GQkIARI0YgISEB9vb2MDExwYoVK2BkZAQzMzNVl0xFDMfMqqHY2Fg8ffoUaWlpsLW1hYaGBscLUa6ePHmC7777DgDQp08f3Lx5E3/88QeAd3PMBgcHY9KkSbC2tsayZctga2srfQ3M44k+5ubNm7C2tsa2bduUTt66c+cO7O3tERsbi2HDhmHNmjUqrJKKovfHSycmJmLBggWIjo7G0qVLUa1aNQDATz/9hOXLl0NfXx99+vTBvXv3cOjQIcjlcnbekBIeCWrI3NwcdevWRf369aUeWQYPet+sWbPQrFkzhISEAACCgoKQkpKCkSNHAng3n6yTkxMWLlyICxcu4Pz58wyylMOHZkcpX748Bg0ahCVLluDw4cNSu6GhIbp06YIdO3YgJCQE27Zt+1KlkprICrI7d+7EjRs3oK+vjxEjRuDmzZvw9/eX1lu6dCmmT5+OxMREtGnTBsePH5deoxhkKTu+Y30F+EdNuXn79i0ePHiAESNGIDIyEp07d8b48ePx66+/4sCBA+jUqRMMDAwwdOhQpKWlwdvbG0lJSZg8ebKqS6ciInvv1/bt2xETE4M3b97A09MTBgYGGD58OBYvXgxPT09cuXIFVlZWWLduHTIyMjB//nxUrVoVd+7cUfGzoKLowIED+PHHH2FkZAR/f384Ojpi8+bN6Nixo9KUbtOnT8fLly/h7OyMYsWKoXv37vywTTlwmAHRV+ru3bvw9fVF6dKlce/ePQghcP/+fWRkZMDe3h7z5s2T1k1NTcXSpUuxdOlS3L59GyYmJiqsnIqaSZMmYfPmzahdu7Y020VAQACaN2+Oq1evYteuXVi9ejXKli2LkiVL4vDhw5DL5WjSpAn69u2LMWPGqPgZkKrlNiyga9euiIyMRN26dVG2bFnUqFEDb968wa1btzBv3jxYWVlJ62YNOdi7dy+6dOnypcunIo5hlugrMn/+fLx48QLjxo1D2bJlsXDhQly9ehV+fn64ffs2AgMDsXHjRgBAeHg4WrRoIW2bmpqKxMREBllS4ufnh4ULF+LXX3+FjY0NDh06hE6dOqFSpUpYs2YNHBwcALy7KIJcLkfx4sUBAF5eXti2bRsiIiKUQgl9227duoUKFSpAR0cH+/fvx6FDh2BtbQ3g3QekJ0+ewMDAALNnz0b//v2VtvX29oaTkxOqV6+uitKpKFPZPApEVOB+/vlnYWpqKjp16iQCAgKEEEI0btxYuLq6SussW7ZM9O3bV6Snp6uqTFITr1+/Fj4+PiI4OFgIIURYWJgwNDQU69atEy1bthRVqlQRx44dU5qG6/z582LUqFHC3NxcREVFqahyKopOnTolZDKZGD9+vDhz5ozIyMgQffr0ETNnzhRCCBETEyN69+4tZDKZ6Natm4qrJXXCnlmir8yTJ0+wcuVKHD16FN999x0GDx6MhQsXYurUqTm+nuPJXvQpp0+fRtWqVREXF4fu3bvDzc0N7u7uOHz4MBwdHWFkZISjR4/Czs4OwLuLc+zbtw/NmjVDxYoVVVw9FTU///wzwsLC8M8//8DV1RUNGjSAg4MDNm/ejK5duyItLQ3Hjx9H+/btOY0b5RnDLNFXJGtcWlJSEu7duwcPDw/89ddfSElJgaOjIwICAlCiRAlVl0lF0KemOtq2bRv8/Pywfft2lC1bFgcOHMDp06el8daamprSfLIi27yyRIDyZbX/+ecfREREwMPDAz179sSjR4+goaGBNWvWoFKlStI2vOQx5RVPgydSMx/7/JkVRvT09FCrVi0cP34c06dPh6WlJR4/fgwDA4MvVSapESGEdOwEBgZi6NChmDBhAnbu3Cmt8+jRI9y9exdv377F06dPERgYCG1tbfj6+kJTUxOZmZlSWGGQpfdlfcgBgMqVK2Po0KG4desWUlJSEBsbi5MnTyI6OlppGwZZyiv2zBKpifHjx+N///sfmjdvnqeer+y9Gvfv30f58uWhoaHBXjNSkv14mDp1KlauXIk2bdogISEBJ06cgLu7O5YvX460tDR8//33ePToEUqWLAlDQ0NERkZCLper+BmQOsp6fUpOTkZ4eDiOHj2KJUuWcNgTfRaGWSI1cP36dYwaNQoJCQnw9/dHo0aN8hRK31+HX9vRh0RGRsLX1xeurq5o1qwZUlNTsX//fgwcOBDu7u5YsGABFAoFNm3aBD09PfTo0QNaWlocd02fLbehLTye6HMwzBKpidOnT2PlypW4e/cuVq9enadAy15Yyotdu3Zh4cKFSEpKwpEjR1C2bFlpWUhICMaOHYuDBw+iSZMmStvxwxFlyS2Y5uX44GsUFQSOmSUq4rI+bzZv3hxjxoyBlZUVRo0ahQsXLiiNQ8ttu6w3iePHj/NKTPRBMpkM+vr6+Oeff/DXX38B+L/jrmHDhtDX10d8fHyO7RhkCQBSUlKkIHv37l08fPgQ6enp+Qqyb968KfQ66evFMEtUxMlkMmRmZgIAWrRokadAm/1NIjAwEO3atcPLly+/eO2kHnr27Ilp06ahYcOGmD17Nk6dOiUdP2ZmZtDW1s41zNK3bcqUKcjIyICOjg4AwMfHBy1btkTTpk1Rs2ZN7Ny5E69evcp12+yvUWvWrMGcOXPw9u3bL1Y7fV04zICoiPrYVEknT56Ev78/7t27l2PIwftvEt7e3li7di169er1JcsnNZH9eDl06BB8fX1x//59jBkzBgYGBti1axfu3LmDa9eusSeWJH/88Qfat2+PGjVq4NSpUzhy5AgGDBiAwMBAGBgYIDQ0FKGhoZgyZQqGDx8OPT09advsx9zatWsxZswYbNmyBT179lTV0yE1xzBLVARlD7JBQUE4f/48dHR0UK9ePQwePBgAcOLECaxevRr379+XTgrLPkZtzZo18PLyQlBQEN8k6KPjF7OHiyNHjmDWrFm4fPkyWrVqhTZt2sDd3R1yuZxjZEmSnp6O8PBwTJgwAYaGhujZsyc0NDQwZswYaZ1p06ZhxYoVOHjwIJo2bSp9g5T9w7aXlxeCg4PRo0cPlTwP+jpwmAFREZQVZCdOnIgpU6ZAQ0MDycnJmDZtGmbNmgUAaN26Ndzc3FCxYkX06tULf/31lxQ0/P394ePjwyBLWLNmDQBIc8HmJvtQlfbt22PGjBlwcHCArq4uGjZsCLlcnqcxkPRtEEJALpfDwcEBixYtQkpKCsaNGycNZUpJSQEAzJo1C02aNMHChQul7bIH2YkTJyIoKIhBlv67QrlILhH9Z8HBwaJSpUriwoULQgghfvnlF6GtrS10dHSEp6entN6BAweEj4+PyMjIEEIIcePGDSGTycT27dtVUjcVHfv37xfm5ubC1dVVass6TnKjUCikn/fu3Ss6dOggHB0dxYkTJwq1TlIfWcdI1r+pqaniwIEDol69eqJmzZoiNTVVCCFEWlqaEEKIMWPGiG7duintIyAgQJQoUULs2rXrC1ZOXzMOMyAqghQKBRYsWACZTAZvb2/8+uuvGDRoEKZMmYLU1FRMmTIFM2bMwLRp05S2y/oa+P79+7C0tFRN8VRkxMXF4eeff8aGDRvQoEEDrFu3DkDehxwcPnwYs2fPRpkyZbBp0ybo6up+sdqp6Mk+/Ck1NRWZmZnQ09NDamoqIiIi4ObmBmNjY5w4cQJyuRzFihVD8+bNUbFiRWzatEk6tnx8fGBra8tvjajAMMwSFQEil7kWk5KS8O+//0JfXx/t2rWDk5MTxo8fj0uXLklXaFq6dCnGjRsnbfOxk8bo25Keni6Ncw0ICMD69evh4OCAZcuWAfhwoBVCSJe3jYmJwfnz51G/fn2UK1fuSz8FKqJmz56N06dPIzk5GRMmTEDXrl2RmZmJkydPws3NDYmJiahYsSKqVKmCCxcu4MqVKxxzTYWK73pEKqZQKKQg+/r1a2RkZAAA9PT0ULlyZdy8eROZmZno378/AEBbWxtdunTBvn374O7urrQvBlkC/m9MIwBs2LABUVFReP78Ofz8/KRjJrcxtFkfqjQ0NODr64sGDRrAzs6OQZYk/v7+CAgIQKNGjVCuXDl0794dy5cvh6amJhwcHODv748qVarg3LlzcHd3x59//gm5XI6MjAwGWSo0vGYckQpl9YABwJw5cxAREYHXr19j0qRJsLe3h6mpKYoXL45Hjx5h+/bt6N27NyZNmgRjY2N06tRJmoOWbxKUXdaHo1mzZmH58uUIDAxE9+7dsXv3bhw9ehSurq4IDAyUAq2mpmaOk3Nmz54Nf39/lC9fXpVPhVTs/W97tLS0sGrVKumkrYYNG+Knn36CEAKenp5o1aoVkpKSYGlpiTp16kBDQwMKhYKXqKXCpYqBukQkRGZmpvSzn5+fMDExEYsWLRKdOnUSFSpUENOnTxePHz8WGRkZYtKkSUJfX19YWloKGxsb6eSK7CfsEGX38uVLYW9vL/z8/KS2uLg4sXDhQlGuXDkxbtw4qT3reBJCiMDAQJ6cQ0II5deXsLAwsX79etGqVascJ5cuX75caGpqimXLlgkhlE8y/NgJh0QFhWGWSMWuXbsm3NzcxMGDB6W2WbNmierVq4upU6eKuLg4kZ6eLq5evSqOHDkivTmkp6erqmRSA+np6aJu3brCw8NDqT0xMVG0aNFCyOVy0bdvX6Vla9asEYaGhgyypBRkvb29hVwuF3Z2dkImkwkXFxfx7NkzpfVXrFghZDKZ2Lp165culUiw35/oC5o8eTJ69OgBW1tbAMD+/fsxYMAA6OnpoXPnztJ6U6dOBQBs2bIFGhoaGDJkCOrUqYM6deoAeHfyDr+2oyy5nfiXmZmJpk2b4ubNm7h58yaqV68O4N1Y7IYNGwIAjIyMpG337dsHV1dX7Nq1i/N+kjTk5PLly4iKisLp06dRrVo1hIWFYdiwYShTpgw8PDxgYmICAHB3d4eFhQW6d++uyrLpG8V3Q6IvJDIyEo8ePULdunWlts6dO2Pw4MEICAjAmTNn0LBhQxgbGwN4F2g1NDSwdOlSlC1bFi4uLtJ2HCNLWbIH2cjISCQkJKB06dKoXbs2PDw80Lx5c8ydOxeenp6wsbFBcnIy/vnnH/Tu3RujRo2SQkvnzp0RHh6OFi1aqPLpUBEg/v/4aX9/f5w8eRLFixeHnZ0dtLS0MHToUADAsGHDAABjx46VXrN69+4NAMjIyOCHbfqiODUX0ReU9Saxa9cu6Ovro2PHjgAANzc3HDp0CBMmTEDfvn1hZGQkbRMSEoKBAwcywFIOIttJWz4+Pti2bRv09fXx4sULtGvXDosXL8bDhw/Ru3dvlC5dGgqFAkIIJCcn49q1a9KJX+zpJwBISEiAgYGBdD8wMBDjx49HqVKlsH//ftSuXVtaFhQUhOHDh2PMmDGYNWuW0nZEXxrn8SH6AhQKBYB34ePu3buYOnUq1q5di5MnTwJ4N91N27ZtsXTpUmzduhVv3ryRtnV2dv7opUjp25UVZP38/BAcHIxNmzbh2rVr6NevH0JDQ3H9+nXY2dnh2LFjcHNzg729Pbp3746rV69Kx5RMJmOQJWzduhUuLi64fPmy1Obq6oqgoCCkpKRg7dq1uHPnjrRsyJAhWL58OS5evIjixYuromQiCXtmiQpZ9t6zrJ8PHTqEefPmwczMDCNHjkTr1q0BvHvzCA8Px7Bhw+Dq6so3CfqorCEGAwYMQK1ateDt7Y3du3dj8ODBWLBgAVxdXZGUlAS5XC7NO5uFXwVTltevX6Np06ZISUlBmzZt4OrqChsbG2l5SEgIpkyZgh9++AGjR49GxYoVpWVZr2kilwu/EH0p7JklKkTZX+C3b9+O0aNHIyMjAx07dsTkyZPx77//IiAgACdOnADw7mu977//HhcvXoS+vr4qS6ciKnv/Q2JiIgDgzp07aNiwIS5cuIBBgwZh4cKFcHV1RXp6OtavX4+IiAi832/BIEtZSpQoASsrK1hbWyMqKgorVqzApUuXpOXOzs6YMWMGdu7cidWrV+Pvv/+WljHIUlHAVzOiQpL9xJwLFy5g69atiIyMhJmZGSZPnowOHToAeDexfWBgIGQyGRwcHLB9+3bpqmB8k6Dssh9Tc+fORcmSJaVetH79+uHNmzdYt24dBgwYAODdGMg9e/YgMzMTbdq0UWXpVESJ/3/hlooVK6Jjx44QQmDKlClYv349NDQ0EBgYiHXr1sHFxQVyuRxDhw5FhQoVULVqVWkffI0iVWOYJSokWaHjp59+QlRUFIyNjaGjo4N169YhOTkZs2fPRocOHSCTyTBnzhzMmTMHhoaGsLW1la6aw8vTEvBuTGz37t1RtmxZaXjAnj17MH36dACAi4sLbty4gSdPnqBLly5QKBR48eIFnJyckJycnOOyx0RZsoKolZUV9u/fD39/f6SkpGDu3LkICwuDnp4e0tPTIZfL4eTkhNKlS6N9+/YqrppIGd8piQpY9q9zw8LCEBISgsWLF2Pnzp24fv06unfvjmPHjmH69OnIyMhA+/btMWHCBFStWlVpnBqDLAHAoUOHsGrVKkydOhUxMTHQ0tLC27dvERsbK81wYWNjAzc3N5iamqJChQpo0KABHB0d8fLlS5w+fZonENIHZb1emZub4+rVqwCAHj164MWLF0hLS5PmKs7i6OjI44mKHL5bEhWQYcOG4c6dO0pfuT158gSmpqaoUaMGNDU1UaxYMcyYMQPVq1dHYGAgZs+ejYyMDPzvf/+Dv7+/1CNLlKVjx45wd3fHnTt3MGnSJMTExKB48eLQ09OT5veUyWTo1q0bwsLCMG/ePAwYMAATJkzA+fPnIZfLkZGRwandKFdZr1f29vYwMzNDYmIi6tSpgypVqmDRokW4c+cOpk6ditu3byttx+OJihIOMyAqAL///juKFSuG8uXLK7WXLFkSMpkMjx8/RrVq1aBQKGBiYoIpU6bg8OHDOHToELS0tDBlyhTpzYE9spQla0iBm5sbhBDYunUrJk2ahGnTpqFy5crQ1dUF8H9XhDM1NYWLiwuKFSsm7YNzyFJeaGpq4ty5cyhVqhQaNGiAHTt2wMTEBHK5HOfOnUOlSpVUXSLRB3FqLqICknWyVnBwMOrVq4e6devi0aNHsLW1RYcOHeDn5wdDQ0MAQHR0tHQCT3R0NHbu3IkKFSqo+BlQUZLbmOnVq1dj27Zt0NHRwfHjx2FtbQ3g3cwEGhoaiI+PR5cuXbB48WKePEj5NnfuXNy6dQuLFy+GmZlZjuUcx09FFcMs0X+UdXIEAPz9999wcXFBUlISgoKCYG1tjbNnz6Jdu3bo3LkzfvjhB1haWmLKlCmoUqUKpkyZAgsLC2zatEk6A50oe2jw8/ODEAKDBw+GgYEB/Pz8sG3bNrx69QoDBgxAtWrVkJKSgtTUVCQmJmLkyJHsiaXPEhcXB11dXanHn+GV1AXDLFEBWbBgAezs7JCYmIgNGzbg2bNnWLt2LaytrREZGYnhw4fj1atXyMzMxHfffYeTJ09CoVCgSZMmWLZsmXThBKIsXl5e2Lx5M7y9vdG7d29YWFgAeBdwd+/ejYoVK2L+/PkoXbq00naZmZkc00hE3wyGWaLPlL3XYseOHejXrx+io6NRp04dHDlyBCtWrEBcXJwUaOPi4vDmzRskJiaiVq1akMlk8PHxwZYtW3D27FmULVtWxc+IipIdO3bAw8MDBw8elGa5yH7M+fv7Y9u2bTA2NkZQUBBKlSqlynKpCMqtZ5XDT+hrxO+iiD5T1ptEaGgokpKSEBAQgDp16gCANA/jihUrMGLECKxduxZ16tSBiYkJAODq1auYM2cOIiIicOTIEQZZyuH+/fvS2OusE8GyhxA3NzckJibi3r170nFFlCV7kL1+/To0NDSgra0NKyurj26X2+W3iYo6DoYh+g8eP34MZ2dnDBkyBE+fPgUAaf7F9u3bw8PDA6VKlUK3bt1w//59aTtTU1PY2Njg1KlT+P7771VQORV19+7dw4MHD6ChoQEtLS1kZmZCJpMhIyMDZ86cQUpKCry8vLB69WpO6UZKsq7qBQDTpk1D79690b17d9SvXx+LFi3CixcvPrhdVnhduXIlpkyZ8sVqJvovGGaJ8uH9wFC2bFkcPHgQdevWxf79+5GSkgJNTU1kZGQAeBdoXVxc0L17d5QrV07aztzcHJMmTUKNGjW+aP1U9HwohHbu3BmpqakICAgA8H/zesbFxWH27Nk4fPgwAEiXPeaJOpQlK5AuWLAAAQEBWL16Nf788090794d06dPR2xsbI5tsgfZtWvXwtvbG7Vr1/6idRN9Lo6ZJcqj7F/b7d27FzExMZDL5bC3t8fTp08xdOhQWFlZ4ciRIwD+b47Q7HhiDmWX/Zi6desWNDU1oa+vDwsLC8TGxmLs2LF4+vQp2rZti1GjRuHevXuYNm0anj59ivPnz/NYog/KyMhA79698b///Q+DBw9GWFgYXFxcMHfuXIwcOVJ6fRJCKH0YWrNmDby8vBAcHIwePXqo+FkQ5Q3DLFE+jR8/Hhs3bkT16tURHR0Na2tr9OrVC/Xr18fgwYNRpUoVHDp0CADDK31Y9p6wmTNnYtu2bcjIyMDbt28RFBSEjh074vHjx1i0aBEOHTqER48eoVKlSjA2NkZ4eDjkcjmPL5K8P7715cuXsLa2RlhYGNLS0uDo6IjFixfD1dUVKSkpmDlzJgYNGqT07dDatWsxYcIEBAUFoWfPnqp4GkSfRxBRnu3cuVNYWFiIyMhIoVAoxKtXr4SLi4to2bKlWLNmjThz5owoW7asaNCggapLJTUxffp0YWZmJg4cOCAePXokunTpIgwMDERwcLAQQojExEQRFxcn9u/fL6KiokRmZqYQQoj09HQVVk1FVVpamvRz1muTnp6eCAoKktqfPn0qWrZsKdatWye1rVixQujo6IjQ0NAvWi9RQeAgK6J8uHv3LsqXLw9ra2sIIWBkZIQ5c+bA2NgYYWFhaNasGTZu3Ahzc3OekEOfFB0djVOnTmHTpk1wdHREVFQUzp49i4YNG2LYsGHYtGkTdHR0YGxsjE6dOsHGxkY62YsXRiBAecz18uXL0bdvX7x69QoA0LhxY9y9exf29vbo3bs3AODVq1cYPHgwFAoFBg8eLG0bHx/PoQWktvhqSJQH4v9/haelpYWUlBSkpaVBX18fGRkZMDMzg4+PDxo0aIBr167BwcEBDg4OAHgFHfo4Q0ND9OjRA23btkV4eDhcXV0xa9YsjB49Gm3atIGHhwdSUlIwfPhwpe14TBGg/Pry22+/4c2bNwgLC4OZmRl8fX0xZMgQPH78GHv27EG9evVQqVIlvHz5EhkZGfj999+hqakpDVXhzAWkzviKSJQHWWPROnTogD///BNLliwBAKl3LDMzE7Vq1YKenp7SdgwdlCW3nvqKFSuiX79+kMlk2LhxI7p27YqRI0cCeDdThoWFBX7++WcIntpAuch6fZk4cSIGDBiA5ORkdOjQAUFBQXBycoJCocC0adOwdOlSODs7o27duhg6dCguXrwIuVyOjIwMjrmmrwJ7ZonyoWbNmtiwYQOGDRuGhIQE9OjRA8bGxpg5cyaMjY0/OSE5fZve70FLTU1FqVKlUKdOHZQqVQrx8fG4du0aunTpIk3tFh8fj6CgIDRs2FCafosT2NP7zpw5g7Vr12Lv3r1o3rw5MjIycPToUfTp0weDBg3C+vXr0apVK7Rq1Uppu8zMTA5Voa8Gj2SifHJyckLx4sUxZswYbN26FXp6ejA1NcWpU6ek8YzskaUsItu0R56enti2bRsSExNRtmxZWFlZYf/+/ShRogTs7e2xaNEivHr1Cr/99hvS09NRv359yGQyHlP0QQkJCShRooR09UFNTU04Ojpiw4YN+PHHH1GyZEnMmTMHBgYGSh+I2CNLXxNOzUX0mWJjY/H06VOkpaXB1tYWGhoauc4tS9+u7OHh6NGjGDduHNasWQMjIyNcv34d06dPh76+PiIjIwG8+7r42rVrMDMzw9q1azn9Fn3SzZs3YW1tjW3btimdvHXnzh3Y29sjNjYWw4YNw5o1a1RYJVHhYpglKiDsPaMP2bdvH/bs2YPixYtj5cqVAN4dL5cvX8aAAQPQrl07+Pn5AQCSk5Ohq6sLIPcLb9C36UOvL0lJSXB3d8f169cxbdo0dOjQAQDw4sULTJ48GW3btkX//v2xceNG9OnT50uXTfRF8FWSqIAwyFJu4uLisGDBAly5ckVp3KKGhgbq16+Pnj174uzZs1KIzQqyQggGWQKgHGS3b9+OmJgYvHnzBp6enjAwMMDw4cOxePFieHp64sqVK7CyssK6deuQkZGB+fPno2rVqrhz546KnwVR4eG7LxFRAXr/yy4TExNs3LgRbdu2RXR0NIKDg5WWV6lSBS9evEBiYqJSO0/2oixZQXbSpEnw9PTEoUOHsGPHDjRq1AinT59GgwYNMHXqVPTq1QuLFy/GvHnzoFAocPToUZiYmMDAwAAlSpRQ8bMgKjwcZkBEVECy96DduXMHMpkMenp6MDc3x7179+Dm5obExET07t0bI0aMwNOnT+Hk5AQdHR3s37+fAZY+yM/PDwsXLsSvv/4KGxsbHDp0CJ06dUKlSpWwZs0aaW7rV69eQS6Xo3jx4gAALy8vbNu2DREREZxthb5a7JklIioA2WctmDFjBrp3745OnTqhXr16WLduHaysrODn54fixYtj/PjxqFOnDtzd3SGXyxEaGirNWkD0vjdv3iA2NhZz5syBjY0Ndu/ejb59+2Lt2rUoW7YsXF1dcfz4caSkpMDY2BjFixfHhQsX4Obmhs2bN2Pv3r0MsvRVY88sEVEBmj17Nvz8/PDzzz+jadOmGDhwIMLDw3Hu3DnUrFkT9+7dw5gxY/DkyRM4OTlh7NixAIDU1FRoa2urtngqsk6fPo2qVasiLi4O3bt3h5ubG9zd3XH48GE4OjrCyMgIR48ehZ2dHQDg9evX2LdvH5o1a4aKFSuquHqiwsWeWSKi/yB7b6oQApcuXcLy5cvRrl07HDt2DKdOncK8efNQs2ZNpKenw8rKCkuXLoWZmRkOHDiAsLAwAGCQJQC5XykOAJo3bw5zc3NcvXoVpUqVkqbhyszMxIQJEzBo0CDY2NgAeHccGhkZYeDAgQyy9E1gmCUi+g+yhhZMmzYNCxcuRFRUFOrXr49Tp05h4MCBmDdvHkaOHInk5GTMmjULDx48QLVq1eDn5wcdHR3Mnz8fu3fvVvGzoKIg+1CVwMBADB06FBMmTMDOnTuldR49eoS7d+/i7du3ePr0KQIDA6GtrQ1fX19oamoiMzNTGnvNMdj0rWCYJSL6DNl70Hbs2IGQkBB07twZzZs3h4eHBzp16oQVK1bA1dUVwLuvfSMiInD69GkoFApUqVIFixcvhqWlJWxtbVX1NKiIyH6BjalTp2LixIl4/fo1rly5gj59+mDcuHEAAA8PDxgbG6N+/fpo2LAhHj58iKlTp0r74QU26FvESQyJiD5DVg/aqVOnEBERgZ9++gm1a9eGra0tli5ditatW2PIkCEAgPj4eLi4uEBTUxP9+vWTLntcvXp1bNmyBXK5XJVPhYqArCAbGRmJe/fu4cCBA2jWrBlSU1Oxf/9+DBw4ENra2liwYAH+/PNPbNq0CXp6eujRowe0tLR4gQ36pvEEMCKizxQbG4tmzZrh2bNn8PHxwaRJk5CRkYHx48cjIiICwLt5ZB8+fIiUlBRcunQpxyVqs/fI0bdt165dWLhwIZKSknDkyBGULVtWWhYSEoKxY8fi4MGDaNKkidJ2vOQxfes4zICI6DOZm5sjLCwMZmZm2LdvHy5fvgwtLS0sXboUM2fOhIODA8zNzfHjjz8iMjIScrkcGRkZSsGDQZayyGQy6Ovr459//sFff/0F4P8uwtGwYUPo6+sjPj4+x3YMsvStY88sEdF/dPXqVTg5OcHOzg5jxoyBtbV1ruuxB40+5eTJk5gxYwYUCgXmzJmDli1bAnh3WWQ7OzssWLAAP/zwg2qLJCpiGGaJiApAdHQ0XFxcYGtrCw8PD9SqVUvVJZEayT7c5NChQ/D19cX9+/cxZswYGBgYYNeuXbhz5w6uXbvGD0RE72GYJSIqINHR0RgxYgQqVKiARYsW8apLlMPHeuezB9ojR45g1qxZuHz5Mlq1aoU2bdpIV4xjDz+RMo6ZJSIqIDY2Nli1ahUMDAxQoUIFVZdDRciaNWsAQJoLNjcymUwaI9u+fXvMmDEDDg4O0NXVRcOGDSGXy5Gens4gS/Qe9swSERWwrB42hUIhTeFF364DBw7AxcUF3bp1Q0BAAIC899Du27cPAQEB0NDQwE8//QQHB4cvVjeRuuCrLBFRAcvqYWOQJQBo3LgxvL298dtvv2HYsGEA8t5D+7///Q8eHh54/fo1AgICkJyc/MXqJlIX7JklIiIqJOnp6dI414CAAKxfvx4ODg5YtmwZgA/30AohpA9EMTExOH/+POrXr49y5cp96adAVOSx24CIiKgQCCGkq7tt2LABUVFReP78Ofz8/ODu7g4g9x7arGEGGhoa8PX1RYMGDWBnZ8cgS/QBDLNERESFIGvc66xZszBx4kS0b98egYGBGDhwII4ePQpXV1cAyoE2+3jZNWvWYPbs2Vi8eDHKly+vmidBpAY4zICIiKiQxMXFoVu3bvjhhx8wevRoAMCrV6+wbt06rFq1Cr169ZKGHGQNSQDeBVkvLy8EBQWhZ8+eKqufSB2wZ5aIiKiQlChRAvHx8fjnn3+kNmNjY4wePRoVK1bEqlWr0K9fPwCQguzatWsxceJEBlmiPNJSdQFERERfg9ymYsvMzETTpk1x8+ZN3Lx5E9WrVwcA6OnpoWHDhgAAIyMjadt9+/bB1dUVu3btQo8ePb74cyBSRxxmQERE9B9lD7KRkZFISEhA6dKlUbt2bfz9999o3rw52rZtC09PT9jY2CA5ORkDBgyAg4MDRo0aJY2TVSgUOHPmDFq0aKHKp0OkVhhmiYiI/oPsJ235+Phg27Zt0NfXx4sXL9CuXTssXrwYDx8+RO/evVG6dGkoFAoIIZCcnIxr165BU1MTQghkZmZCS4tfmBLlF8fMEhER/QdZQdbPzw/BwcHYtGkTrl27hn79+iE0NBTXr1+HnZ0djh07Bjc3N9jb26N79+64evWqNJOBTCZjkCX6TOyZJSIi+g+yhhgMGDAAtWrVgre3N3bv3o3BgwdjwYIFcHV1RVJSEuRyuXSSV5aMjAyGWKL/iD2zRERE+ZS9HygxMREAcOfOHTRs2BAXLlzAoEGDsHDhQri6uiI9PR3r169HREQE3u8/YpAl+u/4V0RERJQP2U/2mjt3LkqWLAlXV1fY2NigX79+ePPmDdatW4cBAwYAABISErBnzx5kZmaiTZs2qiyd6KvEnlkiIqI88PPzw+PHj6GhoYGMjAwAwJ49e1C2bFkAgIuLC2rUqIFy5cqhS5cuUCgUePbsGfr374/k5GTpErZEVLAYZomIiD7h0KFDWLVqFaZOnYqYmBhoaWnh7du3iI2NhaamJgDAxsYGbm5uMDU1RYUKFdCgQQM4Ojri5cuXOH36tNJla4mo4PAEMCIiojzw9/fH9u3bYWVlhQULFsDCwgLVqlXDxo0b0ahRIwDvTuiKi4vDrl27kJaWBgsLC/Tq1Quampo82YuokPCvioiI6COyQqibmxuEENi6dSsmTZqEadOmoXLlytDV1QUAaZ5YU1NTuLi4oFixYtI+OIcsUeFhzywREdEH5HaJ2tWrV2Pbtm3Q0dHB8ePHYW1tDeDdzAQaGhqIj49Hly5dsHjxYqULKhBR4eDHRCIiolxkD7J+fn4QQmDw4MEYNWoUMjMzsW3bNlSvXh0//PADqlWrhpSUFKSmpiIxMREjR44EAAZZoi+AYZaIiCgXWUHWy8sLmzdvhre3N96+fQsDAwOMGTMGALB7927cvXsXw4YNQ+nSpZW2z8zMlE4OI6LCw2EGREREH7Bjxw54eHjg4MGDsLGxAaDcY+vv749t27bB2NgYQUFBKFWqlCrLJfomsWeWiIjoA+7fv4969eqhbt260olg2YcOuLm5ITExEffu3YOJiYkKKyX6djHMEhERfcC9e/fw4MEDaGhoQENDQxo6kJGRgfPnz6N+/frw8vKSTvTK7YQxIipc/IsjIqJvnkKhyLW9c+fOSE1NRUBAAABIY2Dj4uIwe/ZsHD58GMC7E72EEAyyRCrAnlkiIvqmZe9NvXXrFjQ1NaGvrw8LCwvY2trC1tYWO3bswKtXrzBq1Cjcu3cP06ZNw+vXr9GlSxdpP5y5gEg1eAIYERF9s7LPAztz5kxs27YNGRkZePv2LYKCgtCxY0c8fvwYixYtwqFDh/Do0SNUqlQJxsbGCA8Ph1wu56wFRCrGMEtERN+8GTNmIDAwEEFBQbC2tsaoUaNw6tQprFy5Es7OzkhKSkJqaip+++03lClTBnXr1oWGhgYvUUtUBPAvkIiIvmnR0dE4deoUNm3ahHbt2mHfvn04e/YsGjZsiGHDhkFDQwMDBgyAnp4eOnXqJG2nUCgYZImKAI5UJyKib5qhoSF69OiBtm3bIjw8HK6urpg1axaOHTuGFi1awMPDA+vXr8+xHU/2IioaOMyAiIi+GR+aOuvFixcoVaoUnJ2doauri1WrVkFTUxPOzs64ePEiSpUqhYiICJ7kRVQE8WMlERF9E7IH2d9++w3h4eG4du0aAKBUqVKIj4/HtWvXYGZmJs0lGx8fj6CgICnIsv+HqOjhYB8iIvrqZZ8D1tPTE9u2bUNiYiLKli0LKysr7N+/HyVKlIC9vT0WLVqEV69e4bfffkN6ejrq16/PCyIQFWEMs0RE9FXLPv3W0aNHceTIEezYsQNGRka4fv06pk+fDjs7O0RGRsLX1xfa2tq4du0aateujbVr10JTU5PTbxEVYRwzS0RE34R9+/Zhz549KF68OFauXAng3dCDy5cvY8CAAWjXrh38/PwAAMnJydDV1QUATr9FVMTx+xIiIvrqxcXFYcGCBdi+fTvu3r0rtWtoaKB+/fro2bMnrly5guTkZACQgqwQgkGWqIhjmCUioq/O+186mpiYYOPGjWjbti2io6MRHBystLxKlSp48eIFEhMTldo5ewFR0cdhBkRE9FXJfqLWnTt3IJPJoKenB3Nzc9y7dw9ubm5ITExE7969MWLECDx9+hROTk7Q0dHB/v37GWCJ1AzDLBERfTWyn+w1Y8YMhIWFIT09HW/evMHMmTMxbNgw3LlzB+7u7jhx4gQsLS1Rs2ZNJCUlYc+ePdDR0eGsBURqhn+tRET01cgKsrNnz8bq1auxZMkSREZGolGjRvDy8sL169dRqVIlrFq1Cm3atIGuri6aN2+Ow4cPQ0dHB6mpqQyyRGqGf7FERKT2FAqF9LMQApcuXcLy5cvRrl07HDt2DKdOncK8efNQs2ZNpKenw8rKCkuXLoWZmRkOHDiAsLAwAIC2traqngIRfSaGWSIiUntZvanTpk3DwoULERUVhfr16+PUqVMYOHAg5s2bh5EjRyI5ORmzZs3CgwcPUK1aNfj5+UFHRwfz58/H7t27VfwsiOhzMMwSEZHayt4ju2PHDoSEhKBz585o3rw5PDw80KlTJ6xYsQKurq4AgNevXyMiIgKnT5+GQqFAlSpVsHjxYlhaWsLW1lZVT4OI/gOeAEZERGrv1KlT2LlzJ6pWrQoPDw8sXboUS5cuhZ2dHfbt2wcAiI+PR9++fZGUlITjx49DU1NTOtkrPT0dcrlcxc+CiD4HZ4ImIiK1FhsbCxcXFzx79gw+Pj4AAA8PDzx69AgRERGwsbFBlSpV8PDhQ6SkpODSpUs5LlHLCyMQqS/2zBIRkdq7evUqevbsidKlS8PPzw+2trbIzMzEgQMHEBERIZ30NWbMGGhpafEStURfEYZZIiL6Kly9ehVOTk6ws7PDmDFjYG1tnet62XtkiUj98QQwIiL6KlhbWyMoKAhRUVFYtWoV/vrrr1zXY5Al+rqwZ5aIiL4q0dHRGDFiBCpUqIBFixbByspK1SURUSFizywREX1VbGxssGrVKhgYGKBChQqqLoeIChl7ZomI6KskhIBMJpOm3yKirxPDLBERfbWyAi0Rfb34UZWIiL5aDLJEXz+GWSIiIiJSWwyzRERERKS2GGaJiIiISG0xzBIRERGR2mKYJSIiIiK1xTBLRFTAWrZsibFjx0r3LS0t4evr+5/2efPmTTRq1Ag6Ojr4/vvv/9O+iIi+JlqqLoCISB05Oztj48aNOdpv376NsLAwyOXyAn286dOnQ19fH7du3ULx4sULdN8FRSaTYffu3ejWrZuqSyGibwjDLBHRZ+rQoQOCg4OV2kqXLg1NTc0Cf6w7d+6gU6dO/+nyrGlpaShWrFgBVkVEpHocZkBE9Jm0tbVhbm6udNPU1MwxzOB9b968wfDhw2FqaooSJUrAwcEBV65c+eD6MpkMly9fxqxZsyCTyTBjxgwAwLVr1+Dg4ABdXV2ULFkSw4cPx9u3b6XtnJ2d0a1bN8yfPx9lypRB1apVcf/+fchkMuzYsQP29vbQ1dVF/fr18ffff+PSpUuws7ND8eLF0aFDBzx//lza16VLl9C2bVuUKlUKhoaGaNGiBaKioqTllpaWAIDu3btDJpNJ94mIChvDLBHRFySEQKdOnRAbG4uDBw/i8uXLqFevHlq3bo24uLhct4mJiUGtWrXw008/ISYmBuPHj0dSUhI6dOgAY2NjXLp0CTt37sTx48cxevRopW1PnDiBGzdu4NixY9i/f7/UPn36dEyZMgVRUVHQ0tJC37594eXlhRUrVuDMmTO4c+cOpk2bJq2fkJAAJycnnDlzBhcuXECVKlXg6OiIhIQEAO/CLgAEBwcjJiZGuk9EVNg4zICI6DPt379fafxqx44dsXPnzo9uEx4ejmvXruHZs2fQ1tYGACxZsgR79uzBrl27MHz48BzbmJubQ0tLC8WLF4e5uTkAYN26dUhOTsamTZugr68PAFi1ahW6dOmChQsXwszMDACgr6+P9evXS8ML7t+/DwAYP3482rdvDwDw8PBA3759ceLECTRt2hQAMHToUISEhEg1ODg4KNW0Zs0aGBsbIyIiAp07d0bp0qUBAEZGRlKNRERfAsMsEdFnatWqFQICAqT7WaHyYy5fvoy3b9+iZMmSSu3Jycm4c+dOnh/7xo0bqFu3rtJjNm3aFAqFArdu3ZLCbJ06dXIdJ2ttbS39nH3d7G3Pnj2T7j979gzTpk3DyZMn8fTpU2RmZiIpKQkPHz7Mc81ERIWBYZaI6DPp6+ujcuXK+dpGoVDAwsICp06dyrHMyMgoz/sRQkAmk+W6LHv7hwJ29tkWstZ/v02hUEj3nZ2d8fz5c/j6+qJChQrQ1tZG48aNkZaWlueaiYgKA8MsEdEXVK9ePcTGxkJLS+s/nSRVs2ZNbNy4EYmJiVJgPXfuHDQ0NFC1atUCqvb/nDlzBqtXr4ajoyMA4NGjR3jx4oXSOnK5HJmZmQX+2EREH8MTwIiIvqA2bdqgcePG6NatG44cOYL79+/jt99+w5QpUxAZGZnn/fTv3x86OjpwcnLCn3/+ifDwcIwZMwYDBw6Uhg0UpMqVK2Pz5s24ceMGfv/9d/Tv3x+6urpK61haWuLEiROIjY3Fq1evCrwGIqLcMMwSEX1BMpkMBw8eRPPmzTFkyBBUrVoVffr0wf379/MVQvX09HDkyBHExcWhfv366NWrF1q3bo1Vq1YVSt1BQUF49eoVbGxsMHDgQLi7u8PU1FRpnaVLl+LYsWMoV64cbGxsCqUOIqL3yYQQQtVFEBERERF9DvbMEhEREZHaYpglIiIiIrXFMEtEREREaothloiIiIjUFsMsEREREakthlkiIiIiUlsMs0RERESkthhmiYiIiEhtMcwSERERkdpimCUiIiIitcUwS0RERERq6/8BkjxiPJvq5NAAAAAASUVORK5CYII=",
+      "text/plain": [
+       "<Figure size 800x400 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x400 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x400 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "for test, test_results in results.items():\n",
+    "    # Extracting keys and the second element of each tuple\n",
+    "    formats = list(test_results.keys())\n",
+    "    times = [value[1] for value in test_results.values()]\n",
+    "    \n",
+    "    # Creating the bar plot\n",
+    "    plt.figure(figsize=(8, 4))  # Optional: Adjust the figure size\n",
+    "    plt.bar(formats, times)  # You can customize the color\n",
+    "    plt.xlabel('File format')\n",
+    "    plt.ylabel('Time in seconds')\n",
+    "    plt.title(f\"Results from {test}\")\n",
+    "    \n",
+    "    # Rotate x-axis labels\n",
+    "    plt.xticks(rotation=45, ha='right')  # Rotates labels to 45 degrees\n",
+    "    #ax.set_xticklabels(group_labels, ha='right')\n",
+    "    \n",
+    "    plt.show()    "
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.8"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/notebooks/replicate-results-research/03-run-tests-ATL08.ipynb b/notebooks/replicate-results-research/03-run-tests-ATL08.ipynb
new file mode 100644
index 0000000..8646b1e
--- /dev/null
+++ b/notebooks/replicate-results-research/03-run-tests-ATL08.ipynb
@@ -0,0 +1,291 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 78,
+   "id": "19bcc8ae-7f82-4acc-9522-d1240c242c14",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import sys\n",
+    "import os\n",
+    "\n",
+    "# Get the current working directory\n",
+    "current_dir = os.getcwd()\n",
+    "\n",
+    "# Navigate two directories up from the current directory\n",
+    "module_path = os.path.abspath(os.path.join(current_dir, '..', '..'))\n",
+    "\n",
+    "# Add this path to sys.path\n",
+    "if module_path not in sys.path:\n",
+    "    sys.path.append(module_path)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 79,
+   "id": "e15343cc-8110-406b-8347-c99a8f0592e2",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from h5cloud.test_config import TestConfig\n",
+    "from h5cloud.tests.h5py_arr_mean import H5pyArrMean\n",
+    "from h5cloud.tests.h5coro_arr_mean import H5CoroArrMean\n",
+    "from h5cloud.tests.xarray_arr_mean import XarrayArrMean\n",
+    "import matplotlib.pyplot as plt"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 80,
+   "id": "998dedf3-9129-4700-87f8-de53df8efe94",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "tc = TestConfig.load_from_yaml(\n",
+    "    yaml_file=\"../../h5cloud/file_configs/ATL08_006.yaml\",\n",
+    "    results_bucket=\"nasa-veda-scratch\",\n",
+    "    results_directory=\"h5cloud-results\"\n",
+    ")\n",
+    "results = {}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 81,
+   "id": "f724aa6c-966a-41a1-9e62-9639becd9e70",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "fsspec_params = {\n",
+    "    # \"skip_instance_cache\": True\n",
+    "    \"cache_type\": \"blockcache\",  # or \"first\" with enough space\n",
+    "    \"block_size\": 8*1024*1024 # could be bigger\n",
+    "}\n",
+    "driver_kwds = { # only recent versions of xarray and h5netcdf allow this correctly\n",
+    "    \"page_buf_size\": 32*1024*1024, # this one only works in repacked files\n",
+    "    \"rdcc_nbytes\": 8*1024*1024 # this one is to read the chunks \n",
+    "}\n",
+    "io_params = {\n",
+    "    \"fsspec_params\": fsspec_params,\n",
+    "    \"h5py_params\": { \"driver_kwds\": driver_kwds }\n",
+    "}"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "57709b4b-0ea0-4489-8b5d-1434edd95644",
+   "metadata": {},
+   "source": [
+    "# H5Py Array Mean"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 82,
+   "id": "f59b23dc-dbca-455c-91ad-c3b9f0e53527",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "h5py_arr_test = H5pyArrMean(tc, store_results=False)\n",
+    "results['h5py_arr_test'] = {}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 83,
+   "id": "3cc33911-4ee5-464a-94d1-ea49abb4dfd4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "for file_format, file in tc.files.items():\n",
+    "    # run test on file\n",
+    "    if 'kerchunk' not in file_format:\n",
+    "        results['h5py_arr_test'][file_format] = h5py_arr_test.run(file_format)\n",
+    "        results['h5py_arr_test'][f\"{file_format}_wparams\"] = h5py_arr_test.run(file_format=file_format, io_params=io_params)\n",
+    "    "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "daf84f7a-65c3-4fd7-837b-e970bce76106",
+   "metadata": {},
+   "source": [
+    "# H5Coro Array Mean"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 84,
+   "id": "196ac55e-d6af-40d4-a2c3-e7d030e788ee",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "h5coro_arr_test = H5CoroArrMean(tc, store_results=False)\n",
+    "results['h5coro_arr_test'] = {}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 85,
+   "id": "e81afb70-0ed9-4bd4-aa7b-8a2a0726fedb",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "for file_format, file in tc.files.items():\n",
+    "    # run test on file\n",
+    "    if 'kerchunk' not in file_format:\n",
+    "        results['h5coro_arr_test'][file_format] = h5coro_arr_test.run(file_format)\n",
+    "    "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "499ab253-e512-47f8-a178-426b502547df",
+   "metadata": {},
+   "source": [
+    "# Xarray Array Mean"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "296c3883-c948-4c82-9dd8-6f288cbd69bb",
+   "metadata": {},
+   "source": [
+    "TODO: Add optimal arguments for opening data from https://gist.github.com/betolink/b545c364f80882c113b8cc27b763c729\n",
+    "\n",
+    "Note: it does seem like the first time tests are run a cache is created, despite efforts to pass cache=False and ds.close()."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 86,
+   "id": "bd91d1e0-0406-478f-a32f-4c6b001b5018",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "xr_arr_test = XarrayArrMean(tc, store_results=False)\n",
+    "results['xr_arr_test'] = {}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 87,
+   "id": "96d56a68-2082-4264-b1f5-161c77d34f4e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "for file_format, file in tc.files.items():\n",
+    "    results['xr_arr_test'][file_format] = xr_arr_test.run(file_format)\n",
+    "    if file_format != 'original':\n",
+    "        results['xr_arr_test'][f\"{file_format}_wparams\"] = xr_arr_test.run(file_format=file_format, io_params=io_params)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 88,
+   "id": "e0ba8c9f-18ea-419d-aac8-ac3bae976ff2",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'kerchunk': (187.93385314941406, 0.6074647903442383),\n",
+       " 'kerchunk_wparams': (187.93385314941406, 0.23067593574523926),\n",
+       " 'kerchunk_repacked_page_4mb': (187.93385314941406, 0.27347660064697266),\n",
+       " 'kerchunk_repacked_page_4mb_wparams': (187.93385314941406,\n",
+       "  0.2910616397857666),\n",
+       " 'original': (187.93385314941406, 4.656043529510498),\n",
+       " 'repacked_page_4mb': (187.93385314941406, 2.516477346420288),\n",
+       " 'repacked_page_4mb_wparams': (187.93385314941406, 1.7316017150878906)}"
+      ]
+     },
+     "execution_count": 88,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "results['xr_arr_test'] "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 89,
+   "id": "fc495706-4d30-4973-a7b4-3b5324b77525",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x400 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x400 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x400 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "for test, test_results in results.items():\n",
+    "    # Extracting keys and the second element of each tuple\n",
+    "    formats = list(test_results.keys())\n",
+    "    times = [value[1] for value in test_results.values()]\n",
+    "    \n",
+    "    # Creating the bar plot\n",
+    "    plt.figure(figsize=(8, 4))  # Optional: Adjust the figure size\n",
+    "    plt.bar(formats, times)  # You can customize the color\n",
+    "    plt.xlabel('File format')\n",
+    "    plt.ylabel('Time in seconds')\n",
+    "    plt.title(f\"Results from {test}\")\n",
+    "    \n",
+    "    # Rotate x-axis labels\n",
+    "    plt.xticks(rotation=45, ha='right')  # Rotates labels to 45 degrees\n",
+    "    #ax.set_xticklabels(group_labels, ha='right')\n",
+    "    \n",
+    "    plt.show()    "
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.8"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/notebooks/replicate-results-research/03-run-tests-GPM_3IMERGHHE.ipynb b/notebooks/replicate-results-research/03-run-tests-GPM_3IMERGHHE.ipynb
new file mode 100644
index 0000000..c97ce03
--- /dev/null
+++ b/notebooks/replicate-results-research/03-run-tests-GPM_3IMERGHHE.ipynb
@@ -0,0 +1,283 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "id": "19bcc8ae-7f82-4acc-9522-d1240c242c14",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import sys\n",
+    "import os\n",
+    "\n",
+    "# Get the current working directory\n",
+    "current_dir = os.getcwd()\n",
+    "\n",
+    "# Navigate two directories up from the current directory\n",
+    "module_path = os.path.abspath(os.path.join(current_dir, '..', '..'))\n",
+    "\n",
+    "# Add this path to sys.path\n",
+    "if module_path not in sys.path:\n",
+    "    sys.path.append(module_path)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 50,
+   "id": "e15343cc-8110-406b-8347-c99a8f0592e2",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from h5cloud.test_config import TestConfig\n",
+    "from h5cloud.tests.h5py_arr_mean import H5pyArrMean\n",
+    "from h5cloud.tests.h5coro_arr_mean import H5CoroArrMean\n",
+    "from h5cloud.tests.xarray_arr_mean import XarrayArrMean\n",
+    "import matplotlib.pyplot as plt"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 51,
+   "id": "998dedf3-9129-4700-87f8-de53df8efe94",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "tc = TestConfig.load_from_yaml(\n",
+    "    yaml_file=\"../../h5cloud/file_configs/GPM_3IMERGHHE_06.yaml\",\n",
+    "    results_bucket=\"nasa-veda-scratch\",\n",
+    "    results_directory=\"h5cloud-results\"\n",
+    ")\n",
+    "results = {}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 52,
+   "id": "f724aa6c-966a-41a1-9e62-9639becd9e70",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "fsspec_params = {\n",
+    "    # \"skip_instance_cache\": True\n",
+    "    \"cache_type\": \"blockcache\",  # or \"first\" with enough space\n",
+    "    \"block_size\": 8*1024*1024 # could be bigger\n",
+    "}\n",
+    "driver_kwds = { # only recent versions of xarray and h5netcdf allow this correctly\n",
+    "    \"page_buf_size\": 32*1024*1024, # this one only works in repacked files\n",
+    "    \"rdcc_nbytes\": 8*1024*1024 # this one is to read the chunks \n",
+    "}\n",
+    "io_params = {\n",
+    "    \"fsspec_params\": fsspec_params,\n",
+    "    \"h5py_params\": { \"driver_kwds\": driver_kwds }\n",
+    "}"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "57709b4b-0ea0-4489-8b5d-1434edd95644",
+   "metadata": {},
+   "source": [
+    "# H5Py Array Mean"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 53,
+   "id": "f59b23dc-dbca-455c-91ad-c3b9f0e53527",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "h5py_arr_test = H5pyArrMean(tc, store_results=False)\n",
+    "results['h5py_arr_test'] = {}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 54,
+   "id": "3cc33911-4ee5-464a-94d1-ea49abb4dfd4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "for file_format, file in tc.files.items():\n",
+    "    # run test on file\n",
+    "    if 'kerchunk' not in file_format:\n",
+    "        results['h5py_arr_test'][file_format] = h5py_arr_test.run(file_format)\n",
+    "        results['h5py_arr_test'][f\"{file_format}_wparams\"] = h5py_arr_test.run(file_format=file_format, io_params=io_params)\n",
+    "    "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "daf84f7a-65c3-4fd7-837b-e970bce76106",
+   "metadata": {},
+   "source": [
+    "# H5Coro Array Mean\n",
+    "\n",
+    "H5Coro doesn't work for the Grid/precipitationCal dataset since it has 3 dimensions."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 55,
+   "id": "196ac55e-d6af-40d4-a2c3-e7d030e788ee",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# h5coro_arr_test = H5CoroArrMean(tc, store_results=False)\n",
+    "# results['h5coro_arr_test'] = {}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 56,
+   "id": "e81afb70-0ed9-4bd4-aa7b-8a2a0726fedb",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# for file_format, file in tc.files.items():\n",
+    "#     # run test on file\n",
+    "#     if 'kerchunk' not in file_format:\n",
+    "#         results['h5coro_arr_test'][file_format] = h5coro_arr_test.run(file_format)\n",
+    "    "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "499ab253-e512-47f8-a178-426b502547df",
+   "metadata": {},
+   "source": [
+    "# Xarray Array Mean"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "296c3883-c948-4c82-9dd8-6f288cbd69bb",
+   "metadata": {},
+   "source": [
+    "TODO: Add optimal arguments for opening data from https://gist.github.com/betolink/b545c364f80882c113b8cc27b763c729\n",
+    "\n",
+    "Note: it does seem like the first time tests are run a cache is created, despite efforts to pass cache=False and ds.close()."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 57,
+   "id": "bd91d1e0-0406-478f-a32f-4c6b001b5018",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "xr_arr_test = XarrayArrMean(tc, store_results=False)\n",
+    "results['xr_arr_test'] = {}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 58,
+   "id": "96d56a68-2082-4264-b1f5-161c77d34f4e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "for file_format, file in tc.files.items():\n",
+    "    results['xr_arr_test'][file_format] = xr_arr_test.run(file_format)\n",
+    "    if file_format != 'original':\n",
+    "        results['xr_arr_test'][f\"{file_format}_wparams\"] = xr_arr_test.run(file_format=file_format, io_params=io_params)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 59,
+   "id": "e0ba8c9f-18ea-419d-aac8-ac3bae976ff2",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'kerchunk': (0.1435171663761139, 0.32570505142211914),\n",
+       " 'kerchunk_wparams': (0.1435171663761139, 0.2596704959869385),\n",
+       " 'kerchunk_repacked_page_4mb': (0.1435171663761139, 0.301281213760376),\n",
+       " 'kerchunk_repacked_page_4mb_wparams': (0.1435171663761139,\n",
+       "  0.4843318462371826),\n",
+       " 'original': (0.1435171663761139, 4.738888502120972),\n",
+       " 'repacked_page_4mb': (0.1435171663761139, 0.6849892139434814),\n",
+       " 'repacked_page_4mb_wparams': (0.1435171663761139, 0.5416264533996582)}"
+      ]
+     },
+     "execution_count": 59,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "results['xr_arr_test'] "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 60,
+   "id": "fc495706-4d30-4973-a7b4-3b5324b77525",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x400 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x400 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "for test, test_results in results.items():\n",
+    "    # Extracting keys and the second element of each tuple\n",
+    "    formats = list(test_results.keys())\n",
+    "    times = [value[1] for value in test_results.values()]\n",
+    "    \n",
+    "    # Creating the bar plot\n",
+    "    plt.figure(figsize=(8, 4))  # Optional: Adjust the figure size\n",
+    "    plt.bar(formats, times)  # You can customize the color\n",
+    "    plt.xlabel('File format')\n",
+    "    plt.ylabel('Time in seconds')\n",
+    "    plt.title(f\"Results from {test}\")\n",
+    "    \n",
+    "    # Rotate x-axis labels\n",
+    "    plt.xticks(rotation=45, ha='right')  # Rotates labels to 45 degrees\n",
+    "    #ax.set_xticklabels(group_labels, ha='right')\n",
+    "    \n",
+    "    plt.show()    "
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.8"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/notebooks/replicate-results-research/03-run-tests-OMVFPITMET.ipynb b/notebooks/replicate-results-research/03-run-tests-OMVFPITMET.ipynb
new file mode 100644
index 0000000..bb21a51
--- /dev/null
+++ b/notebooks/replicate-results-research/03-run-tests-OMVFPITMET.ipynb
@@ -0,0 +1,288 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 51,
+   "id": "19bcc8ae-7f82-4acc-9522-d1240c242c14",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import sys\n",
+    "import os\n",
+    "\n",
+    "# Get the current working directory\n",
+    "current_dir = os.getcwd()\n",
+    "\n",
+    "# Navigate two directories up from the current directory\n",
+    "module_path = os.path.abspath(os.path.join(current_dir, '..', '..'))\n",
+    "\n",
+    "# Add this path to sys.path\n",
+    "if module_path not in sys.path:\n",
+    "    sys.path.append(module_path)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 52,
+   "id": "e15343cc-8110-406b-8347-c99a8f0592e2",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from h5cloud.test_config import TestConfig\n",
+    "from h5cloud.tests.h5py_arr_mean import H5pyArrMean\n",
+    "from h5cloud.tests.h5coro_arr_mean import H5CoroArrMean\n",
+    "from h5cloud.tests.xarray_arr_mean import XarrayArrMean\n",
+    "import matplotlib.pyplot as plt"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 53,
+   "id": "998dedf3-9129-4700-87f8-de53df8efe94",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "tc = TestConfig.load_from_yaml(\n",
+    "    yaml_file=\"../../h5cloud/file_configs/OMVFPITMET_003.yaml\",\n",
+    "    results_bucket=\"nasa-veda-scratch\",\n",
+    "    results_directory=\"h5cloud-results\"\n",
+    ")\n",
+    "results = {}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 54,
+   "id": "f724aa6c-966a-41a1-9e62-9639becd9e70",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "fsspec_params = {\n",
+    "    # \"skip_instance_cache\": True\n",
+    "    \"cache_type\": \"blockcache\",  # or \"first\" with enough space\n",
+    "    \"block_size\": 8*1024*1024 # could be bigger\n",
+    "}\n",
+    "driver_kwds = { # only recent versions of xarray and h5netcdf allow this correctly\n",
+    "    \"page_buf_size\": 32*1024*1024, # this one only works in repacked files\n",
+    "    \"rdcc_nbytes\": 8*1024*1024 # this one is to read the chunks \n",
+    "}\n",
+    "io_params = {\n",
+    "    \"fsspec_params\": fsspec_params,\n",
+    "    \"h5py_params\": { \"driver_kwds\": driver_kwds }\n",
+    "}"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "57709b4b-0ea0-4489-8b5d-1434edd95644",
+   "metadata": {},
+   "source": [
+    "# H5Py Array Mean"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 55,
+   "id": "f59b23dc-dbca-455c-91ad-c3b9f0e53527",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "h5py_arr_test = H5pyArrMean(tc, store_results=False)\n",
+    "results['h5py_arr_test'] = {}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 56,
+   "id": "3cc33911-4ee5-464a-94d1-ea49abb4dfd4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "for file_format, file in tc.files.items():\n",
+    "    # run test on file\n",
+    "    if 'kerchunk' not in file_format:\n",
+    "        results['h5py_arr_test'][file_format] = h5py_arr_test.run(file_format)\n",
+    "        results['h5py_arr_test'][f\"{file_format}_wparams\"] = h5py_arr_test.run(file_format=file_format, io_params=io_params)\n",
+    "    "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "daf84f7a-65c3-4fd7-837b-e970bce76106",
+   "metadata": {},
+   "source": [
+    "# H5Coro Array Mean"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 57,
+   "id": "196ac55e-d6af-40d4-a2c3-e7d030e788ee",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "h5coro_arr_test = H5CoroArrMean(tc, store_results=False)\n",
+    "results['h5coro_arr_test'] = {}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 58,
+   "id": "e81afb70-0ed9-4bd4-aa7b-8a2a0726fedb",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "for file_format, file in tc.files.items():\n",
+    "    # run test on file\n",
+    "    if 'kerchunk' not in file_format:\n",
+    "        results['h5coro_arr_test'][file_format] = h5coro_arr_test.run(file_format)\n",
+    "    "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "499ab253-e512-47f8-a178-426b502547df",
+   "metadata": {},
+   "source": [
+    "# Xarray Array Mean"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "296c3883-c948-4c82-9dd8-6f288cbd69bb",
+   "metadata": {},
+   "source": [
+    "Note: it does seem like the first time tests are run a cache is created, despite efforts to pass cache=False and ds.close()."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 59,
+   "id": "bd91d1e0-0406-478f-a32f-4c6b001b5018",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "xr_arr_test = XarrayArrMean(tc, store_results=False)\n",
+    "results['xr_arr_test'] = {}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 60,
+   "id": "96d56a68-2082-4264-b1f5-161c77d34f4e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "for file_format, file in tc.files.items():\n",
+    "    results['xr_arr_test'][file_format] = xr_arr_test.run(file_format)\n",
+    "    if file_format != 'original':\n",
+    "        results['xr_arr_test'][f\"{file_format}_wparams\"] = xr_arr_test.run(file_format=file_format, io_params=io_params)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 61,
+   "id": "e0ba8c9f-18ea-419d-aac8-ac3bae976ff2",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'kerchunk': (99149.9609375, 0.3055531978607178),\n",
+       " 'kerchunk_wparams': (99149.9609375, 0.2577502727508545),\n",
+       " 'kerchunk_repacked_page_4mb': (99149.9609375, 0.265244722366333),\n",
+       " 'kerchunk_repacked_page_4mb_wparams': (99149.9609375, 0.27146339416503906),\n",
+       " 'original': (99149.9609375, 3.451099395751953),\n",
+       " 'repacked_page_4mb': (99149.9609375, 0.22344636917114258),\n",
+       " 'repacked_page_4mb_wparams': (99149.9609375, 0.3026292324066162)}"
+      ]
+     },
+     "execution_count": 61,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "results['xr_arr_test'] "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 62,
+   "id": "fc495706-4d30-4973-a7b4-3b5324b77525",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x400 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x400 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x400 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "for test, test_results in results.items():\n",
+    "    # Extracting keys and the second element of each tuple\n",
+    "    formats = list(test_results.keys())\n",
+    "    times = [value[1] for value in test_results.values()]\n",
+    "    \n",
+    "    # Creating the bar plot\n",
+    "    plt.figure(figsize=(8, 4))  # Optional: Adjust the figure size\n",
+    "    plt.bar(formats, times)  # You can customize the color\n",
+    "    plt.xlabel('File format')\n",
+    "    plt.ylabel('Time in seconds')\n",
+    "    plt.title(f\"Results from {test}\")\n",
+    "    \n",
+    "    # Rotate x-axis labels\n",
+    "    plt.xticks(rotation=45, ha='right')  # Rotates labels to 45 degrees\n",
+    "    #ax.set_xticklabels(group_labels, ha='right')\n",
+    "    \n",
+    "    plt.show()    "
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.8"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/notebooks/replicate-results-research/03-run-tests-SNDRSNIML2CCPRETN.ipynb b/notebooks/replicate-results-research/03-run-tests-SNDRSNIML2CCPRETN.ipynb
new file mode 100644
index 0000000..9f49a93
--- /dev/null
+++ b/notebooks/replicate-results-research/03-run-tests-SNDRSNIML2CCPRETN.ipynb
@@ -0,0 +1,288 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "id": "19bcc8ae-7f82-4acc-9522-d1240c242c14",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import sys\n",
+    "import os\n",
+    "\n",
+    "# Get the current working directory\n",
+    "current_dir = os.getcwd()\n",
+    "\n",
+    "# Navigate two directories up from the current directory\n",
+    "module_path = os.path.abspath(os.path.join(current_dir, '..', '..'))\n",
+    "\n",
+    "# Add this path to sys.path\n",
+    "if module_path not in sys.path:\n",
+    "    sys.path.append(module_path)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "id": "e15343cc-8110-406b-8347-c99a8f0592e2",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from h5cloud.test_config import TestConfig\n",
+    "from h5cloud.tests.h5py_arr_mean import H5pyArrMean\n",
+    "from h5cloud.tests.h5coro_arr_mean import H5CoroArrMean\n",
+    "from h5cloud.tests.xarray_arr_mean import XarrayArrMean\n",
+    "import matplotlib.pyplot as plt"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "id": "998dedf3-9129-4700-87f8-de53df8efe94",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "tc = TestConfig.load_from_yaml(\n",
+    "    yaml_file=\"../../h5cloud/file_configs/SNDRSNIML2CCPRETN_2.yaml\",\n",
+    "    results_bucket=\"nasa-veda-scratch\",\n",
+    "    results_directory=\"h5cloud-results\"\n",
+    ")\n",
+    "results = {}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "id": "f724aa6c-966a-41a1-9e62-9639becd9e70",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "fsspec_params = {\n",
+    "    # \"skip_instance_cache\": True\n",
+    "    \"cache_type\": \"blockcache\",  # or \"first\" with enough space\n",
+    "    \"block_size\": 8*1024*1024 # could be bigger\n",
+    "}\n",
+    "driver_kwds = { # only recent versions of xarray and h5netcdf allow this correctly\n",
+    "    \"page_buf_size\": 32*1024*1024, # this one only works in repacked files\n",
+    "    \"rdcc_nbytes\": 8*1024*1024 # this one is to read the chunks \n",
+    "}\n",
+    "io_params = {\n",
+    "    \"fsspec_params\": fsspec_params,\n",
+    "    \"h5py_params\": { \"driver_kwds\": driver_kwds }\n",
+    "}"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "57709b4b-0ea0-4489-8b5d-1434edd95644",
+   "metadata": {},
+   "source": [
+    "# H5Py Array Mean"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "id": "f59b23dc-dbca-455c-91ad-c3b9f0e53527",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "h5py_arr_test = H5pyArrMean(tc, store_results=False)\n",
+    "results['h5py_arr_test'] = {}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "id": "3cc33911-4ee5-464a-94d1-ea49abb4dfd4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "for file_format, file in tc.files.items():\n",
+    "    # run test on file\n",
+    "    if 'kerchunk' not in file_format:\n",
+    "        results['h5py_arr_test'][file_format] = h5py_arr_test.run(file_format)\n",
+    "        results['h5py_arr_test'][f\"{file_format}_wparams\"] = h5py_arr_test.run(file_format=file_format, io_params=io_params)\n",
+    "    "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "daf84f7a-65c3-4fd7-837b-e970bce76106",
+   "metadata": {},
+   "source": [
+    "# H5Coro Array Mean"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "id": "196ac55e-d6af-40d4-a2c3-e7d030e788ee",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "h5coro_arr_test = H5CoroArrMean(tc, store_results=False)\n",
+    "results['h5coro_arr_test'] = {}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "id": "e81afb70-0ed9-4bd4-aa7b-8a2a0726fedb",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "for file_format, file in tc.files.items():\n",
+    "    # run test on file\n",
+    "    if 'kerchunk' not in file_format:\n",
+    "        results['h5coro_arr_test'][file_format] = h5coro_arr_test.run(file_format)\n",
+    "    "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "499ab253-e512-47f8-a178-426b502547df",
+   "metadata": {},
+   "source": [
+    "# Xarray Array Mean"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "296c3883-c948-4c82-9dd8-6f288cbd69bb",
+   "metadata": {},
+   "source": [
+    "Note: it does seem like the first time tests are run a cache is created, despite efforts to pass cache=False and ds.close()."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "id": "bd91d1e0-0406-478f-a32f-4c6b001b5018",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "xr_arr_test = XarrayArrMean(tc, store_results=False)\n",
+    "results['xr_arr_test'] = {}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 46,
+   "id": "96d56a68-2082-4264-b1f5-161c77d34f4e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "for file_format, file in tc.files.items():\n",
+    "    results['xr_arr_test'][file_format] = xr_arr_test.run(file_format)\n",
+    "    if file_format != 'original':\n",
+    "        results['xr_arr_test'][f\"{file_format}_wparams\"] = xr_arr_test.run(file_format=file_format, io_params=io_params)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "id": "e0ba8c9f-18ea-419d-aac8-ac3bae976ff2",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'kerchunk': (254.5687713623047, 0.615347146987915),\n",
+       " 'kerchunk_wparams': (254.5687713623047, 0.478543758392334),\n",
+       " 'kerchunk_repacked_page_4mb': (254.5687713623047, 0.7147064208984375),\n",
+       " 'kerchunk_repacked_page_4mb_wparams': (254.5687713623047, 0.576711893081665),\n",
+       " 'original': (254.5687713623047, 1.1119279861450195),\n",
+       " 'repacked_page_4mb': (254.5687713623047, 7.316617488861084),\n",
+       " 'repacked_page_4mb_wparams': (254.5687713623047, 1.3438646793365479)}"
+      ]
+     },
+     "execution_count": 47,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "results['xr_arr_test'] "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 48,
+   "id": "fc495706-4d30-4973-a7b4-3b5324b77525",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x400 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x400 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x400 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "for test, test_results in results.items():\n",
+    "    # Extracting keys and the second element of each tuple\n",
+    "    formats = list(test_results.keys())\n",
+    "    times = [value[1] for value in test_results.values()]\n",
+    "    \n",
+    "    # Creating the bar plot\n",
+    "    plt.figure(figsize=(8, 4))  # Optional: Adjust the figure size\n",
+    "    plt.bar(formats, times)  # You can customize the color\n",
+    "    plt.xlabel('File format')\n",
+    "    plt.ylabel('Time in seconds')\n",
+    "    plt.title(f\"Results from {test}\")\n",
+    "    \n",
+    "    # Rotate x-axis labels\n",
+    "    plt.xticks(rotation=45, ha='right')  # Rotates labels to 45 degrees\n",
+    "    #ax.set_xticklabels(group_labels, ha='right')\n",
+    "    \n",
+    "    plt.show()    "
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.8"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/notebooks/replicate-results-research/README.md b/notebooks/replicate-results-research/README.md
new file mode 100644
index 0000000..55d9914
--- /dev/null
+++ b/notebooks/replicate-results-research/README.md
@@ -0,0 +1,31 @@
+# H5Cloud Optimization Research
+
+The goal of this research was 2 fold:
+
+1. Replicate the results of cloud-optimized formatting (h5repack) and open file options for fsspec and f5py for ATL03 found in [HDF at the speed of Zarr](https://docs.google.com/presentation/d/1iYFvGt9Zz0iaTj0STIMbboRKcBGhpOH_LuLBLqsJAlk/edit?usp=sharing)
+2. Understand if those results applied to other NASA HDF5 datasets.
+
+## Discoveries:
+
+1. In [01-check-co-hdf5-cmr.ipynb](01-check-co-hdf5-cmr.ipynb) we discovered that **all NASA HDF5 datasets in Earthdata Cloud** use the HDF5 defaults for file space management - that is:
+    * `strategy = FSM_AGGR`: Use free-space managers, aggregators and virtual file driver for file space allocation.
+    * `page size = 4096`: File space page size in bytes is 4kb. ([source](https://docs.hdfgroup.org/archive/support/HDF5/doc/RM/Tools.html))
+2. This finds the same results as `HDF at the speed of Zarr` for ATL03, such as:
+    * h5py library - best performance is seen using "informed parameters". Repacking makes a much less significant difference.
+    * h5coro - Difference in performance between the original and repacked versions seems insignificant.
+    * xarray - best performance was seen with kerchunk, but a repacked version performs better than the original. Informed parameters may also improve performance with the repacked version.
+3. In testing with other datasets, results varied and more testing may be needed.
+    * For reading with h5py, repacking and informed parameters does appear to make a difference, except in the case of ATL08. But more analysis and robust testing should be done.
+    * For reading with h5coro, repacking does not appear to make a significant difference.
+    * For reading with xarray, repacking and kerchunk both make a significant difference. Kerchunk especially. The exception was that for SNDRSNIML2CCPRETN (Sounder SIPS: Suomi NPP CrIMSS Level 2 CLIMCAPS Normal Spectral Resolution: Atmosphere cloud and surface geophysical state V2) `surf_temp`, the repacked version was slower.
+
+## Additional considerations
+
+* Caching - In [benchmark-small-file-h5repack.ipynb](../benchmark-small-file-h5repack.ipynb) it seems clear the first test run always takes the longest. It is unclear if this is due to S3 caching or caching in the underlying libraries. The test notebooks were run more than once (without restarting the kernel) but more could be done to make these results robust to the impact of caching.
+
+## In conclusion
+
+* The results for ATL03 were consistent with results in slide 13 of [HDF at the speed of Zarr](https://docs.google.com/presentation/d/1iYFvGt9Zz0iaTj0STIMbboRKcBGhpOH_LuLBLqsJAlk/edit?usp=sharing). 
+* Informed parameters for fsspec and h5py appear to improve performance when using h5py and xarray.
+* Repacking does not matter to h5coro.
+* The use of kerchunk (and possibly repacking) significantly improves the performance of xarray with HDF5 datasets in the cloud.
diff --git a/notebooks/replicate-results-research/hdf_cmr_query_results.json b/notebooks/replicate-results-research/hdf_cmr_query_results.json
new file mode 100644
index 0000000..8deb97c
--- /dev/null
+++ b/notebooks/replicate-results-research/hdf_cmr_query_results.json
@@ -0,0 +1 @@
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"OMI-Aura_L3-OMHCHOd_2004m1001_v003-2019m0725t193741.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"3A11.19971201.7.HDF": {"collection": "TRMM_3A11", "version": "7", "direct_link": "s3://gesdisc-cumulus-prod-protected/TRMM_L3/TRMM_3A11.7/1997/3A11.19971201.7.HDF", "filename": "3A11.19971201.7.HDF", "data_center": "GES_DISC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"MOD13C1.A2000049.061.2020041213023.hdf": {"collection": "MOD13C1", "version": "061", "direct_link": "s3://lp-prod-protected/MOD13C1.061/MOD13C1.A2000049.061.2020041213023/MOD13C1.A2000049.061.2020041213023.hdf", "filename": "MOD13C1.A2000049.061.2020041213023.hdf", "data_center": "LPDAAC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"2A53.971127.1.DARW.1.HDF": {"collection": "TRMM_2A53", "version": "7", "direct_link": "s3://gesdisc-cumulus-prod-protected/TRMM_GV_L2/TRMM_2A53.7/1997/331/2A53.971127.1.DARW.1.HDF", "filename": "2A53.971127.1.DARW.1.HDF", "data_center": "GES_DISC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"MOD44B.A2000065.h11v12.061.2022273160936.hdf": {"collection": "MOD44B", "version": "061", "direct_link": "s3://lp-prod-protected/MOD44B.061/MOD44B.A2000065.h11v12.061.2022273160936/MOD44B.A2000065.h11v12.061.2022273160936.hdf", "filename": "MOD44B.A2000065.h11v12.061.2022273160936.hdf", "data_center": "LPDAAC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"VNP46A4.A2012001.h00v00.001.2021124113641.h5": {"collection": "VNP46A4", "version": "1", "direct_link": "s3://prod-lads/VNP46A4/VNP46A4.A2012001.h00v00.001.2021124113641.h5", "filename": "VNP46A4.A2012001.h00v00.001.2021124113641.h5", "data_center": "LAADS", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"20070101120000-UKMO-L4_GHRSST-SSTfnd-OSTIA-GLOB-v02.0-fv02.0.nc": {"collection": "OSTIA-UKMO-L4-GLOB-v2.0", "version": "2.0", "direct_link": "s3://podaac-ops-cumulus-protected/OSTIA-UKMO-L4-GLOB-v2.0/20070101120000-UKMO-L4_GHRSST-SSTfnd-OSTIA-GLOB-v02.0-fv02.0.nc", "filename": "20070101120000-UKMO-L4_GHRSST-SSTfnd-OSTIA-GLOB-v02.0-fv02.0.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"TROPESS_CrIS-SNPP_L2_Summary_HDO_20151201_MUSES_R1p17_RS_F0p8_J0.nc": {"collection": "TRPSYL2HDOCRSRS", "version": "1", "direct_link": "s3://gesdisc-cumulus-prod-protected/TROPESS_Reanalysis_Summary/TRPSYL2HDOCRSRS.1/2015/TROPESS_CrIS-SNPP_L2_Summary_HDO_20151201_MUSES_R1p17_RS_F0p8_J0.nc", "filename": "TROPESS_CrIS-SNPP_L2_Summary_HDO_20151201_MUSES_R1p17_RS_F0p8_J0.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"MLS-Aura_L2GP-CH3CN_v04-20-c01_2004d215.he5": {"collection": "ML2CH3CN", "version": "004", "direct_link": "s3://gesdisc-cumulus-prod-protected/Aura_MLS_Level2/ML2CH3CN.004/2004/MLS-Aura_L2GP-CH3CN_v04-20-c01_2004d215.he5", "filename": "MLS-Aura_L2GP-CH3CN_v04-20-c01_2004d215.he5", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"OCO2GriddedXCO2_20140906_v3_1639402520.nc": {"collection": "OCO2GriddedXCO2", "version": "3", "direct_link": "s3://gesdisc-cumulus-prod-protected/CO2/OCO2GriddedXCO2.3/2014/OCO2GriddedXCO2_20140906_v3_1639402520.nc", "filename": "OCO2GriddedXCO2_20140906_v3_1639402520.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"GRCTellus.JPL.200204_202402.GLO.RL06.1M.MSCNv03CRI.nc": {"collection": "TELLUS_GRAC-GRFO_MASCON_CRI_GRID_RL06.1_V3", "version": "RL06.1Mv03", "direct_link": "s3://podaac-ops-cumulus-protected/TELLUS_GRAC-GRFO_MASCON_CRI_GRID_RL06.1_V3/GRCTellus.JPL.200204_202402.GLO.RL06.1M.MSCNv03CRI.nc", "filename": "GRCTellus.JPL.200204_202402.GLO.RL06.1M.MSCNv03CRI.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"ndvi3g_geo_v1_1_1982_0106.nc4": {"collection": "Global_Veg_Greenness_GIMMS_3G_2187", "version": "1", "direct_link": "s3://ornl-cumulus-prod-protected/global_vegetation/Global_Veg_Greenness_GIMMS_3G/data/ndvi3g_geo_v1_1_1982_0106.nc4", "filename": "ndvi3g_geo_v1_1_1982_0106.nc4", "data_center": "ORNLDAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"20020704000015-JPL-L2P_GHRSST-SSTskin-MODIS_A-N-v02.0-fv01.0.nc": {"collection": "MODIS_A-JPL-L2P-v2019.0", "version": "2019.0", "direct_link": "s3://podaac-ops-cumulus-protected/MODIS_A-JPL-L2P-v2019.0/20020704000015-JPL-L2P_GHRSST-SSTskin-MODIS_A-N-v02.0-fv01.0.nc", "filename": "20020704000015-JPL-L2P_GHRSST-SSTskin-MODIS_A-N-v02.0-fv01.0.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"NLDAS_FORA0125_M.A197901.020.nc": {"collection": "NLDAS_FORA0125_M", "version": "2.0", "direct_link": "s3://gesdisc-cumulus-prod-protected/NLDAS/NLDAS_FORA0125_M.2.0/1979/NLDAS_FORA0125_M.A197901.020.nc", "filename": "NLDAS_FORA0125_M.A197901.020.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"2B.GPM.DPRGMI.CORRA2022.20140308-S220950-E234217.000144.V07A.HDF5": {"collection": "GPM_2BCMB", "version": "07", "direct_link": "s3://gesdisc-cumulus-prod-protected/GPM_L2/GPM_2BCMB.07/2014/067/2B.GPM.DPRGMI.CORRA2022.20140308-S220950-E234217.000144.V07A.HDF5", "filename": "2B.GPM.DPRGMI.CORRA2022.20140308-S220950-E234217.000144.V07A.HDF5", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, "Caught exception 'accessKeyId' while trying to process file from collection TEMPO_NO2_L2, version V01", {"GSSTF.3.1987.07.09.he5": {"collection": "GSSTF", "version": "3", "direct_link": "s3://gesdisc-cumulus-prod-protected/GSSTF/GSSTF.3/1987/GSSTF.3.1987.07.09.he5", "filename": "GSSTF.3.1987.07.09.he5", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"LPRM-TMI_L3_DY_SOILM3_V001-20120406T231009Z_19971207.nc": {"collection": "LPRM_TMI_DY_SOILM3", "version": "001", "direct_link": "s3://gesdisc-cumulus-prod-protected/WAOB/LPRM_TMI_DY_SOILM3.001/1997/12/LPRM-TMI_L3_DY_SOILM3_V001-20120406T231009Z_19971207.nc", "filename": "LPRM-TMI_L3_DY_SOILM3_V001-20120406T231009Z_19971207.nc", "data_center": "GES_DISC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"MERRA2_100.tavgM_2d_lfo_Nx.198001.nc4": {"collection": "M2TMNXLFO", "version": "5.12.4", "direct_link": "s3://gesdisc-cumulus-prod-protected/MERRA2_MONTHLY/M2TMNXLFO.5.12.4/1980/MERRA2_100.tavgM_2d_lfo_Nx.198001.nc4", "filename": "MERRA2_100.tavgM_2d_lfo_Nx.198001.nc4", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"2A55.971127.1.DARW.1.HDF": {"collection": "TRMM_2A55", "version": "7", "direct_link": "s3://gesdisc-cumulus-prod-protected/TRMM_GV_L2/TRMM_2A55.7/1997/331/2A55.971127.1.DARW.1.HDF", "filename": "2A55.971127.1.DARW.1.HDF", "data_center": "GES_DISC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"MOD11C1.A2000058.061.2020058191556.hdf": {"collection": "MOD11C1", "version": "061", "direct_link": "s3://lp-prod-protected/MOD11C1.061/MOD11C1.A2000058.061.2020058191556/MOD11C1.A2000058.061.2020058191556.hdf", "filename": "MOD11C1.A2000058.061.2020058191556.hdf", "data_center": "LPDAAC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"oscar_currents_interim_20200101.nc": {"collection": "OSCAR_L4_OC_INTERIM_V2.0", "version": "2.0", "direct_link": "s3://podaac-ops-cumulus-protected/OSCAR_L4_OC_INTERIM_V2.0/oscar_currents_interim_20200101.nc", "filename": "oscar_currents_interim_20200101.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"maclwp_cloudlwpave_1988_v1.nc4": {"collection": "MACLWP_mean", "version": "1", "direct_link": "s3://gesdisc-cumulus-prod-protected/LWP/MACLWP_mean.1/maclwp_cloudlwpave_1988_v1.nc4", "filename": "maclwp_cloudlwpave_1988_v1.nc4", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, "Caught exception An error occurred (403) when calling the HeadObject operation: Forbidden while trying to process file from collection SWOT_L2_NALT_IGDR_2.0, version 2.0", {"VNP03DNB.A2012019.0000.002.2020318135750.nc": {"collection": "VNP03DNB", "version": "2", "direct_link": "s3://prod-lads/VNP03DNB/VNP03DNB.A2012019.0000.002.2020318135750.nc", "filename": "VNP03DNB.A2012019.0000.002.2020318135750.nc", "data_center": "LAADS", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"FLDAS_NOAH001_G_CA_D.A20001001.001.nc": {"collection": "FLDAS_NOAH001_G_CA_D", "version": "001", "direct_link": "s3://gesdisc-cumulus-prod-protected/FLDAS/FLDAS_NOAH001_G_CA_D.001/2000/10/FLDAS_NOAH001_G_CA_D.A20001001.001.nc", "filename": "FLDAS_NOAH001_G_CA_D.A20001001.001.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"MLS-Aura_L2GP-HCl_v04-20-c01_2004d215.he5": {"collection": "ML2HCL", "version": "004", "direct_link": "s3://gesdisc-cumulus-prod-protected/Aura_MLS_Level2/ML2HCL.004/2004/MLS-Aura_L2GP-HCl_v04-20-c01_2004d215.he5", "filename": "MLS-Aura_L2GP-HCl_v04-20-c01_2004d215.he5", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"GOZ-Merged-MLP_O3_ev1-01_1979.nc4": {"collection": "GozMmlpO3", "version": "1", "direct_link": "s3://gesdisc-cumulus-prod-protected/GOZCARDS/GozMmlpO3.1/GOZ-Merged-MLP_O3_ev1-01_1979.nc4", "filename": "GOZ-Merged-MLP_O3_ev1-01_1979.nc4", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"OMPS-N20_NMSO2-PCA-L2-Step1_v1.0_2018m0116t140223_o00841_2023m1025t135817.nc": {"collection": "OMPS_N20_NMSO2_PCA_L2_Step1", "version": "1", "direct_link": "s3://gesdisc-cumulus-prod-protected/NOAA20_OMPS_Level2/OMPS_N20_NMSO2_PCA_L2_Step1.1/2018/016/OMPS-N20_NMSO2-PCA-L2-Step1_v1.0_2018m0116t140223_o00841_2023m1025t135817.nc", "filename": "OMPS-N20_NMSO2-PCA-L2-Step1_v1.0_2018m0116t140223_o00841_2023m1025t135817.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"MYD16A2GF.A2002001.h27v06.061.2020294150306.hdf": {"collection": "MYD16A2GF", "version": "061", "direct_link": "s3://lp-prod-protected/MYD16A2GF.061/MYD16A2GF.A2002001.h27v06.061.2020294150306/MYD16A2GF.A2002001.h27v06.061.2020294150306.hdf", "filename": "MYD16A2GF.A2002001.h27v06.061.2020294150306.hdf", "data_center": "LPDAAC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"carve_DADS_L1_b23_20120523_20150621190727.nc": {"collection": "CARVE_L1_FlightPath_1425", "version": "1", "direct_link": "s3://ornl-cumulus-prod-protected/carve/campaign/CARVE_L1_FlightPath/data/carve_DADS_L1_b23_20120523_20150621190727.nc", "filename": "carve_DADS_L1_b23_20120523_20150621190727.nc", "data_center": "ORNLDAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"MERRA2_100.tavgM_2d_int_Nx.198001.nc4": {"collection": "M2TMNXINT", "version": "5.12.4", "direct_link": "s3://gesdisc-cumulus-prod-protected/MERRA2_MONTHLY/M2TMNXINT.5.12.4/1980/MERRA2_100.tavgM_2d_int_Nx.198001.nc4", "filename": "MERRA2_100.tavgM_2d_int_Nx.198001.nc4", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"1C.NOAA16.AMSUB.XCAL2017-V.20001004-S121203-E135409.000184.V07A.HDF5": {"collection": "GPM_1CNOAA16AMSUB", "version": "07", "direct_link": "s3://gesdisc-cumulus-prod-protected/GPM_L1C/GPM_1CNOAA16AMSUB.07/2000/278/1C.NOAA16.AMSUB.XCAL2017-V.20001004-S121203-E135409.000184.V07A.HDF5", "filename": "1C.NOAA16.AMSUB.XCAL2017-V.20001004-S121203-E135409.000184.V07A.HDF5", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"GSSTF_F13.3.1995.05.03.he5": {"collection": "GSSTF_F13", "version": "3", "direct_link": "s3://gesdisc-cumulus-prod-protected/GSSTF/GSSTF_F13.3/1995/GSSTF_F13.3.1995.05.03.he5", "filename": "GSSTF_F13.3.1995.05.03.he5", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"GRACEDADM_CLSM025GL_7D.A20030203.030.nc4": {"collection": "GRACEDADM_CLSM025GL_7D", "version": "3.0", "direct_link": "s3://gesdisc-cumulus-prod-protected/GRACEDA/GRACEDADM_CLSM025GL_7D.3.0/2003/GRACEDADM_CLSM025GL_7D.A20030203.030.nc4", "filename": "GRACEDADM_CLSM025GL_7D.A20030203.030.nc4", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"3B31.19971201.7.HDF": {"collection": "TRMM_3B31", "version": "7", "direct_link": "s3://gesdisc-cumulus-prod-protected/TRMM_L3/TRMM_3B31.7/1997/3B31.19971201.7.HDF", "filename": "3B31.19971201.7.HDF", "data_center": "GES_DISC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"MYD17A2HGF.A2002001.h15v01.061.2020167190803.hdf": {"collection": "MYD17A2HGF", "version": "061", "direct_link": "s3://lp-prod-protected/MYD17A2HGF.061/MYD17A2HGF.A2002001.h15v01.061.2020167190803/MYD17A2HGF.A2002001.h15v01.061.2020167190803.hdf", "filename": "MYD17A2HGF.A2002001.h15v01.061.2020167190803.hdf", "data_center": "LPDAAC", "fsm_strategy": "Not found", "page_size": "Not found"}}, "Caught exception An error occurred (403) when calling the HeadObject operation: Forbidden while trying to process file from collection SWOT_L2_LR_SSH_1.1, version 1.1", {"TROPESS_CrIS-SNPP_L2_Summary_PAN_20210201_MUSES_R1p11_FS_F0p6.nc": {"collection": "TRPSYL2PANCRSFS", "version": "1", "direct_link": "s3://gesdisc-cumulus-prod-protected/TROPESS_Summary/TRPSYL2PANCRSFS.1/2021/TROPESS_CrIS-SNPP_L2_Summary_PAN_20210201_MUSES_R1p11_FS_F0p6.nc", "filename": "TROPESS_CrIS-SNPP_L2_Summary_PAN_20210201_MUSES_R1p11_FS_F0p6.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"S5P_RPRO_L2__O3_____20180430T001950_20180430T020120_02818_03_020401_20221003T085027.nc": {"collection": "S5P_L2__O3_TOT_HiR", "version": "2", "direct_link": "s3://gesdisc-cumulus-prod-protected/S5P_TROPOMI_Level2/S5P_L2__O3_TOT_HiR.2/2018/120/S5P_RPRO_L2__O3_____20180430T001950_20180430T020120_02818_03_020401_20221003T085027.nc", "filename": "S5P_RPRO_L2__O3_____20180430T001950_20180430T020120_02818_03_020401_20221003T085027.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"S5P_OFFL_L2__O3__PR_20211116T033235_20211116T051404_21207_02_020301_20211118T005104.nc": {"collection": "S5P_L2__O3__PR_HiR", "version": "2", "direct_link": "s3://gesdisc-cumulus-prod-protected/S5P_TROPOMI_Level2/S5P_L2__O3__PR_HiR.2/2021/320/S5P_OFFL_L2__O3__PR_20211116T033235_20211116T051404_21207_02_020301_20211118T005104.nc", "filename": "S5P_OFFL_L2__O3__PR_20211116T033235_20211116T051404_21207_02_020301_20211118T005104.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"EMIT_L2A_RFL_001_20220810T034103_2222203_001.nc": {"collection": "EMITL2ARFL", "version": "001", "direct_link": "s3://lp-prod-protected/EMITL2ARFL.001/EMIT_L2A_RFL_001_20220810T034103_2222203_001/EMIT_L2A_RFL_001_20220810T034103_2222203_001.nc", "filename": "EMIT_L2A_RFL_001_20220810T034103_2222203_001.nc", "data_center": "LPDAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"MERRA2_100.inst3_3d_chm_Nv.19800101.nc4": {"collection": "M2I3NVCHM", "version": "5.12.4", "direct_link": "s3://gesdisc-cumulus-prod-protected/MERRA2/M2I3NVCHM.5.12.4/1980/01/MERRA2_100.inst3_3d_chm_Nv.19800101.nc4", "filename": "MERRA2_100.inst3_3d_chm_Nv.19800101.nc4", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"MOD11_L2.A2000055.1525.061.2020042181955.hdf": {"collection": "MOD11_L2", "version": "061", "direct_link": "s3://lp-prod-protected/MOD11_L2.061/MOD11_L2.A2000055.1525.061.2020042181955/MOD11_L2.A2000055.1525.061.2020042181955.hdf", "filename": "MOD11_L2.A2000055.1525.061.2020042181955.hdf", "data_center": "LPDAAC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"20120702232149-REMSS-L2P_GHRSST-SSTsubskin-AMSR2-L2B_v8.2_r00675-v02.0-fv01.0.nc": {"collection": "AMSR2-REMSS-L2P-v8.2", "version": "8.2", "direct_link": "s3://podaac-ops-cumulus-protected/AMSR2-REMSS-L2P-v8.2/20120702232149-REMSS-L2P_GHRSST-SSTsubskin-AMSR2-L2B_v8.2_r00675-v02.0-fv01.0.nc", "filename": "20120702232149-REMSS-L2P_GHRSST-SSTsubskin-AMSR2-L2B_v8.2_r00675-v02.0-fv01.0.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"SMAP_L2B_SSS_NRT_07178_A_20160605T081831.h5": {"collection": "SMAP_JPL_L2B_NRT_SSS_CAP_V5", "version": "5.0", "direct_link": "s3://podaac-ops-cumulus-protected/SMAP_JPL_L2B_NRT_SSS_CAP_V5/2016/157/SMAP_L2B_SSS_NRT_07178_A_20160605T081831.h5", "filename": "SMAP_L2B_SSS_NRT_07178_A_20160605T081831.h5", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"1B.TRMM.TMI.Tb2021.19971207-S235717-E012836.000160.V07A.HDF5": {"collection": "GPM_1BTMI", "version": "07", "direct_link": "s3://gesdisc-cumulus-prod-protected/TRMM_L1/GPM_1BTMI.07/1997/341/1B.TRMM.TMI.Tb2021.19971207-S235717-E012836.000160.V07A.HDF5", "filename": "1B.TRMM.TMI.Tb2021.19971207-S235717-E012836.000160.V07A.HDF5", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, "Caught exception An error occurred (403) when calling the HeadObject operation: Forbidden while trying to process file from collection SWOT_L2_NALT_IGDR_1.0, version 1.0", {"MERRA2_100.inst3_3d_gas_Nv.19800101.nc4": {"collection": "M2I3NVGAS", "version": "5.12.4", "direct_link": "s3://gesdisc-cumulus-prod-protected/MERRA2/M2I3NVGAS.5.12.4/1980/01/MERRA2_100.inst3_3d_gas_Nv.19800101.nc4", "filename": "MERRA2_100.inst3_3d_gas_Nv.19800101.nc4", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"MYD09CMG.A2002185.061.2020079160326.hdf": {"collection": "MYD09CMG", "version": "061", "direct_link": "s3://lp-prod-protected/MYD09CMG.061/MYD09CMG.A2002185.061.2020079160326/MYD09CMG.A2002185.061.2020079160326.hdf", "filename": "MYD09CMG.A2002185.061.2020079160326.hdf", "data_center": "LPDAAC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"carve_AtmosISGA_L2_N_b23_20120523_20150713021129.nc": {"collection": "CARVE_L2_AtmosGas_NOAA_1401", "version": "1", "direct_link": "s3://ornl-cumulus-prod-protected/carve/campaign/CARVE_L2_AtmosGas_NOAA/data/carve_AtmosISGA_L2_N_b23_20120523_20150713021129.nc", "filename": "carve_AtmosISGA_L2_N_b23_20120523_20150713021129.nc", "data_center": "ORNLDAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"TROPESS_CrIS-SNPP_L2_Summary_CO_20210201_MUSES_R1p11_FS_F0p6.nc": {"collection": "TRPSYL2COCRSFS", "version": "1", "direct_link": "s3://gesdisc-cumulus-prod-protected/TROPESS_Summary/TRPSYL2COCRSFS.1/2021/TROPESS_CrIS-SNPP_L2_Summary_CO_20210201_MUSES_R1p11_FS_F0p6.nc", "filename": "TROPESS_CrIS-SNPP_L2_Summary_CO_20210201_MUSES_R1p11_FS_F0p6.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"cyg.ddmi.s20180801-000000-e20180801-235959.l2.wind-mss.a31.d32.nc": {"collection": "CYGNSS_L2_V3.1", "version": "3.1", "direct_link": "s3://podaac-ops-cumulus-protected/CYGNSS_L2_V3.1/cyg.ddmi.s20180801-000000-e20180801-235959.l2.wind-mss.a31.d32.nc", "filename": "cyg.ddmi.s20180801-000000-e20180801-235959.l2.wind-mss.a31.d32.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"MLS-Aura_L3ZMRAR-BrO_v05-00-c01_2004d215.nc4": {"collection": "ML3DZMBRO", "version": "005", "direct_link": "s3://gesdisc-cumulus-prod-protected/Aura_MLS_Level3/ML3DZMBRO.005/2004/MLS-Aura_L3ZMRAR-BrO_v05-00-c01_2004d215.nc4", "filename": "MLS-Aura_L3ZMRAR-BrO_v05-00-c01_2004d215.nc4", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"TOVS_DAILY_AM_841228_NF.HDF": {"collection": "TOVSADNF", "version": "01", "direct_link": "s3://gesdisc-cumulus-prod-protected/tovs/TOVSADNF/1984/362/TOVS_DAILY_AM_841228_NF.HDF", "filename": "TOVS_DAILY_AM_841228_NF.HDF", "data_center": "GES_DISC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"NLDAS_NOAH0125_M.A197901.020.nc": {"collection": "NLDAS_NOAH0125_M", "version": "2.0", "direct_link": "s3://gesdisc-cumulus-prod-protected/NLDAS/NLDAS_NOAH0125_M.2.0/1979/NLDAS_NOAH0125_M.A197901.020.nc", "filename": "NLDAS_NOAH0125_M.A197901.020.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"OMI-Aura_L2-OMDOAO3Z_2004m1006t0656-o01209_v003-2011m0920t132820.he5": {"collection": "OMDOAO3Z", "version": "003", "direct_link": "s3://gesdisc-cumulus-prod-protected/Aura_OMI_Level2/OMDOAO3Z.003/2004/280/OMI-Aura_L2-OMDOAO3Z_2004m1006t0656-o01209_v003-2011m0920t132820.he5", "filename": "OMI-Aura_L2-OMDOAO3Z_2004m1006t0656-o01209_v003-2011m0920t132820.he5", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"MLS-Aura_L3DB-CH3Cl_v04-23-c01_2004d215.nc": {"collection": "ML3DBCH3CL", "version": "004", "direct_link": "s3://gesdisc-cumulus-prod-protected/Aura_MLS_Level3/ML3DBCH3CL.004/2004/MLS-Aura_L3DB-CH3Cl_v04-23-c01_2004d215.nc", "filename": "MLS-Aura_L3DB-CH3Cl_v04-23-c01_2004d215.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"SRL_OPRSSHA_2PfS138_0637_20200318_001517_20200318_015316.EUM.nc": {"collection": "ALTIKA_SARAL_L2_OST_XOGDR", "version": "f", "direct_link": "s3://podaac-ops-cumulus-protected/ALTIKA_SARAL_L2_OST_XOGDR/c138/SRL_OPRSSHA_2PfS138_0637_20200318_001517_20200318_015316.EUM.nc", "filename": "SRL_OPRSSHA_2PfS138_0637_20200318_001517_20200318_015316.EUM.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"MLS-Aura_L3DB-HOCl_v05-01-c06_2004d215.nc": {"collection": "ML3DBHOCL", "version": "005", "direct_link": "s3://gesdisc-cumulus-prod-protected/Aura_MLS_Level3/ML3DBHOCL.005/2004/MLS-Aura_L3DB-HOCl_v05-01-c06_2004d215.nc", "filename": "MLS-Aura_L3DB-HOCl_v05-01-c06_2004d215.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"LPRM-AMSR_E_L2_D_SOILM2_V002_20020619002947.nc": {"collection": "LPRM_AMSRE_SOILM2", "version": "002", "direct_link": "s3://gesdisc-cumulus-prod-protected/WAOB/LPRM_AMSRE_SOILM2.002/2002/170/LPRM-AMSR_E_L2_D_SOILM2_V002_20020619002947.nc", "filename": "LPRM-AMSR_E_L2_D_SOILM2_V002_20020619002947.nc", "data_center": "GES_DISC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"MERRA2_100.tavgM_2d_ocn_Nx.198001.nc4": {"collection": "M2TMNXOCN", "version": "5.12.4", "direct_link": "s3://gesdisc-cumulus-prod-protected/MERRA2_MONTHLY/M2TMNXOCN.5.12.4/1980/MERRA2_100.tavgM_2d_ocn_Nx.198001.nc4", "filename": "MERRA2_100.tavgM_2d_ocn_Nx.198001.nc4", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"TROPESS_AIRS-Aqua_L2_Summary_CH4_20020901_MUSES_R1p6_RS_F0p8_J0.nc": {"collection": "TRPSYL2CH4AIRSORS", "version": "1", "direct_link": "s3://gesdisc-cumulus-prod-protected/TROPESS_Reanalysis_Summary/TRPSYL2CH4AIRSORS.1/2002/TROPESS_AIRS-Aqua_L2_Summary_CH4_20020901_MUSES_R1p6_RS_F0p8_J0.nc", "filename": "TROPESS_AIRS-Aqua_L2_Summary_CH4_20020901_MUSES_R1p6_RS_F0p8_J0.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"LPRM-WINDSAT_L2_SOILM2_V001_20030201012753.nc": {"collection": "LPRM_WINDSAT_SOILM2", "version": "001", "direct_link": "s3://gesdisc-cumulus-prod-protected/WAOB/LPRM_WINDSAT_SOILM2.001/2003/032/LPRM-WINDSAT_L2_SOILM2_V001_20030201012753.nc", "filename": "LPRM-WINDSAT_L2_SOILM2_V001_20030201012753.nc", "data_center": "GES_DISC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"AIRS.2002.08.31.L3.RetSup_H001.v6.0.12.0.G14104141407.hdf": {"collection": "AIRH3SPD", "version": "006", "direct_link": "s3://gesdisc-cumulus-prod-protected/Aqua_AIRS_Level3/AIRH3SPD.006/2002/AIRS.2002.08.31.L3.RetSup_H001.v6.0.12.0.G14104141407.hdf", "filename": "AIRS.2002.08.31.L3.RetSup_H001.v6.0.12.0.G14104141407.hdf", "data_center": "GES_DISC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"GLDAS_CLSM10_M.A200001.021.nc4": {"collection": "GLDAS_CLSM10_M", "version": "2.1", "direct_link": "s3://gesdisc-cumulus-prod-protected/GLDAS/GLDAS_CLSM10_M.2.1/2000/GLDAS_CLSM10_M.A200001.021.nc4", "filename": "GLDAS_CLSM10_M.A200001.021.nc4", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"TROPESS_AIRS-Aqua_L2_Standard_TATM_20210201_MUSES_R1p11_FS_F0p1.nc": {"collection": "TRPSDL2TATMAIRSFS", "version": "1", "direct_link": "s3://gesdisc-cumulus-prod-protected/TROPESS_Standard/TRPSDL2TATMAIRSFS.1/2021/TROPESS_AIRS-Aqua_L2_Standard_TATM_20210201_MUSES_R1p11_FS_F0p1.nc", "filename": "TROPESS_AIRS-Aqua_L2_Standard_TATM_20210201_MUSES_R1p11_FS_F0p1.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"HAQES_NA_v1.0_3h_PM25_BC.20221101.nc": {"collection": "HAQES_NA_PM25_BC", "version": "1", "direct_link": "s3://gesdisc-cumulus-prod-protected/HAQAST/HAQES_NA_PM25_BC.1/2022/HAQES_NA_v1.0_3h_PM25_BC.20221101.nc", "filename": "HAQES_NA_v1.0_3h_PM25_BC.20221101.nc", "data_center": "GES_DISC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"FLDAS_NOAH01_CP_GL_M.A201901.001.nc": {"collection": "FLDAS_NOAH01_CP_GL_M", "version": "001", "direct_link": "s3://gesdisc-cumulus-prod-protected/FLDAS/FLDAS_NOAH01_CP_GL_M.001/2019/FLDAS_NOAH01_CP_GL_M.A201901.001.nc", "filename": "FLDAS_NOAH01_CP_GL_M.A201901.001.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"TROPESS_AIRS-Aqua_L2_Standard_NH3_20210201_MUSES_R1p11_FS_F0p1.nc": {"collection": "TRPSDL2NH3AIRSFS", "version": "1", "direct_link": "s3://gesdisc-cumulus-prod-protected/TROPESS_Standard/TRPSDL2NH3AIRSFS.1/2021/TROPESS_AIRS-Aqua_L2_Standard_NH3_20210201_MUSES_R1p11_FS_F0p1.nc", "filename": "TROPESS_AIRS-Aqua_L2_Standard_NH3_20210201_MUSES_R1p11_FS_F0p1.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"MERRA2_100.inst6_3d_ana_Nv.19800101.nc4": {"collection": "M2I6NVANA", "version": "5.12.4", "direct_link": "s3://gesdisc-cumulus-prod-protected/MERRA2/M2I6NVANA.5.12.4/1980/01/MERRA2_100.inst6_3d_ana_Nv.19800101.nc4", "filename": "MERRA2_100.inst6_3d_ana_Nv.19800101.nc4", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"GEDI01_B_2019108002012_O01959_01_T03909_02_005_01_V002.h5": {"collection": "GEDI01_B", "version": "002", "direct_link": "s3://lp-prod-protected/GEDI01_B.002/GEDI01_B_2019108002012_O01959_01_T03909_02_005_01_V002/GEDI01_B_2019108002012_O01959_01_T03909_02_005_01_V002.h5", "filename": "GEDI01_B_2019108002012_O01959_01_T03909_02_005_01_V002.h5", "data_center": "LPDAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"MLS-Aura_L3ZMRAR-HO2_v05-00-c01_2004d215.nc4": {"collection": "ML3DZMHO2", "version": "005", "direct_link": "s3://gesdisc-cumulus-prod-protected/Aura_MLS_Level3/ML3DZMHO2.005/2004/MLS-Aura_L3ZMRAR-HO2_v05-00-c01_2004d215.nc4", "filename": "MLS-Aura_L3ZMRAR-HO2_v05-00-c01_2004d215.nc4", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"S5P_OFFL_L2__CH4____20190806T022006_20190806T040136_09388_01_010302_20190812T040851.nc": {"collection": "S5P_L2__CH4____HiR", "version": "1", "direct_link": "s3://gesdisc-cumulus-prod-protected/S5P_TROPOMI_Level2/S5P_L2__CH4____HiR.1/2019/218/S5P_OFFL_L2__CH4____20190806T022006_20190806T040136_09388_01_010302_20190812T040851.nc", "filename": "S5P_OFFL_L2__CH4____20190806T022006_20190806T040136_09388_01_010302_20190812T040851.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"MLS-Aura_L2GP-O3_v05-01-c01_2004d215.he5": {"collection": "ML2O3", "version": "005", "direct_link": "s3://gesdisc-cumulus-prod-protected/Aura_MLS_Level2/ML2O3.005/2004/MLS-Aura_L2GP-O3_v05-01-c01_2004d215.he5", "filename": "MLS-Aura_L2GP-O3_v05-01-c01_2004d215.he5", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, "Caught exception An error occurred (403) when calling the HeadObject operation: Forbidden while trying to process file from collection SWOT_L2_LR_SSH_1.0, version 1.0", {"MERRA2_100.tavgM_2d_chm_Nx.198001.nc4": {"collection": "M2TMNXCHM", "version": "5.12.4", "direct_link": "s3://gesdisc-cumulus-prod-protected/MERRA2_MONTHLY/M2TMNXCHM.5.12.4/1980/MERRA2_100.tavgM_2d_chm_Nx.198001.nc4", "filename": "MERRA2_100.tavgM_2d_chm_Nx.198001.nc4", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, "Caught exception An error occurred (403) when calling the HeadObject operation: Forbidden while trying to process file from collection SWOT_L2_NALT_OGDR_2.0, version 2.0", {"MERRA2_100.instM_2d_gas_Nx.198001.nc4": {"collection": "M2IMNXGAS", "version": "5.12.4", "direct_link": "s3://gesdisc-cumulus-prod-protected/MERRA2_MONTHLY/M2IMNXGAS.5.12.4/1980/MERRA2_100.instM_2d_gas_Nx.198001.nc4", "filename": "MERRA2_100.instM_2d_gas_Nx.198001.nc4", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"MLS-Aura_L2GP-SO2_v05-01-c01_2004d215.he5": {"collection": "ML2SO2", "version": "005", "direct_link": "s3://gesdisc-cumulus-prod-protected/Aura_MLS_Level2/ML2SO2.005/2004/MLS-Aura_L2GP-SO2_v05-01-c01_2004d215.he5", "filename": "MLS-Aura_L2GP-SO2_v05-01-c01_2004d215.he5", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"20000224000006-JPL-L2P_GHRSST-SSTskin-MODIS_T-N-v02.0-fv01.0.nc": {"collection": "MODIS_T-JPL-L2P-v2019.0", "version": "2019.0", "direct_link": "s3://podaac-ops-cumulus-protected/MODIS_T-JPL-L2P-v2019.0/20000224000006-JPL-L2P_GHRSST-SSTskin-MODIS_T-N-v02.0-fv01.0.nc", "filename": "20000224000006-JPL-L2P_GHRSST-SSTskin-MODIS_T-N-v02.0-fv01.0.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"SurfaceNO2_0.0083deg_1990.nc": {"collection": "SFC_NITROGEN_DIOXIDE_CONC", "version": "1", "direct_link": "s3://gesdisc-cumulus-prod-protected/HAQAST/SFC_NITROGEN_DIOXIDE_CONC.1/SurfaceNO2_0.0083deg_1990.nc", "filename": "SurfaceNO2_0.0083deg_1990.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"1Base.TRMM.TMI.TaTb2021.19971207-S235717-E012836.000160.V07A.HDF5": {"collection": "GPM_BASETRMMTMI", "version": "07", "direct_link": "s3://gesdisc-cumulus-prod-protected/TRMM_L1/GPM_BASETRMMTMI.07/1997/341/1Base.TRMM.TMI.TaTb2021.19971207-S235717-E012836.000160.V07A.HDF5", "filename": "1Base.TRMM.TMI.TaTb2021.19971207-S235717-E012836.000160.V07A.HDF5", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"MOD21.A2000055.1525.061.2020037140102.hdf": {"collection": "MOD21", "version": "061", "direct_link": "s3://lp-prod-protected/MOD21.061/MOD21.A2000055.1525.061.2020037140102/MOD21.A2000055.1525.061.2020037140102.hdf", "filename": "MOD21.A2000055.1525.061.2020037140102.hdf", "data_center": "LPDAAC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"MYD13C2.A2002182.061.2020080105511.hdf": {"collection": "MYD13C2", "version": "061", "direct_link": "s3://lp-prod-protected/MYD13C2.061/MYD13C2.A2002182.061.2020080105511/MYD13C2.A2002182.061.2020080105511.hdf", "filename": "MYD13C2.A2002182.061.2020080105511.hdf", "data_center": "LPDAAC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"MLS-Aura_L2GP-CH3OH_v05-01-c01_2004d215.he5": {"collection": "ML2CH3OH", "version": "005", "direct_link": "s3://gesdisc-cumulus-prod-protected/Aura_MLS_Level2/ML2CH3OH.005/2004/MLS-Aura_L2GP-CH3OH_v05-01-c01_2004d215.he5", "filename": "MLS-Aura_L2GP-CH3OH_v05-01-c01_2004d215.he5", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"MLS-Aura_L2GP-CO_v05-01-c01_2004d215.he5": {"collection": "ML2CO", "version": "005", "direct_link": "s3://gesdisc-cumulus-prod-protected/Aura_MLS_Level2/ML2CO.005/2004/MLS-Aura_L2GP-CO_v05-01-c01_2004d215.he5", "filename": "MLS-Aura_L2GP-CO_v05-01-c01_2004d215.he5", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"ATL13_20181014031222_02370101_006_01.h5": {"collection": "ATL13", "version": "006", "direct_link": "s3://nsidc-cumulus-prod-protected/ATLAS/ATL13/006/2018/10/ATL13_20181014031222_02370101_006_01.h5", "filename": "ATL13_20181014031222_02370101_006_01.h5", "data_center": "NSIDC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"MERRA2_100.statM_2d_slv_Nx.198001.nc4": {"collection": "M2SMNXSLV", "version": "5.12.4", "direct_link": "s3://gesdisc-cumulus-prod-protected/MERRA2_MONTHLY/M2SMNXSLV.5.12.4/1980/MERRA2_100.statM_2d_slv_Nx.198001.nc4", "filename": "MERRA2_100.statM_2d_slv_Nx.198001.nc4", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"MLS-Aura_L2GP-DGG_v04-20-c01_2004d215.he5": {"collection": "ML2DGG", "version": "004", "direct_link": "s3://gesdisc-cumulus-prod-protected/Aura_MLS_Level2/ML2DGG.004/2004/MLS-Aura_L2GP-DGG_v04-20-c01_2004d215.he5", "filename": "MLS-Aura_L2GP-DGG_v04-20-c01_2004d215.he5", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"TOVS_5DAYS_AM_B861127.E861201_NG.HDF.Z": {"collection": "TOVSA5NG", "version": "01", "direct_link": "s3://gesdisc-cumulus-prod-protected/tovs/TOVSA5NG/1986/330/TOVS_5DAYS_AM_B861127.E861201_NG.HDF.Z", "filename": "TOVS_5DAYS_AM_B861127.E861201_NG.HDF.Z", "data_center": "GES_DISC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"GOZ-Merged-MLP_HCl_ev1-01_1991.nc4": {"collection": "GozMmlpHCl", "version": "1", "direct_link": "s3://gesdisc-cumulus-prod-protected/GOZCARDS/GozMmlpHCl.1/GOZ-Merged-MLP_HCl_ev1-01_1991.nc4", "filename": "GOZ-Merged-MLP_HCl_ev1-01_1991.nc4", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"S5P_RPRO_L2__NO2____20180430T001851_20180430T020219_02818_01_010202_20190201T131951.nc": {"collection": "S5P_L2__NO2___", "version": "1", "direct_link": "s3://gesdisc-cumulus-prod-protected/S5P_TROPOMI_Level2/S5P_L2__NO2___.1/2018/120/S5P_RPRO_L2__NO2____20180430T001851_20180430T020219_02818_01_010202_20190201T131951.nc", "filename": "S5P_RPRO_L2__NO2____20180430T001851_20180430T020219_02818_01_010202_20190201T131951.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"AIRS.2002.08.30.225.L2.RetSup.v7.0.1.0.G20193143744.hdf": {"collection": "AIRX2SUP", "version": "7.0", "direct_link": "s3://gesdisc-cumulus-prod-protected/Aqua_AIRS_Level2/AIRX2SUP.7.0/2002/242/AIRS.2002.08.30.225.L2.RetSup.v7.0.1.0.G20193143744.hdf", "filename": "AIRS.2002.08.30.225.L2.RetSup.v7.0.1.0.G20193143744.hdf", "data_center": "GES_DISC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"GEOLST4KHR_200004010015_002_20210607132111.h5": {"collection": "GEOLST4KHR", "version": "002", "direct_link": "s3://lp-prod-protected/GEOLST4KHR.002/GEOLST4KHR_200004010015_002_20210607132111/GEOLST4KHR_200004010015_002_20210607132111.h5", "filename": "GEOLST4KHR_200004010015_002_20210607132111.h5", "data_center": "LPDAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"NLDAS_FORB0125_M.A197901.020.nc": {"collection": "NLDAS_FORB0125_M", "version": "2.0", "direct_link": "s3://gesdisc-cumulus-prod-protected/NLDAS/NLDAS_FORB0125_M.2.0/1979/NLDAS_FORB0125_M.A197901.020.nc", "filename": "NLDAS_FORB0125_M.A197901.020.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"3B42RT.2000030100.7R2.nc4": {"collection": "TRMM_3B42RT", "version": "7", "direct_link": "s3://gesdisc-cumulus-prod-protected/TRMM_RT/TRMM_3B42RT.7/2000/060/3B42RT.2000030100.7R2.nc4", "filename": "3B42RT.2000030100.7R2.nc4", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"MERRA2_100.instM_2d_asm_Nx.198001.nc4": {"collection": "M2IMNXASM", "version": "5.12.4", "direct_link": "s3://gesdisc-cumulus-prod-protected/MERRA2_MONTHLY/M2IMNXASM.5.12.4/1980/MERRA2_100.instM_2d_asm_Nx.198001.nc4", "filename": "MERRA2_100.instM_2d_asm_Nx.198001.nc4", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"MCD12Q2.A2001001.h16v09.061.2022070170517.hdf": {"collection": "MCD12Q2", "version": "061", "direct_link": "s3://lp-prod-protected/MCD12Q2.061/MCD12Q2.A2001001.h16v09.061.2022070170517/MCD12Q2.A2001001.h16v09.061.2022070170517.hdf", "filename": "MCD12Q2.A2001001.h16v09.061.2022070170517.hdf", "data_center": "LPDAAC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"MOD11B3.A2000032.h20v01.061.2020048181324.hdf": {"collection": "MOD11B3", "version": "061", "direct_link": "s3://lp-prod-protected/MOD11B3.061/MOD11B3.A2000032.h20v01.061.2020048181324/MOD11B3.A2000032.h20v01.061.2020048181324.hdf", "filename": "MOD11B3.A2000032.h20v01.061.2020048181324.hdf", "data_center": "LPDAAC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"GPCPMON_L3_198301_V3.2.nc4": {"collection": "GPCPMON", "version": "3.2", "direct_link": "s3://gesdisc-cumulus-prod-protected/GPCP/GPCPMON.3.2/1983/GPCPMON_L3_198301_V3.2.nc4", "filename": "GPCPMON_L3_198301_V3.2.nc4", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"S5P_OFFL_L2__O3_TCL_20180430T105026_20180506T131804_02824_01_010105_20181212T112006.nc": {"collection": "S5P_L2__O3_TCL", "version": "1", "direct_link": "s3://gesdisc-cumulus-prod-protected/S5P_TROPOMI_Level2/S5P_L2__O3_TCL.1/2018/S5P_OFFL_L2__O3_TCL_20180430T105026_20180506T131804_02824_01_010105_20181212T112006.nc", "filename": "S5P_OFFL_L2__O3_TCL_20180430T105026_20180506T131804_02824_01_010105_20181212T112006.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"20230111111900-REMSS-L2P_GHRSST-SSTsubskin-AMSR2-L2B_rt_r56661-v02.0-fv01.0.nc": {"collection": "AMSR2-REMSS-L2P_RT-v8.2", "version": "8.2", "direct_link": "s3://podaac-ops-cumulus-protected/AMSR2-REMSS-L2P_RT-v8.2/20230111111900-REMSS-L2P_GHRSST-SSTsubskin-AMSR2-L2B_rt_r56661-v02.0-fv01.0.nc", "filename": "20230111111900-REMSS-L2P_GHRSST-SSTsubskin-AMSR2-L2B_rt_r56661-v02.0-fv01.0.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"TROPESS_CrIS-SNPP_L2_Standard_CO_20151102_MUSES_R1p5_SC_TS2_F0p1.nc": {"collection": "TRPSDL2COCRSTS2", "version": "1", "direct_link": "s3://gesdisc-cumulus-prod-protected/TROPESS_Special/TRPSDL2COCRSTS2.1/2015/TROPESS_CrIS-SNPP_L2_Standard_CO_20151102_MUSES_R1p5_SC_TS2_F0p1.nc", "filename": "TROPESS_CrIS-SNPP_L2_Standard_CO_20151102_MUSES_R1p5_SC_TS2_F0p1.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"AMSRE.L2.RainRateAE_RainStrip200kmAlongCloudSat.2006.06.01.000936Z.v002.hdf": {"collection": "AMSRERR_CPR", "version": "002", "direct_link": "s3://gesdisc-cumulus-prod-protected/AMSRE/AMSRERR_CPR.002/2006/152/AMSRE.L2.RainRateAE_RainStrip200kmAlongCloudSat.2006.06.01.000936Z.v002.hdf", "filename": "AMSRE.L2.RainRateAE_RainStrip200kmAlongCloudSat.2006.06.01.000936Z.v002.hdf", "data_center": "GES_DISC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"oscar_currents_nrt_20210101.nc": {"collection": "OSCAR_L4_OC_NRT_V2.0", "version": "2.0", "direct_link": "s3://podaac-ops-cumulus-protected/OSCAR_L4_OC_NRT_V2.0/oscar_currents_nrt_20210101.nc", "filename": "oscar_currents_nrt_20210101.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"TROPESS_CrIS-SNPP_L2_Standard_NH3_20210201_MUSES_R1p11_FS_F0p1.nc": {"collection": "TRPSDL2NH3CRSFS", "version": "1", "direct_link": "s3://gesdisc-cumulus-prod-protected/TROPESS_Standard/TRPSDL2NH3CRSFS.1/2021/TROPESS_CrIS-SNPP_L2_Standard_NH3_20210201_MUSES_R1p11_FS_F0p1.nc", "filename": "TROPESS_CrIS-SNPP_L2_Standard_NH3_20210201_MUSES_R1p11_FS_F0p1.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"GLDAS_VIC10_3H.A20000101.0300.021.nc4": {"collection": "GLDAS_VIC10_3H", "version": "2.1", "direct_link": "s3://gesdisc-cumulus-prod-protected/GLDAS/GLDAS_VIC10_3H.2.1/2000/001/GLDAS_VIC10_3H.A20000101.0300.021.nc4", "filename": "GLDAS_VIC10_3H.A20000101.0300.021.nc4", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"OMI-Aura_L2G-OMAEROG_2004m1001_v003-2011m1006t204118.he5": {"collection": "OMAEROG", "version": "003", "direct_link": "s3://gesdisc-cumulus-prod-protected/Aura_OMI_Level2G/OMAEROG.003/2004/OMI-Aura_L2G-OMAEROG_2004m1001_v003-2011m1006t204118.he5", "filename": "OMI-Aura_L2G-OMAEROG_2004m1001_v003-2011m1006t204118.he5", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"MLS-Aura_L2GP-CO_v04-20-c01_2004d215.he5": {"collection": "ML2CO", "version": "004", "direct_link": "s3://gesdisc-cumulus-prod-protected/Aura_MLS_Level2/ML2CO.004/2004/MLS-Aura_L2GP-CO_v04-20-c01_2004d215.he5", "filename": "MLS-Aura_L2GP-CO_v04-20-c01_2004d215.he5", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"NCALDAS_NOAH0125_D.A19790102.002.nc4": {"collection": "NCALDAS_NOAH0125_D", "version": "2.0", "direct_link": "s3://gesdisc-cumulus-prod-protected/NCALDAS/NCALDAS_NOAH0125_D.2.0/1979/01/NCALDAS_NOAH0125_D.A19790102.002.nc4", "filename": "NCALDAS_NOAH0125_D.A19790102.002.nc4", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"TROPESS_AIRS-Aqua_OMI-Aura_L2_Summary_O3_20210201_MUSES_R1p11_FS_F0p6.nc": {"collection": "TRPSYL2O3AIRSOMIFS", "version": "1", "direct_link": "s3://gesdisc-cumulus-prod-protected/TROPESS_Summary/TRPSYL2O3AIRSOMIFS.1/2021/TROPESS_AIRS-Aqua_OMI-Aura_L2_Summary_O3_20210201_MUSES_R1p11_FS_F0p6.nc", "filename": "TROPESS_AIRS-Aqua_OMI-Aura_L2_Summary_O3_20210201_MUSES_R1p11_FS_F0p6.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"MERRA2_100.tavgU_2d_lnd_Nx.198001.nc4": {"collection": "M2TUNXLND", "version": "5.12.4", "direct_link": "s3://gesdisc-cumulus-prod-protected/MERRA2_DIURNAL/M2TUNXLND.5.12.4/1980/MERRA2_100.tavgU_2d_lnd_Nx.198001.nc4", "filename": "MERRA2_100.tavgU_2d_lnd_Nx.198001.nc4", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"CSH.971201.6.HDF": {"collection": "TRMM_CSH", "version": "6", "direct_link": "s3://gesdisc-cumulus-prod-protected/TRMM_L3/TRMM_CSH.6/1997/335/CSH.971201.6.HDF", "filename": "CSH.971201.6.HDF", "data_center": "GES_DISC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"MERRA2_100.tavg1_2d_lfo_Nx.19800101.nc4": {"collection": "M2T1NXLFO", "version": "5.12.4", "direct_link": "s3://gesdisc-cumulus-prod-protected/MERRA2/M2T1NXLFO.5.12.4/1980/01/MERRA2_100.tavg1_2d_lfo_Nx.19800101.nc4", "filename": "MERRA2_100.tavg1_2d_lfo_Nx.19800101.nc4", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"MCD19A3D.A2000055.h23v10.061.2022153214103.hdf": {"collection": "MCD19A3D", "version": "061", "direct_link": "s3://lp-prod-protected/MCD19A3D.061/MCD19A3D.A2000055.h23v10.061.2022153214103/MCD19A3D.A2000055.h23v10.061.2022153214103.hdf", "filename": "MCD19A3D.A2000055.h23v10.061.2022153214103.hdf", "data_center": "LPDAAC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"TOVSB_DAILY_AM_910630_ND.HDF.Z": {"collection": "TOVSBDND", "version": "01", "direct_link": "s3://gesdisc-cumulus-prod-protected/tovs/TOVSBDND/1991/180/TOVSB_DAILY_AM_910630_ND.HDF.Z", "filename": "TOVSB_DAILY_AM_910630_ND.HDF.Z", "data_center": "GES_DISC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"ascat_20191022_095700_metopc_04964_eps_o_250_3203_ovw.l2.nc": {"collection": "ASCATC-L2-25km", "version": "Operational/Near-Real-Time", "direct_link": "s3://podaac-ops-cumulus-protected/ASCATC-L2-25km/ascat_20191022_095700_metopc_04964_eps_o_250_3203_ovw.l2.nc", "filename": "ascat_20191022_095700_metopc_04964_eps_o_250_3203_ovw.l2.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"TOVS_DAILY_AM_910705_ND.HDF.Z": {"collection": "TOVSADND", "version": "01", "direct_link": "s3://gesdisc-cumulus-prod-protected/tovs/TOVSADND/1991/185/TOVS_DAILY_AM_910705_ND.HDF.Z", "filename": "TOVS_DAILY_AM_910705_ND.HDF.Z", "data_center": "GES_DISC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"GEOSCarb_CASAGFED3v3_Flux.Monthly.x720_y360.2003.nc": {"collection": "GEOS_CASAGFED_M_FLUX", "version": "3", "direct_link": "s3://gesdisc-cumulus-prod-protected/CMS/GEOS_CASAGFED_M_FLUX.3/GEOSCarb_CASAGFED3v3_Flux.Monthly.x720_y360.2003.nc", "filename": "GEOSCarb_CASAGFED3v3_Flux.Monthly.x720_y360.2003.nc", "data_center": "GES_DISC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"S5P_OFFL_L2__O3_____20190806T022006_20190806T040136_09388_01_010107_20190812T040851.nc": {"collection": "S5P_L2__O3_TOT_HiR", "version": "1", "direct_link": "s3://gesdisc-cumulus-prod-protected/S5P_TROPOMI_Level2/S5P_L2__O3_TOT_HiR.1/2019/218/S5P_OFFL_L2__O3_____20190806T022006_20190806T040136_09388_01_010107_20190812T040851.nc", "filename": "S5P_OFFL_L2__O3_____20190806T022006_20190806T040136_09388_01_010107_20190812T040851.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"GRD-3_2002094-2002120_GRAC_JPLEM_BA01_0600_LND_v04.nc": {"collection": "TELLUS_GRAC_L3_JPL_RL06_LND_v04", "version": "RL06v04", "direct_link": "s3://podaac-ops-cumulus-protected/TELLUS_GRAC_L3_JPL_RL06_LND_v04/GRD-3_2002094-2002120_GRAC_JPLEM_BA01_0600_LND_v04.nc", "filename": "GRD-3_2002094-2002120_GRAC_JPLEM_BA01_0600_LND_v04.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"GLDAS_VIC10_3H.A19480101.0300.020.nc4": {"collection": "GLDAS_VIC10_3H", "version": "2.0", "direct_link": "s3://gesdisc-cumulus-prod-protected/GLDAS/GLDAS_VIC10_3H.2.0/1948/001/GLDAS_VIC10_3H.A19480101.0300.020.nc4", "filename": "GLDAS_VIC10_3H.A19480101.0300.020.nc4", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, "Caught exception An error occurred (403) when calling the HeadObject operation: Forbidden while trying to process file from collection SWOT_L2_NALT_GDR_2.0, version 2.0", {"1B.TRMM.PR.V9-20210630.19971207-S235717-E012836.000160.V07A.HDF5": {"collection": "GPM_1BPR", "version": "07", "direct_link": "s3://gesdisc-cumulus-prod-protected/TRMM_L1/GPM_1BPR.07/1997/341/1B.TRMM.PR.V9-20210630.19971207-S235717-E012836.000160.V07A.HDF5", "filename": "1B.TRMM.PR.V9-20210630.19971207-S235717-E012836.000160.V07A.HDF5", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"MYD11B3.A2002182.h24v12.061.2020161141212.hdf": {"collection": "MYD11B3", "version": "061", "direct_link": "s3://lp-prod-protected/MYD11B3.061/MYD11B3.A2002182.h24v12.061.2020161141212/MYD11B3.A2002182.h24v12.061.2020161141212.hdf", "filename": "MYD11B3.A2002182.h24v12.061.2020161141212.hdf", "data_center": "LPDAAC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"GLDAS_NOAH10_M.A194801.020.nc4": {"collection": "GLDAS_NOAH10_M", "version": "2.0", "direct_link": "s3://gesdisc-cumulus-prod-protected/GLDAS/GLDAS_NOAH10_M.2.0/1948/GLDAS_NOAH10_M.A194801.020.nc4", "filename": "GLDAS_NOAH10_M.A194801.020.nc4", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"Scarb-car_c131_19950817_R2_1688_Level1C_20171201.nc": {"collection": "CAR_SCARB_L1C", "version": "1", "direct_link": "s3://gesdisc-cumulus-prod-protected/CAR/CAR_SCARB_L1C.1/Scarb-car_c131_19950817_R2_1688_Level1C_20171201.nc", "filename": "Scarb-car_c131_19950817_R2_1688_Level1C_20171201.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"BLWV_M_V02.00_2002m07.nc4": {"collection": "AMMBLWV", "version": "2", "direct_link": "s3://gesdisc-cumulus-prod-protected/BLWV/AMMBLWV.2/2002/BLWV_M_V02.00_2002m07.nc4", "filename": "BLWV_M_V02.00_2002m07.nc4", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"MYD11C1.A2002185.061.2020149012902.hdf": {"collection": "MYD11C1", "version": "061", "direct_link": "s3://lp-prod-protected/MYD11C1.061/MYD11C1.A2002185.061.2020149012902/MYD11C1.A2002185.061.2020149012902.hdf", "filename": "MYD11C1.A2002185.061.2020149012902.hdf", "data_center": "LPDAAC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"cyg.ddmi.s20170318-000000-e20170318-235959.l2.wind-mss.a21.d21.nc": {"collection": "CYGNSS_L2_V2.1", "version": "2.1", "direct_link": "s3://podaac-ops-cumulus-protected/CYGNSS_L2_V2.1/2017/077/cyg.ddmi.s20170318-000000-e20170318-235959.l2.wind-mss.a21.d21.nc", "filename": "cyg.ddmi.s20170318-000000-e20170318-235959.l2.wind-mss.a21.d21.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"MLS-Aura_L2GP-HCl_v05-01-c01_2004d215.he5": {"collection": "ML2HCL", "version": "005", "direct_link": "s3://gesdisc-cumulus-prod-protected/Aura_MLS_Level2/ML2HCL.005/2004/MLS-Aura_L2GP-HCl_v05-01-c01_2004d215.he5", "filename": "MLS-Aura_L2GP-HCl_v05-01-c01_2004d215.he5", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"S5P_OFFL_L2__AER_AI_20180628T102407_20180628T120537_03661_01_010002_20180704T095226.nc": {"collection": "S5P_L2__AER_AI", "version": "1", "direct_link": "s3://gesdisc-cumulus-prod-protected/S5P_TROPOMI_Level2/S5P_L2__AER_AI.1/2018/179/S5P_OFFL_L2__AER_AI_20180628T102407_20180628T120537_03661_01_010002_20180704T095226.nc", "filename": "S5P_OFFL_L2__AER_AI_20180628T102407_20180628T120537_03661_01_010002_20180704T095226.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"F14_SSMI_FCDR2021_L2_V1_19970507-S172506-E190704.000467.V01E.nc": {"collection": "PRECIP_SSMI_F14", "version": "1", "direct_link": "s3://gesdisc-cumulus-prod-protected/Precipitation/PRECIP_SSMI_F14.1/1997/127/F14_SSMI_FCDR2021_L2_V1_19970507-S172506-E190704.000467.V01E.nc", "filename": "F14_SSMI_FCDR2021_L2_V1_19970507-S172506-E190704.000467.V01E.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"RSS_SMAP_SSS_L2C_r00870_20150401T004312_2015091_FNL_V05.0.nc": {"collection": "SMAP_RSS_L2_SSS_V5", "version": "5.0", "direct_link": "s3://podaac-ops-cumulus-protected/SMAP_RSS_L2_SSS_V5/RSS_SMAP_SSS_L2C_r00870_20150401T004312_2015091_FNL_V05.0.nc", "filename": "RSS_SMAP_SSS_L2C_r00870_20150401T004312_2015091_FNL_V05.0.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"20020901090000-JPL-L4_GHRSST-SSTfnd-MUR25-GLOB-v02.0-fv04.2.nc": {"collection": "MUR25-JPL-L4-GLOB-v04.2", "version": "4.2", "direct_link": "s3://podaac-ops-cumulus-protected/MUR25-JPL-L4-GLOB-v04.2/20020901090000-JPL-L4_GHRSST-SSTfnd-MUR25-GLOB-v02.0-fv04.2.nc", "filename": "20020901090000-JPL-L4_GHRSST-SSTfnd-MUR25-GLOB-v02.0-fv04.2.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"AIRS.2002.08.30.240.L1B.VIS_QaSub.v5.0.0.0.G07068155735.hdf": {"collection": "AIRVBQAP", "version": "005", "direct_link": "s3://gesdisc-cumulus-prod-protected/Aqua_AIRS_Level1/AIRVBQAP.005/2002/242/AIRS.2002.08.30.240.L1B.VIS_QaSub.v5.0.0.0.G07068155735.hdf", "filename": "AIRS.2002.08.30.240.L1B.VIS_QaSub.v5.0.0.0.G07068155735.hdf", "data_center": "GES_DISC", "fsm_strategy": "Not found", "page_size": "Not found"}}, "Caught exception An error occurred (403) when calling the HeadObject operation: Forbidden while trying to process file from collection SWOT_L2_HR_Raster_2.0, version 2.0", {"CMS_Flux_NBEPrior_2010_v2.nc": {"collection": "CMSFluxNBEPrior", "version": "2", "direct_link": "s3://gesdisc-cumulus-prod-protected/CMS/CMSFluxNBEPrior.2/CMS_Flux_NBEPrior_2010_v2.nc", "filename": "CMS_Flux_NBEPrior_2010_v2.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"1C.F17.SSMIS.XCAL2021-V.20080319-S101453-E115649.007076.V07A.HDF5": {"collection": "GPM_1CF17SSMIS", "version": "07", "direct_link": "s3://gesdisc-cumulus-prod-protected/GPM_L1C/GPM_1CF17SSMIS.07/2008/079/1C.F17.SSMIS.XCAL2021-V.20080319-S101453-E115649.007076.V07A.HDF5", "filename": "1C.F17.SSMIS.XCAL2021-V.20080319-S101453-E115649.007076.V07A.HDF5", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"MERRA2_100.instU_3d_asm_Np.198001.nc4": {"collection": "M2IUNPASM", "version": "5.12.4", "direct_link": "s3://gesdisc-cumulus-prod-protected/MERRA2_DIURNAL/M2IUNPASM.5.12.4/1980/MERRA2_100.instU_3d_asm_Np.198001.nc4", "filename": "MERRA2_100.instU_3d_asm_Np.198001.nc4", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"MLS-Aura_L2GP-IWC_v05-01-c01_2004d215.he5": {"collection": "ML2IWC", "version": "005", "direct_link": "s3://gesdisc-cumulus-prod-protected/Aura_MLS_Level2/ML2IWC.005/2004/MLS-Aura_L2GP-IWC_v05-01-c01_2004d215.he5", "filename": "MLS-Aura_L2GP-IWC_v05-01-c01_2004d215.he5", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"20160119080703-OSISAF-L2P_GHRSST-SSTsubskin-AVHRR_SST_METOP_B-sstmgr_metop01_20160119_080703-v02.0-fv01.0.nc": {"collection": "AVHRR_SST_METOP_B-OSISAF-L2P-v1.0", "version": "1", "direct_link": "s3://podaac-ops-cumulus-protected/AVHRR_SST_METOP_B-OSISAF-L2P-v1.0/20160119080703-OSISAF-L2P_GHRSST-SSTsubskin-AVHRR_SST_METOP_B-sstmgr_metop01_20160119_080703-v02.0-fv01.0.nc", "filename": "20160119080703-OSISAF-L2P_GHRSST-SSTsubskin-AVHRR_SST_METOP_B-sstmgr_metop01_20160119_080703-v02.0-fv01.0.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"MLS-Aura_L2GP-ClO_v05-01-c01_2004d215.he5": {"collection": "ML2CLO", "version": "005", "direct_link": "s3://gesdisc-cumulus-prod-protected/Aura_MLS_Level2/ML2CLO.005/2004/MLS-Aura_L2GP-ClO_v05-01-c01_2004d215.he5", "filename": "MLS-Aura_L2GP-ClO_v05-01-c01_2004d215.he5", "data_center": "GES_DISC", "fsm_strategy": 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{"MYD11C3.A2002182.061.2020153184206.hdf": {"collection": "MYD11C3", "version": "061", "direct_link": "s3://lp-prod-protected/MYD11C3.061/MYD11C3.A2002182.061.2020153184206/MYD11C3.A2002182.061.2020153184206.hdf", "filename": "MYD11C3.A2002182.061.2020153184206.hdf", "data_center": "LPDAAC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"GSSTF_F10.3.1991.01.07.he5": {"collection": "GSSTF_F10", "version": "3", "direct_link": "s3://gesdisc-cumulus-prod-protected/GSSTF/GSSTF_F10.3/1991/GSSTF_F10.3.1991.01.07.he5", "filename": "GSSTF_F10.3.1991.01.07.he5", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, "Caught exception An error occurred (403) when calling the HeadObject operation: Forbidden while trying to process file from collection SWOT_L2_HR_Raster_1.1, version 1.1", {"cyg03.ddmi.s20180801-000000-e20180801-235959.l1.power-brcs-cdr.a12.d12.nc": {"collection": "CYGNSS_L1_CDR_V1.2", "version": "1.2", "direct_link": 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"ATL15_A2_0318_20km_003_01.nc", "data_center": "NSIDC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"MLS-Aura_L2GP-CH3OH_v04-20-c01_2004d215.he5": {"collection": "ML2CH3OH", "version": "004", "direct_link": "s3://gesdisc-cumulus-prod-protected/Aura_MLS_Level2/ML2CH3OH.004/2004/MLS-Aura_L2GP-CH3OH_v04-20-c01_2004d215.he5", "filename": "MLS-Aura_L2GP-CH3OH_v04-20-c01_2004d215.he5", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"TROPESS_CrIS-SNPP_L2_Standard_H2O_20160102_MUSES_R1p12_SC_MGMEX_F0p6.nc": {"collection": "TRPSDL2ALLCRSMGMEX", "version": "1", "direct_link": "s3://gesdisc-cumulus-prod-protected/TROPESS_MegaCities_Standard/TRPSDL2ALLCRSMGMEX.1/2016/TROPESS_CrIS-SNPP_L2_Standard_H2O_20160102_MUSES_R1p12_SC_MGMEX_F0p6.nc", "filename": "TROPESS_CrIS-SNPP_L2_Standard_H2O_20160102_MUSES_R1p12_SC_MGMEX_F0p6.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"MERRA2_100.tavg3_3d_trb_Ne.19800101.nc4": {"collection": "M2T3NETRB", "version": "5.12.4", "direct_link": "s3://gesdisc-cumulus-prod-protected/MERRA2/M2T3NETRB.5.12.4/1980/01/MERRA2_100.tavg3_3d_trb_Ne.19800101.nc4", "filename": "MERRA2_100.tavg3_3d_trb_Ne.19800101.nc4", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"GOZ-Source-MLP_O3_ev1-01_1979.nc4": {"collection": "GozSmlpO3", "version": "1", "direct_link": "s3://gesdisc-cumulus-prod-protected/GOZCARDS/GozSmlpO3.1/GOZ-Source-MLP_O3_ev1-01_1979.nc4", "filename": "GOZ-Source-MLP_O3_ev1-01_1979.nc4", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"S5P_OFFL_L2__CO_____20190806T022006_20190806T040136_09388_01_010302_20190812T014003.nc": {"collection": "S5P_L2__CO_____HiR", "version": "1", "direct_link": "s3://gesdisc-cumulus-prod-protected/S5P_TROPOMI_Level2/S5P_L2__CO_____HiR.1/2019/218/S5P_OFFL_L2__CO_____20190806T022006_20190806T040136_09388_01_010302_20190812T014003.nc", "filename": "S5P_OFFL_L2__CO_____20190806T022006_20190806T040136_09388_01_010302_20190812T014003.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, "Caught exception An error occurred (403) when calling the HeadObject operation: Forbidden while trying to process file from collection SWOT_L2_HR_PIXC_2.0, version 2.0", {"CMS_Flux_OceanPrior_2010_v2.nc": {"collection": "CMSFluxOceanPrior", "version": "2", "direct_link": "s3://gesdisc-cumulus-prod-protected/CMS/CMSFluxOceanPrior.2/CMS_Flux_OceanPrior_2010_v2.nc", "filename": "CMS_Flux_OceanPrior_2010_v2.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"GLDAS_VIC10_M.A194801.020.nc4": {"collection": "GLDAS_VIC10_M", "version": "2.0", "direct_link": "s3://gesdisc-cumulus-prod-protected/GLDAS/GLDAS_VIC10_M.2.0/1948/GLDAS_VIC10_M.A194801.020.nc4", "filename": "GLDAS_VIC10_M.A194801.020.nc4", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"cyg.ddmi.s20180801-000000-e20180801-235959.l2.wind-mss.a32.d33.nc": {"collection": "CYGNSS_L2_V3.2", "version": "3.2", "direct_link": "s3://podaac-ops-cumulus-protected/CYGNSS_L2_V3.2/cyg.ddmi.s20180801-000000-e20180801-235959.l2.wind-mss.a32.d33.nc", "filename": "cyg.ddmi.s20180801-000000-e20180801-235959.l2.wind-mss.a32.d33.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"GSSTFM.3.1987.07.01.he5": {"collection": "GSSTFM", "version": "3", "direct_link": "s3://gesdisc-cumulus-prod-protected/GSSTF/GSSTFM.3/1987/GSSTFM.3.1987.07.01.he5", "filename": "GSSTFM.3.1987.07.01.he5", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"OMI-Aura_L2G-OMSO2G_2004m1001_v003-2020m0526t135739.he5": {"collection": "OMSO2G", "version": "003", "direct_link": "s3://gesdisc-cumulus-prod-protected/Aura_OMI_Level2G/OMSO2G.003/2004/OMI-Aura_L2G-OMSO2G_2004m1001_v003-2020m0526t135739.he5", "filename": "OMI-Aura_L2G-OMSO2G_2004m1001_v003-2020m0526t135739.he5", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"AIRS.2002.08.30.225.L2.RetSup.v6.0.7.0.G13201091521.hdf": {"collection": "AIRX2SUP", "version": "006", "direct_link": "s3://gesdisc-cumulus-prod-protected/Aqua_AIRS_Level2/AIRX2SUP.006/2002/242/AIRS.2002.08.30.225.L2.RetSup.v6.0.7.0.G13201091521.hdf", "filename": "AIRS.2002.08.30.225.L2.RetSup.v6.0.7.0.G13201091521.hdf", "data_center": "GES_DISC", "fsm_strategy": "Not found", "page_size": "Not found"}}, "Caught exception An error occurred (403) when calling the HeadObject operation: Forbidden while trying to process file from collection SWOT_L2_HR_PIXC_1.1, version 1.1", {"discoverAQ-car_p3b_20140708_2037_Level1C_20171110.nc": {"collection": "CAR_DISCOVERAQ_L1C", "version": "1", "direct_link": "s3://gesdisc-cumulus-prod-protected/CAR/CAR_DISCOVERAQ_L1C.1/discoverAQ-car_p3b_20140708_2037_Level1C_20171110.nc", "filename": "discoverAQ-car_p3b_20140708_2037_Level1C_20171110.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"TROPESS_CrIS-SNPP_L2_Summary_O3_20210201_MUSES_R1p11_FS_F0p6.nc": {"collection": "TRPSYL2O3CRSFS", "version": "1", "direct_link": "s3://gesdisc-cumulus-prod-protected/TROPESS_Summary/TRPSYL2O3CRSFS.1/2021/TROPESS_CrIS-SNPP_L2_Summary_O3_20210201_MUSES_R1p11_FS_F0p6.nc", "filename": "TROPESS_CrIS-SNPP_L2_Summary_O3_20210201_MUSES_R1p11_FS_F0p6.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"GRACEDADM_CLSM0125US_7D.A20020401.040.nc4": {"collection": "GRACEDADM_CLSM0125US_7D", "version": "4.0", "direct_link": "s3://gesdisc-cumulus-prod-protected/GRACEDA/GRACEDADM_CLSM0125US_7D.4.0/2002/GRACEDADM_CLSM0125US_7D.A20020401.040.nc4", "filename": "GRACEDADM_CLSM0125US_7D.A20020401.040.nc4", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"GOZ-Source-MLP_H2O_ev1-01_1991.nc4": {"collection": "GozSmlpH2O", "version": "1", "direct_link": "s3://gesdisc-cumulus-prod-protected/GOZCARDS/GozSmlpH2O.1/GOZ-Source-MLP_H2O_ev1-01_1991.nc4", "filename": "GOZ-Source-MLP_H2O_ev1-01_1991.nc4", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"PET_MULTISEN_025.L4.V002.19840101T00Z.nc": {"collection": "PET_PU_3H025", "version": "002", "direct_link": "s3://gesdisc-cumulus-prod-protected/PET_PU/PET_PU_3H025.002/1984/PET_MULTISEN_025.L4.V002.19840101T00Z.nc", "filename": "PET_MULTISEN_025.L4.V002.19840101T00Z.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"MLS-Aura_L2GP-HO2_v04-20-c01_2004d215.he5": {"collection": "ML2HO2", "version": "004", "direct_link": "s3://gesdisc-cumulus-prod-protected/Aura_MLS_Level2/ML2HO2.004/2004/MLS-Aura_L2GP-HO2_v04-20-c01_2004d215.he5", "filename": "MLS-Aura_L2GP-HO2_v04-20-c01_2004d215.he5", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"OMI-Aura_L2G-OMCLDRRG_2004m1001_v003-2018m0430t175306.he5": {"collection": "OMCLDRRG", "version": "003", "direct_link": "s3://gesdisc-cumulus-prod-protected/Aura_OMI_Level2G/OMCLDRRG.003/2004/OMI-Aura_L2G-OMCLDRRG_2004m1001_v003-2018m0430t175306.he5", "filename": "OMI-Aura_L2G-OMCLDRRG_2004m1001_v003-2018m0430t175306.he5", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"TROPESS_CrIS-SNPP_L2_Standard_CH4_20210201_MUSES_R1p11_FS_F0p1.nc": {"collection": "TRPSDL2CH4CRSFS", "version": "1", "direct_link": "s3://gesdisc-cumulus-prod-protected/TROPESS_Standard/TRPSDL2CH4CRSFS.1/2021/TROPESS_CrIS-SNPP_L2_Standard_CH4_20210201_MUSES_R1p11_FS_F0p1.nc", "filename": "TROPESS_CrIS-SNPP_L2_Standard_CH4_20210201_MUSES_R1p11_FS_F0p1.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"ARMCAS-car_c131_19950603_1675_Level1C_20171129.nc": {"collection": "CAR_ARMCAS_L1C", "version": "1", "direct_link": "s3://gesdisc-cumulus-prod-protected/CAR/CAR_ARMCAS_L1C.1/ARMCAS-car_c131_19950603_1675_Level1C_20171129.nc", "filename": "ARMCAS-car_c131_19950603_1675_Level1C_20171129.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"TROPESS_AIRS-Aqua_OMI-Aura_L2_Standard_O3_20210201_MUSES_R1p11_FS_F0p1.nc": {"collection": "TRPSDL2O3AIRSOMIFS", "version": "1", "direct_link": "s3://gesdisc-cumulus-prod-protected/TROPESS_Standard/TRPSDL2O3AIRSOMIFS.1/2021/TROPESS_AIRS-Aqua_OMI-Aura_L2_Standard_O3_20210201_MUSES_R1p11_FS_F0p1.nc", "filename": "TROPESS_AIRS-Aqua_OMI-Aura_L2_Standard_O3_20210201_MUSES_R1p11_FS_F0p1.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"MultiInstrumentFusedXCO2_20140906_v3_1639402833.nc": {"collection": "MultiInstrumentFusedXCO2", "version": "3", "direct_link": "s3://gesdisc-cumulus-prod-protected/CO2/MultiInstrumentFusedXCO2.3/2014/MultiInstrumentFusedXCO2_20140906_v3_1639402833.nc", "filename": "MultiInstrumentFusedXCO2_20140906_v3_1639402833.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"GRD-3_2002095-2002120_GRAC_UTCSR_BA01_0600_OCN_v04.nc": {"collection": "TELLUS_GRAC_L3_CSR_RL06_OCN_v04", "version": "RL06v04", "direct_link": "s3://podaac-ops-cumulus-protected/TELLUS_GRAC_L3_CSR_RL06_OCN_v04/GRD-3_2002095-2002120_GRAC_UTCSR_BA01_0600_OCN_v04.nc", "filename": "GRD-3_2002095-2002120_GRAC_UTCSR_BA01_0600_OCN_v04.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"LPRM-AMSR2_L2_DS_D_SOILM2_V001_20120702231838.nc4": {"collection": "LPRM_AMSR2_DS_SOILM2", "version": "001", "direct_link": "s3://gesdisc-cumulus-prod-protected/WAOB/LPRM_AMSR2_DS_SOILM2.001/2012/184/LPRM-AMSR2_L2_DS_D_SOILM2_V001_20120702231838.nc4", "filename": "LPRM-AMSR2_L2_DS_D_SOILM2_V001_20120702231838.nc4", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"MYD21C1.A2002185.061.2020071135152.hdf": {"collection": "MYD21C1", "version": "061", "direct_link": "s3://lp-prod-protected/MYD21C1.061/MYD21C1.A2002185.061.2020071135152/MYD21C1.A2002185.061.2020071135152.hdf", "filename": "MYD21C1.A2002185.061.2020071135152.hdf", "data_center": "LPDAAC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"OMI-Aura_L1-OML1BRUG_2004m1001t0003-o001132_v0401-2022m0615t1307.nc": {"collection": "OML1BRUG", "version": "004", "direct_link": "s3://gesdisc-cumulus-prod-protected/Aura_OMI_Level1/OML1BRUG.004/2004/275/OMI-Aura_L1-OML1BRUG_2004m1001t0003-o001132_v0401-2022m0615t1307.nc", "filename": "OMI-Aura_L1-OML1BRUG_2004m1001t0003-o001132_v0401-2022m0615t1307.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"F11_SSMI_FCDR2021_L2_V1_19911203-S180601-E194758.000074.V01E.nc": {"collection": "PRECIP_SSMI_F11", "version": "1", "direct_link": "s3://gesdisc-cumulus-prod-protected/Precipitation/PRECIP_SSMI_F11.1/1991/337/F11_SSMI_FCDR2021_L2_V1_19911203-S180601-E194758.000074.V01E.nc", "filename": "F11_SSMI_FCDR2021_L2_V1_19911203-S180601-E194758.000074.V01E.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, "Caught exception 'accessKeyId' while trying to process file from collection TEMPO_CLDO4_L2, version V01", {"GOZ-Merged-MLP_H2O_ev1-01_1991.nc4": {"collection": "GozMmlpH2O", "version": "1", "direct_link": "s3://gesdisc-cumulus-prod-protected/GOZCARDS/GozMmlpH2O.1/GOZ-Merged-MLP_H2O_ev1-01_1991.nc4", "filename": "GOZ-Merged-MLP_H2O_ev1-01_1991.nc4", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"LPRM-TMI_L2_SOILM2_V001-20120404T010804Z_19971207235718.nc": {"collection": "LPRM_TMI_SOILM2", "version": "001", "direct_link": "s3://gesdisc-cumulus-prod-protected/WAOB/LPRM_TMI_SOILM2.001/1997/341/LPRM-TMI_L2_SOILM2_V001-20120404T010804Z_19971207235718.nc", "filename": "LPRM-TMI_L2_SOILM2_V001-20120404T010804Z_19971207235718.nc", "data_center": "GES_DISC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"AIRS.2002.08.30.225.L1C.AIRS_Rad.v6.7.2.0.G20035181328.hdf": {"collection": "AIRICRAD", "version": "6.7", "direct_link": "s3://gesdisc-cumulus-prod-protected/Aqua_AIRS_Level1/AIRICRAD.6.7/2002/242/AIRS.2002.08.30.225.L1C.AIRS_Rad.v6.7.2.0.G20035181328.hdf", "filename": "AIRS.2002.08.30.225.L1C.AIRS_Rad.v6.7.2.0.G20035181328.hdf", "data_center": "GES_DISC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"MYD16A3GF.A2002001.h18v14.061.2020301202641.hdf": {"collection": "MYD16A3GF", "version": "061", "direct_link": "s3://lp-prod-protected/MYD16A3GF.061/MYD16A3GF.A2002001.h18v14.061.2020301202641/MYD16A3GF.A2002001.h18v14.061.2020301202641.hdf", "filename": "MYD16A3GF.A2002001.h18v14.061.2020301202641.hdf", "data_center": "LPDAAC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"S5P_RPRO_L2__O3_____20180430T001851_20180430T020219_02818_01_010107_20190513T141133.nc": {"collection": "S5P_L2__O3_TOT", "version": "1", "direct_link": "s3://gesdisc-cumulus-prod-protected/S5P_TROPOMI_Level2/S5P_L2__O3_TOT.1/2018/120/S5P_RPRO_L2__O3_____20180430T001851_20180430T020219_02818_01_010107_20190513T141133.nc", "filename": "S5P_RPRO_L2__O3_____20180430T001851_20180430T020219_02818_01_010107_20190513T141133.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"oco3_L2DiaSC_01457a_190806_B10305r_211112191800.h5": {"collection": "OCO3_L2_Diagnostic", "version": "10r", "direct_link": "s3://gesdisc-cumulus-prod-protected/OCO3_DATA/OCO3_L2_Diagnostic.10r/2019/218/oco3_L2DiaSC_01457a_190806_B10305r_211112191800.h5", "filename": "oco3_L2DiaSC_01457a_190806_B10305r_211112191800.h5", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"RSS_SMAP_SSS_L2C_r00870_20150401T004312_2015091_FNL_V06.0.nc": {"collection": "SMAP_RSS_L2_SSS_V6", "version": "6.0", "direct_link": "s3://podaac-ops-cumulus-protected/SMAP_RSS_L2_SSS_V6/RSS_SMAP_SSS_L2C_r00870_20150401T004312_2015091_FNL_V06.0.nc", "filename": "RSS_SMAP_SSS_L2C_r00870_20150401T004312_2015091_FNL_V06.0.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, "Caught exception 'accessKeyId' while trying to process file from collection TEMPO_O3TOT_L2, version V01", {"TROPESS_CrIS-JPSS1_L2_Standard_NH3_20210401_MUSES_R1p12_FS_F0p1.nc": {"collection": "TRPSDL2NH3CRS1FS", "version": "1", "direct_link": "s3://gesdisc-cumulus-prod-protected/TROPESS_Standard/TRPSDL2NH3CRS1FS.1/2021/TROPESS_CrIS-JPSS1_L2_Standard_NH3_20210401_MUSES_R1p12_FS_F0p1.nc", "filename": "TROPESS_CrIS-JPSS1_L2_Standard_NH3_20210401_MUSES_R1p12_FS_F0p1.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"TROPESS_AIRS-Aqua_L2_Summary_O3_20210201_MUSES_R1p11_FS_F0p6.nc": {"collection": "TRPSYL2O3AIRSFS", "version": "1", "direct_link": "s3://gesdisc-cumulus-prod-protected/TROPESS_Summary/TRPSYL2O3AIRSFS.1/2021/TROPESS_AIRS-Aqua_L2_Summary_O3_20210201_MUSES_R1p11_FS_F0p6.nc", "filename": "TROPESS_AIRS-Aqua_L2_Summary_O3_20210201_MUSES_R1p11_FS_F0p6.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"Arctas-car_p3b_20080406_2001_Level1C_20171121.nc": {"collection": "CAR_ARCTAS_L1C", "version": "1", "direct_link": "s3://gesdisc-cumulus-prod-protected/CAR/CAR_ARCTAS_L1C.1/Arctas-car_p3b_20080406_2001_Level1C_20171121.nc", "filename": "Arctas-car_p3b_20080406_2001_Level1C_20171121.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"TARFOX-car_c131_19960710_1722_Level1C_20171129.nc": {"collection": "CAR_TARFOX_L1C", "version": "1", "direct_link": "s3://gesdisc-cumulus-prod-protected/CAR/CAR_TARFOX_L1C.1/TARFOX-car_c131_19960710_1722_Level1C_20171129.nc", "filename": "TARFOX-car_c131_19960710_1722_Level1C_20171129.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"ucar_cu_cygnss_sm_v1_2017_077.nc": {"collection": "CYGNSS_L3_SOIL_MOISTURE_V1.0", "version": "1.0", "direct_link": "s3://podaac-ops-cumulus-protected/CYGNSS_L3_SOIL_MOISTURE_V1.0/2017/077/ucar_cu_cygnss_sm_v1_2017_077.nc", "filename": "ucar_cu_cygnss_sm_v1_2017_077.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, "Caught exception 'accessKeyId' while trying to process file from collection TEMPO_HCHO_L2, version V01", {"OMI-Aura_L2G-OMHCHOG_2004m1001_v003-2014m0707t161246.he5": {"collection": "OMHCHOG", "version": "003", "direct_link": "s3://gesdisc-cumulus-prod-protected/Aura_OMI_Level2G/OMHCHOG.003/2004/OMI-Aura_L2G-OMHCHOG_2004m1001_v003-2014m0707t161246.he5", "filename": "OMI-Aura_L2G-OMHCHOG_2004m1001_v003-2014m0707t161246.he5", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"MLS-Aura_L3MB-ClO_v04-23-c03_2004.nc": {"collection": "ML3MBCLO", "version": "004", "direct_link": "s3://gesdisc-cumulus-prod-protected/Aura_MLS_Level3/ML3MBCLO.004/2004/MLS-Aura_L3MB-ClO_v04-23-c03_2004.nc", "filename": "MLS-Aura_L3MB-ClO_v04-23-c03_2004.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"20120105050601-JPL-L2P_GHRSST-SSTskin-VIIRS_NPP-D-v02.0-fv01.0.nc": {"collection": "VIIRS_NPP-JPL-L2P-v2016.2", "version": "2016.2", "direct_link": "s3://podaac-ops-cumulus-protected/VIIRS_NPP-JPL-L2P-v2016.2/20120105050601-JPL-L2P_GHRSST-SSTskin-VIIRS_NPP-D-v02.0-fv01.0.nc", "filename": "20120105050601-JPL-L2P_GHRSST-SSTskin-VIIRS_NPP-D-v02.0-fv01.0.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"EMIT_L1B_RAD_001_20220810T034103_2222203_001.nc": {"collection": "EMITL1BRAD", "version": "001", "direct_link": "s3://lp-prod-protected/EMITL1BRAD.001/EMIT_L1B_RAD_001_20220810T034103_2222203_001/EMIT_L1B_RAD_001_20220810T034103_2222203_001.nc", "filename": "EMIT_L1B_RAD_001_20220810T034103_2222203_001.nc", "data_center": "LPDAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"GOZ-Merged-MLP_HNO3_ev1-01_2004.nc4": {"collection": "GozMmlpHNO3", "version": "1", "direct_link": "s3://gesdisc-cumulus-prod-protected/GOZCARDS/GozMmlpHNO3.1/GOZ-Merged-MLP_HNO3_ev1-01_2004.nc4", "filename": "GOZ-Merged-MLP_HNO3_ev1-01_2004.nc4", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"MERRA2_100.tavgM_3d_udt_Np.198001.nc4": {"collection": "M2TMNPUDT", "version": "5.12.4", "direct_link": "s3://gesdisc-cumulus-prod-protected/MERRA2_MONTHLY/M2TMNPUDT.5.12.4/1980/MERRA2_100.tavgM_3d_udt_Np.198001.nc4", "filename": "MERRA2_100.tavgM_3d_udt_Np.198001.nc4", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"TROPESS_AIRS-Aqua_L2_Summary_O3_20020901_MUSES_R1p6_RS_F0p8_J0.nc": {"collection": "TRPSYL2O3AIRSORS", "version": "1", "direct_link": "s3://gesdisc-cumulus-prod-protected/TROPESS_Reanalysis_Summary/TRPSYL2O3AIRSORS.1/2002/TROPESS_AIRS-Aqua_L2_Summary_O3_20020901_MUSES_R1p6_RS_F0p8_J0.nc", "filename": "TROPESS_AIRS-Aqua_L2_Summary_O3_20020901_MUSES_R1p6_RS_F0p8_J0.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"WLDAS_NOAHMP001_DA1_19790103.D10.nc": {"collection": "WLDAS_NOAHMP001_DA1", "version": "D1.0", "direct_link": "s3://gesdisc-cumulus-prod-protected/WLDAS/WLDAS_NOAHMP001_DA1.D1.0/1979/01/WLDAS_NOAHMP001_DA1_19790103.D10.nc", "filename": "WLDAS_NOAHMP001_DA1_19790103.D10.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"19820101120000-UKMO-L4_GHRSST-SSTfnd-OSTIA-GLOB_REP-v02.0-fv02.0.nc": {"collection": "OSTIA-UKMO-L4-GLOB-REP-v2.0", "version": "2.0", "direct_link": "s3://podaac-ops-cumulus-protected/OSTIA-UKMO-L4-GLOB-REP-v2.0/1982/001/19820101120000-UKMO-L4_GHRSST-SSTfnd-OSTIA-GLOB_REP-v02.0-fv02.0.nc", "filename": "19820101120000-UKMO-L4_GHRSST-SSTfnd-OSTIA-GLOB_REP-v02.0-fv02.0.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"GRD-3_2002095-2002120_GRAC_GFZOP_BA01_0600_OCN_v04.nc": {"collection": "TELLUS_GRAC_L3_GFZ_RL06_OCN_v04", "version": "RL06v04", "direct_link": "s3://podaac-ops-cumulus-protected/TELLUS_GRAC_L3_GFZ_RL06_OCN_v04/GRD-3_2002095-2002120_GRAC_GFZOP_BA01_0600_OCN_v04.nc", "filename": "GRD-3_2002095-2002120_GRAC_GFZOP_BA01_0600_OCN_v04.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"GRD-3_2002094-2002120_GRAC_JPLEM_BA01_0600_OCN_v04.nc": {"collection": "TELLUS_GRAC_L3_JPL_RL06_OCN_v04", "version": "RL06v04", "direct_link": "s3://podaac-ops-cumulus-protected/TELLUS_GRAC_L3_JPL_RL06_OCN_v04/GRD-3_2002094-2002120_GRAC_JPLEM_BA01_0600_OCN_v04.nc", "filename": "GRD-3_2002094-2002120_GRAC_JPLEM_BA01_0600_OCN_v04.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"TOVSB_5DAYS_AM_B910630_E910704_ND.HDF.Z": {"collection": "TOVSB5ND", "version": "01", "direct_link": "s3://gesdisc-cumulus-prod-protected/tovs/TOVSB5ND/1991/180/TOVSB_5DAYS_AM_B910630_E910704_ND.HDF.Z", "filename": "TOVSB_5DAYS_AM_B910630_E910704_ND.HDF.Z", "data_center": "GES_DISC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"TROPESS_AIRS-Aqua_L2_Standard_CH4_20210201_MUSES_R1p11_FS_F0p1.nc": {"collection": "TRPSDL2CH4AIRSFS", "version": "1", "direct_link": "s3://gesdisc-cumulus-prod-protected/TROPESS_Standard/TRPSDL2CH4AIRSFS.1/2021/TROPESS_AIRS-Aqua_L2_Standard_CH4_20210201_MUSES_R1p11_FS_F0p1.nc", "filename": "TROPESS_AIRS-Aqua_L2_Standard_CH4_20210201_MUSES_R1p11_FS_F0p1.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"1C.F16.SSMIS.XCAL2021-V.20051120-S023527-E041722.010784.V07A.HDF5": {"collection": "GPM_1CF16SSMIS", "version": "07", "direct_link": "s3://gesdisc-cumulus-prod-protected/GPM_L1C/GPM_1CF16SSMIS.07/2005/324/1C.F16.SSMIS.XCAL2021-V.20051120-S023527-E041722.010784.V07A.HDF5", "filename": "1C.F16.SSMIS.XCAL2021-V.20051120-S023527-E041722.010784.V07A.HDF5", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"S6A_P4_2__HR_RED__NR_038_241_20211128T225521_20211128T230521_F04.nc": {"collection": "JASON_CS_S6A_L2_ALT_HR_RED_OST_NRT_F", "version": "F", "direct_link": "s3://podaac-ops-cumulus-protected/JASON_CS_S6A_L2_ALT_HR_RED_OST_NRT_F/S6A_P4_2__HR_RED__NR_038_241_20211128T225521_20211128T230521_F04.nc", "filename": "S6A_P4_2__HR_RED__NR_038_241_20211128T225521_20211128T230521_F04.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"20221026-100450_NZRO-NZAA_L1.nc": {"collection": "RONGOWAI_L1_SDR_V1.0", "version": "1.0", "direct_link": "s3://podaac-ops-cumulus-protected/RONGOWAI_L1_SDR_V1.0/20221026-100450_NZRO-NZAA_L1.nc", "filename": "20221026-100450_NZRO-NZAA_L1.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"ATL07-01_20181014000347_02350101_006_02.h5": {"collection": "ATL07", "version": "006", "direct_link": "s3://nsidc-cumulus-prod-protected/ATLAS/ATL07/006/2018/10/14/ATL07-01_20181014000347_02350101_006_02.h5", "filename": "ATL07-01_20181014000347_02350101_006_02.h5", "data_center": "NSIDC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"OMI-Aura_L2G-OMCLDO2G_2004m1001_v003-2017m1102t195214.he5": {"collection": "OMCLDO2G", "version": "003", "direct_link": "s3://gesdisc-cumulus-prod-protected/Aura_OMI_Level2G/OMCLDO2G.003/2004/OMI-Aura_L2G-OMCLDO2G_2004m1001_v003-2017m1102t195214.he5", "filename": "OMI-Aura_L2G-OMCLDO2G_2004m1001_v003-2017m1102t195214.he5", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"3H31.19980101.7.HDF": {"collection": "TRMM_3H31", "version": "7", "direct_link": "s3://gesdisc-cumulus-prod-protected/TRMM_L3/TRMM_3H31.7/1998/001/3H31.19980101.7.HDF", "filename": "3H31.19980101.7.HDF", "data_center": "GES_DISC", "fsm_strategy": "Not found", "page_size": "Not found"}}, "Caught exception An error occurred (404) when calling the HeadObject operation: Not Found while trying to process file from collection AIRS2CCF_NRT, version 7.0", {"ATL10-01_20181014000347_02350101_006_02.h5": {"collection": "ATL10", "version": "006", "direct_link": "s3://nsidc-cumulus-prod-protected/ATLAS/ATL10/006/2018/10/14/ATL10-01_20181014000347_02350101_006_02.h5", "filename": "ATL10-01_20181014000347_02350101_006_02.h5", "data_center": "NSIDC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"GLDAS_CLSM10_M.A194801.020.nc4": {"collection": "GLDAS_CLSM10_M", "version": "2.0", "direct_link": "s3://gesdisc-cumulus-prod-protected/GLDAS/GLDAS_CLSM10_M.2.0/1948/GLDAS_CLSM10_M.A194801.020.nc4", "filename": "GLDAS_CLSM10_M.A194801.020.nc4", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"1B.GPM.GMI.TB2021.20140304-S175932-E193159.000079.V07A.HDF5": {"collection": "GPM_1BGMI", "version": "07", "direct_link": "s3://gesdisc-cumulus-prod-protected/GPM_L1B/GPM_1BGMI.07/2014/063/1B.GPM.GMI.TB2021.20140304-S175932-E193159.000079.V07A.HDF5", "filename": "1B.GPM.GMI.TB2021.20140304-S175932-E193159.000079.V07A.HDF5", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"OMI-Aura_L1-OML1BIRR_2004m1001t1631-o001142_v0401-2022m0615t1321.nc": {"collection": "OML1BIRR", "version": "004", "direct_link": "s3://gesdisc-cumulus-prod-protected/Aura_OMI_Level1/OML1BIRR.004/2004/275/OMI-Aura_L1-OML1BIRR_2004m1001t1631-o001142_v0401-2022m0615t1321.nc", "filename": "OMI-Aura_L1-OML1BIRR_2004m1001t1631-o001142_v0401-2022m0615t1321.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"AIRS.2024.04.12.071.L2.CC_IR.v6.0.34.0.R24103050330.hdf": {"collection": "AIRS2CCF_NRT", "version": "006", "direct_link": "s3://gesdisc-cumulus-prod-protected/Aqua_AIRS_NRT/AIRS2CCF_NRT.006/2024/103/AIRS.2024.04.12.071.L2.CC_IR.v6.0.34.0.R24103050330.hdf", "filename": "AIRS.2024.04.12.071.L2.CC_IR.v6.0.34.0.R24103050330.hdf", "data_center": "GES_DISC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"TROPESS_CrIS-SNPP_L2_Standard_HDO_20210201_MUSES_R1p11_FS_F0p1.nc": {"collection": "TRPSDL2HDOCRSFS", "version": "1", "direct_link": "s3://gesdisc-cumulus-prod-protected/TROPESS_Standard/TRPSDL2HDOCRSFS.1/2021/TROPESS_CrIS-SNPP_L2_Standard_HDO_20210201_MUSES_R1p11_FS_F0p1.nc", "filename": "TROPESS_CrIS-SNPP_L2_Standard_HDO_20210201_MUSES_R1p11_FS_F0p1.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"20190109000000-NAVO-L4_GHRSST-SST1m-K10_SST-GLOB-v02.0-fv01.0.nc": {"collection": "K10_SST-NAVO-L4-GLOB-v01", "version": "1.0", "direct_link": "s3://podaac-ops-cumulus-protected/K10_SST-NAVO-L4-GLOB-v01/20190109000000-NAVO-L4_GHRSST-SST1m-K10_SST-GLOB-v02.0-fv01.0.nc", "filename": "20190109000000-NAVO-L4_GHRSST-SST1m-K10_SST-GLOB-v02.0-fv01.0.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"maclwp_totallwpave_1988_v1.nc4": {"collection": "MACTWP_mean", "version": "1", "direct_link": "s3://gesdisc-cumulus-prod-protected/LWP/MACTWP_mean.1/maclwp_totallwpave_1988_v1.nc4", "filename": "maclwp_totallwpave_1988_v1.nc4", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"NLDAS_MOS0125_M.A197901.020.nc": {"collection": "NLDAS_MOS0125_M", "version": "2.0", "direct_link": "s3://gesdisc-cumulus-prod-protected/NLDAS/NLDAS_MOS0125_M.2.0/1979/NLDAS_MOS0125_M.A197901.020.nc", "filename": "NLDAS_MOS0125_M.A197901.020.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"SMAP_L2B_SSS_00865_20150331T163144_R17000_V5.0.h5": {"collection": "SMAP_JPL_L2B_SSS_CAP_V5", "version": "5.0", "direct_link": "s3://podaac-ops-cumulus-protected/SMAP_JPL_L2B_SSS_CAP_V5/2015/090/SMAP_L2B_SSS_00865_20150331T163144_R17000_V5.0.h5", "filename": "SMAP_L2B_SSS_00865_20150331T163144_R17000_V5.0.h5", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"TROPESS_CrIS-SNPP_L2_Standard_O3_20160102_MUSES_R1p12_SC_MGBEI_F0p6.nc": {"collection": "TRPSDL2ALLCRSMGBEI", "version": "1", "direct_link": "s3://gesdisc-cumulus-prod-protected/TROPESS_MegaCities_Standard/TRPSDL2ALLCRSMGBEI.1/2016/TROPESS_CrIS-SNPP_L2_Standard_O3_20160102_MUSES_R1p12_SC_MGBEI_F0p6.nc", "filename": "TROPESS_CrIS-SNPP_L2_Standard_O3_20160102_MUSES_R1p12_SC_MGBEI_F0p6.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"AIRS.2002.09.01.L3.RetQuant005.v6.0.9.0.G13208032126.hdf": {"collection": "AIRX3QP5", "version": "006", "direct_link": "s3://gesdisc-cumulus-prod-protected/Aqua_AIRS_Level3/AIRX3QP5.006/2002/AIRS.2002.09.01.L3.RetQuant005.v6.0.9.0.G13208032126.hdf", "filename": "AIRS.2002.09.01.L3.RetQuant005.v6.0.9.0.G13208032126.hdf", "data_center": "GES_DISC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"cyg.ddmi.s20180801-000000-e20180801-235959.l2.surface-flux.a20.d20.nc": {"collection": "CYGNSS_L2_SURFACE_FLUX_V2.0", "version": "2.0", "direct_link": "s3://podaac-ops-cumulus-protected/CYGNSS_L2_SURFACE_FLUX_V2.0/cyg.ddmi.s20180801-000000-e20180801-235959.l2.surface-flux.a20.d20.nc", "filename": "cyg.ddmi.s20180801-000000-e20180801-235959.l2.surface-flux.a20.d20.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"2A-CLIM.GCOMW1.AMSR2.GPROF2021v1.20120702-S223117-E001009.000676.V07A.HDF5": {"collection": "GPM_2AGPROFGCOMW1AMSR2_CLIM", "version": "07", "direct_link": "s3://gesdisc-cumulus-prod-protected/GPM_L2/GPM_2AGPROFGCOMW1AMSR2_CLIM.07/2012/184/2A-CLIM.GCOMW1.AMSR2.GPROF2021v1.20120702-S223117-E001009.000676.V07A.HDF5", "filename": "2A-CLIM.GCOMW1.AMSR2.GPROF2021v1.20120702-S223117-E001009.000676.V07A.HDF5", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"MERRA2_100.tavgM_3d_rad_Np.198001.nc4": {"collection": "M2TMNPRAD", "version": "5.12.4", "direct_link": "s3://gesdisc-cumulus-prod-protected/MERRA2_MONTHLY/M2TMNPRAD.5.12.4/1980/MERRA2_100.tavgM_3d_rad_Np.198001.nc4", "filename": "MERRA2_100.tavgM_3d_rad_Np.198001.nc4", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"TROPESS_CrIS-JPSS1_L2_Standard_CH4_20210401_MUSES_R1p12_FS_F0p1.nc": {"collection": "TRPSDL2CH4CRS1FS", "version": "1", "direct_link": "s3://gesdisc-cumulus-prod-protected/TROPESS_Standard/TRPSDL2CH4CRS1FS.1/2021/TROPESS_CrIS-JPSS1_L2_Standard_CH4_20210401_MUSES_R1p12_FS_F0p1.nc", "filename": "TROPESS_CrIS-JPSS1_L2_Standard_CH4_20210401_MUSES_R1p12_FS_F0p1.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"AIRS.2002.08.31.L3.RetSup001.v7.0.3.0.G20203113933.hdf": {"collection": "AIRX3SPD", "version": "7.0", "direct_link": "s3://gesdisc-cumulus-prod-protected/Aqua_AIRS_Level3/AIRX3SPD.7.0/2002/AIRS.2002.08.31.L3.RetSup001.v7.0.3.0.G20203113933.hdf", "filename": "AIRS.2002.08.31.L3.RetSup001.v7.0.3.0.G20203113933.hdf", "data_center": "GES_DISC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"GSSTFMC.3.Jan.1988_2008.he5": {"collection": "GSSTFMC", "version": "3", "direct_link": "s3://gesdisc-cumulus-prod-protected/GSSTF/GSSTFMC.3/GSSTFMC.3.Jan.1988_2008.he5", "filename": "GSSTFMC.3.Jan.1988_2008.he5", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"CMS_Flux_Total_2010_v2.nc": {"collection": "CMSFluxTotal", "version": "2", "direct_link": "s3://gesdisc-cumulus-prod-protected/CMS/CMSFluxTotal.2/CMS_Flux_Total_2010_v2.nc", "filename": "CMS_Flux_Total_2010_v2.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"MOD21C2.A2000049.061.2020101172303.hdf": {"collection": "MOD21C2", "version": "061", "direct_link": "s3://lp-prod-protected/MOD21C2.061/MOD21C2.A2000049.061.2020101172303/MOD21C2.A2000049.061.2020101172303.hdf", "filename": "MOD21C2.A2000049.061.2020101172303.hdf", "data_center": "LPDAAC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"MODIS_CR.EqualAngle_3h.C61.V1.0.L3.2003.nc4": {"collection": "MODIS_CR_Equal_Angle_3h", "version": "1.0", "direct_link": "s3://gesdisc-cumulus-prod-protected/CloudRegimes/MODIS_CR_Equal_Angle_3h.1.0/MODIS_CR.EqualAngle_3h.C61.V1.0.L3.2003.nc4", "filename": "MODIS_CR.EqualAngle_3h.C61.V1.0.L3.2003.nc4", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, "Caught exception An error occurred (403) when calling the HeadObject operation: Forbidden while trying to process file from collection SWOT_L2_RAD_IGDR_2.0, version 2.0", {"20020601161248-REMSS-L2P_GHRSST-SSTsubskin-AMSRE-l2b_v07a_r00414.dat-v02.0-fv01.0.nc": {"collection": "AMSRE-REMSS-L2P-v7a", "version": "7a", "direct_link": "s3://podaac-ops-cumulus-protected/AMSRE-REMSS-L2P-v7a/20020601161248-REMSS-L2P_GHRSST-SSTsubskin-AMSRE-l2b_v07a_r00414.dat-v02.0-fv01.0.nc", "filename": "20020601161248-REMSS-L2P_GHRSST-SSTsubskin-AMSRE-l2b_v07a_r00414.dat-v02.0-fv01.0.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"FLEXPART_black_carbon_aerosol_L4_global_daily_1x1_degrees_V1_2008.nc": {"collection": "BCFLEXPART", "version": "1", "direct_link": "s3://gesdisc-cumulus-prod-protected/FLEXPART/BCFLEXPART.1/FLEXPART_black_carbon_aerosol_L4_global_daily_1x1_degrees_V1_2008.nc", "filename": "FLEXPART_black_carbon_aerosol_L4_global_daily_1x1_degrees_V1_2008.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"MERRA2_100.instM_2d_int_Nx.198001.nc4": {"collection": "M2IMNXINT", "version": "5.12.4", "direct_link": "s3://gesdisc-cumulus-prod-protected/MERRA2_MONTHLY/M2IMNXINT.5.12.4/1980/MERRA2_100.instM_2d_int_Nx.198001.nc4", "filename": "MERRA2_100.instM_2d_int_Nx.198001.nc4", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"S5P_OFFL_L2__AER_AI_20190806T022006_20190806T040136_09388_01_010302_20190812T014007.nc": {"collection": "S5P_L2__AER_AI_HiR", "version": "1", "direct_link": "s3://gesdisc-cumulus-prod-protected/S5P_TROPOMI_Level2/S5P_L2__AER_AI_HiR.1/2019/218/S5P_OFFL_L2__AER_AI_20190806T022006_20190806T040136_09388_01_010302_20190812T014007.nc", "filename": "S5P_OFFL_L2__AER_AI_20190806T022006_20190806T040136_09388_01_010302_20190812T014007.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, "Caught exception 'accessKeyId' while trying to process file from collection TEMPO_NO2_L3, version V01", {"FIREACE-car_c131_19980521_R2_1752_Level1C_20171201.nc": {"collection": "CAR_FIREACE_L1C", "version": "1", "direct_link": "s3://gesdisc-cumulus-prod-protected/CAR/CAR_FIREACE_L1C.1/FIREACE-car_c131_19980521_R2_1752_Level1C_20171201.nc", "filename": "FIREACE-car_c131_19980521_R2_1752_Level1C_20171201.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"20080723120000-ABOM-L4_GHRSST-SSTfnd-GAMSSA_28km-GLOB-v02.0-fv01.0.nc": {"collection": "GAMSSA_28km-ABOM-L4-GLOB-v01", "version": "1.0", "direct_link": "s3://podaac-ops-cumulus-protected/GAMSSA_28km-ABOM-L4-GLOB-v01/20080723120000-ABOM-L4_GHRSST-SSTfnd-GAMSSA_28km-GLOB-v02.0-fv01.0.nc", "filename": "20080723120000-ABOM-L4_GHRSST-SSTfnd-GAMSSA_28km-GLOB-v02.0-fv01.0.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"20121019000000-STAR-L2P_GHRSST-SSTsubskin-AVHRRF_MB-ACSPO_V2.80-v02.0-fv01.0.nc": {"collection": "AVHRRF_MB-STAR-L2P-v2.80", "version": "2.80", "direct_link": "s3://podaac-ops-cumulus-protected/AVHRRF_MB-STAR-L2P-v2.80/2012/293/20121019000000-STAR-L2P_GHRSST-SSTsubskin-AVHRRF_MB-ACSPO_V2.80-v02.0-fv01.0.nc", "filename": "20121019000000-STAR-L2P_GHRSST-SSTsubskin-AVHRRF_MB-ACSPO_V2.80-v02.0-fv01.0.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"S5P_OFFL_L2__HCHO___20190806T022006_20190806T040136_09388_01_010107_20190812T040851.nc": {"collection": "S5P_L2__HCHO___HiR", "version": "1", "direct_link": "s3://gesdisc-cumulus-prod-protected/S5P_TROPOMI_Level2/S5P_L2__HCHO___HiR.1/2019/218/S5P_OFFL_L2__HCHO___20190806T022006_20190806T040136_09388_01_010107_20190812T040851.nc", "filename": "S5P_OFFL_L2__HCHO___20190806T022006_20190806T040136_09388_01_010107_20190812T040851.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, "Caught exception An error occurred (403) when calling the HeadObject operation: Forbidden while trying to process file from collection SWOT_L2_RAD_OGDR_2.0, version 2.0", {"AIRS.AQUA.AIRS.20020901.M01.L3_SpecOLR.std.v06_01_00.M.191116170609.nc": {"collection": "AIRSIL3MSOLR", "version": "6.1", "direct_link": "s3://gesdisc-cumulus-prod-protected/Aqua_AIRS_Level3/AIRSIL3MSOLR.6.1/2002/AIRS.AQUA.AIRS.20020901.M01.L3_SpecOLR.std.v06_01_00.M.191116170609.nc", "filename": "AIRS.AQUA.AIRS.20020901.M01.L3_SpecOLR.std.v06_01_00.M.191116170609.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"MLS-Aura_L3DZ-HNO3_v05-01-c06_2004.nc": {"collection": "ML3DZHNO3", "version": "005", "direct_link": "s3://gesdisc-cumulus-prod-protected/Aura_MLS_Level3/ML3DZHNO3.005/2004/MLS-Aura_L3DZ-HNO3_v05-01-c06_2004.nc", "filename": "MLS-Aura_L3DZ-HNO3_v05-01-c06_2004.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"20230319000000-STAR-L2P_GHRSST-SSTsubskin-VIIRS_N21-ACSPO_V2.80-v02.0-fv01.0.nc": {"collection": "N21-VIIRS-L2P-ACSPO-v2.80", "version": "2.80", "direct_link": "s3://podaac-ops-cumulus-protected/N21-VIIRS-L2P-ACSPO-v2.80/20230319000000-STAR-L2P_GHRSST-SSTsubskin-VIIRS_N21-ACSPO_V2.80-v02.0-fv01.0.nc", "filename": "20230319000000-STAR-L2P_GHRSST-SSTsubskin-VIIRS_N21-ACSPO_V2.80-v02.0-fv01.0.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"OISSS_L4_multimission_global_monthly_v2.0_2011-09.nc": {"collection": "OISSS_L4_multimission_monthly_v2", "version": "2.0", "direct_link": "s3://podaac-ops-cumulus-protected/OISSS_L4_multimission_monthly_v2/OISSS_L4_multimission_global_monthly_v2.0_2011-09.nc", "filename": "OISSS_L4_multimission_global_monthly_v2.0_2011-09.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"MLS-Aura_L3DB-HCl_v04-23-c01_2004d215.nc": {"collection": "ML3DBHCL", "version": "004", "direct_link": "s3://gesdisc-cumulus-prod-protected/Aura_MLS_Level3/ML3DBHCL.004/2004/MLS-Aura_L3DB-HCl_v04-23-c01_2004d215.nc", "filename": "MLS-Aura_L3DB-HCl_v04-23-c01_2004d215.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"MLS-Aura_L3DB-O3_v05-01-c06_2004d215.nc": {"collection": "ML3DBO3", "version": "005", "direct_link": "s3://gesdisc-cumulus-prod-protected/Aura_MLS_Level3/ML3DBO3.005/2004/MLS-Aura_L3DB-O3_v05-01-c06_2004d215.nc", "filename": "MLS-Aura_L3DB-O3_v05-01-c06_2004d215.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"FLEXPART_organic_carbon_aerosol_L4_global_daily_1x1_degrees_V1_2008.nc": {"collection": "OCFLEXPART", "version": "1", "direct_link": "s3://gesdisc-cumulus-prod-protected/FLEXPART/OCFLEXPART.1/FLEXPART_organic_carbon_aerosol_L4_global_daily_1x1_degrees_V1_2008.nc", "filename": "FLEXPART_organic_carbon_aerosol_L4_global_daily_1x1_degrees_V1_2008.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"RSS_SMAP_SSS_L2C_r47566_20231227T214701_2023361_NRT_V06.0_001.nc": {"collection": "SMAP_RSS_L2_SSS_NRT_V6", "version": "6.0", "direct_link": "s3://podaac-ops-cumulus-protected/SMAP_RSS_L2_SSS_NRT_V6/RSS_SMAP_SSS_L2C_r47566_20231227T214701_2023361_NRT_V06.0_001.nc", "filename": "RSS_SMAP_SSS_L2C_r47566_20231227T214701_2023361_NRT_V06.0_001.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"GFED4_Emission_Factors.csv": {"collection": "fire_emissions_v4_R1_1293", "version": "4.1", "direct_link": "s3://ornl-cumulus-prod-protected/global_vegetation/fire_emissions_v4_R1/data/GFED4_Emission_Factors.csv", "filename": "GFED4_Emission_Factors.csv", "data_center": "ORNLDAAC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"S6A_P4_2__HR_STD__ST_038_241_20211128T220816_20211128T230429_F04.nc": {"collection": "JASON_CS_S6A_L2_ALT_HR_STD_OST_STC_F", "version": "F", "direct_link": "s3://podaac-ops-cumulus-protected/JASON_CS_S6A_L2_ALT_HR_STD_OST_STC_F/S6A_P4_2__HR_STD__ST_038_241_20211128T220816_20211128T230429_F04.nc", "filename": "S6A_P4_2__HR_STD__ST_038_241_20211128T220816_20211128T230429_F04.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"landmet_L3_19980101_v1.nc": {"collection": "LANDMET", "version": "1", "direct_link": "s3://gesdisc-cumulus-prod-protected/LANDMET/LANDMET.1/1998/landmet_L3_19980101_v1.nc", "filename": "landmet_L3_19980101_v1.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"GOZ-Merged-MLP_N2O_ev1-01_2004.nc4": {"collection": "GozMmlpN2O", "version": "1", "direct_link": "s3://gesdisc-cumulus-prod-protected/GOZCARDS/GozMmlpN2O.1/GOZ-Merged-MLP_N2O_ev1-01_2004.nc4", "filename": "GOZ-Merged-MLP_N2O_ev1-01_2004.nc4", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"MERRA2_100.tavgM_3d_mst_Np.198001.nc4": {"collection": "M2TMNPMST", "version": "5.12.4", "direct_link": "s3://gesdisc-cumulus-prod-protected/MERRA2_MONTHLY/M2TMNPMST.5.12.4/1980/MERRA2_100.tavgM_3d_mst_Np.198001.nc4", "filename": "MERRA2_100.tavgM_3d_mst_Np.198001.nc4", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"MLS-Aura_L1BRADG_v05-01-c01_2004d215.h5": {"collection": "ML1RADG", "version": "005", "direct_link": "s3://gesdisc-cumulus-prod-protected/Aura_MLS_Level1/ML1RADG.005/2004/MLS-Aura_L1BRADG_v05-01-c01_2004d215.h5", "filename": "MLS-Aura_L1BRADG_v05-01-c01_2004d215.h5", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, "Caught exception An error occurred (403) when calling the HeadObject operation: Forbidden while trying to process file from collection SWOT_L2_RAD_GDR_2.0, version 2.0", {"L4BNEE_2012-01_v1.nc4": {"collection": "AirMOSS_L4_Regional_NEE_1423", "version": "1", "direct_link": "s3://ornl-cumulus-prod-protected/airmoss/campaign/AirMOSS_L4_Regional_NEE/data/L4BNEE_2012-01_v1.nc4", "filename": "L4BNEE_2012-01_v1.nc4", "data_center": "ORNLDAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"GEOSCarb_CASAGFED3v3_Fire.Daily.x720_y360.2003.nc": {"collection": "GEOS_CASAGFED_D_FIRE", "version": "3", "direct_link": "s3://gesdisc-cumulus-prod-protected/CMS/GEOS_CASAGFED_D_FIRE.3/GEOSCarb_CASAGFED3v3_Fire.Daily.x720_y360.2003.nc", "filename": "GEOSCarb_CASAGFED3v3_Fire.Daily.x720_y360.2003.nc", "data_center": "GES_DISC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"LPRM-WINDSAT_L3_DY_SOILM3_V001_20030201012753.nc": {"collection": "LPRM_WINDSAT_DY_SOILM3", "version": "001", "direct_link": "s3://gesdisc-cumulus-prod-protected/WAOB/LPRM_WINDSAT_DY_SOILM3.001/2003/02/LPRM-WINDSAT_L3_DY_SOILM3_V001_20030201012753.nc", "filename": "LPRM-WINDSAT_L3_DY_SOILM3_V001_20030201012753.nc", "data_center": "GES_DISC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"MYD21C3.A2002182.061.2020112123747.hdf": {"collection": "MYD21C3", "version": "061", "direct_link": "s3://lp-prod-protected/MYD21C3.061/MYD21C3.A2002182.061.2020112123747/MYD21C3.A2002182.061.2020112123747.hdf", "filename": "MYD21C3.A2002182.061.2020112123747.hdf", "data_center": "LPDAAC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"MERRA2_100.tavg3_3d_cld_Nv.19800101.nc4": {"collection": "M2T3NVCLD", "version": "5.12.4", "direct_link": "s3://gesdisc-cumulus-prod-protected/MERRA2/M2T3NVCLD.5.12.4/1980/01/MERRA2_100.tavg3_3d_cld_Nv.19800101.nc4", "filename": "MERRA2_100.tavg3_3d_cld_Nv.19800101.nc4", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"TROPESS_CrIS-SNPP_L2_Summary_NH3_20160102_MUSES_R1p12_SC_MGLOS_F0p6.nc": {"collection": "TRPSYL2ALLCRSMGLOS", "version": "1", "direct_link": "s3://gesdisc-cumulus-prod-protected/TROPESS_MegaCities_Summary/TRPSYL2ALLCRSMGLOS.1/2016/TROPESS_CrIS-SNPP_L2_Summary_NH3_20160102_MUSES_R1p12_SC_MGLOS_F0p6.nc", "filename": "TROPESS_CrIS-SNPP_L2_Summary_NH3_20160102_MUSES_R1p12_SC_MGLOS_F0p6.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"MLS-Aura_L2GP-DGG_v05-01-c01_2004d215.he5": {"collection": "ML2DGG", "version": "005", "direct_link": "s3://gesdisc-cumulus-prod-protected/Aura_MLS_Level2/ML2DGG.005/2004/MLS-Aura_L2GP-DGG_v05-01-c01_2004d215.he5", "filename": "MLS-Aura_L2GP-DGG_v05-01-c01_2004d215.he5", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"S6A_P4_2__LR_STD__NR_022_215_20210622T065556_20210622T085149_F02.nc": {"collection": "JASON_CS_S6A_L2_ALT_LR_STD_OST_NRT_F", "version": "F", "direct_link": "s3://podaac-ops-cumulus-protected/JASON_CS_S6A_L2_ALT_LR_STD_OST_NRT_F/S6A_P4_2__LR_STD__NR_022_215_20210622T065556_20210622T085149_F02.nc", "filename": "S6A_P4_2__LR_STD__NR_022_215_20210622T065556_20210622T085149_F02.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"20140602000000-OSPO-L4_GHRSST-SSTfnd-Geo_Polar_Blended-GLOB-v02.0-fv01.0.nc": {"collection": "Geo_Polar_Blended-OSPO-L4-GLOB-v1.0", "version": "1.0", "direct_link": "s3://podaac-ops-cumulus-protected/Geo_Polar_Blended-OSPO-L4-GLOB-v1.0/20140602000000-OSPO-L4_GHRSST-SSTfnd-Geo_Polar_Blended-GLOB-v02.0-fv01.0.nc", "filename": "20140602000000-OSPO-L4_GHRSST-SSTfnd-Geo_Polar_Blended-GLOB-v02.0-fv01.0.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"oco2_L2DiaND_00958a_140906_B10004r_200103151559.h5": {"collection": "OCO2_L2_Diagnostic", "version": "10r", "direct_link": "s3://gesdisc-cumulus-prod-protected/OCO2_DATA/OCO2_L2_Diagnostic.10r/2014/249/oco2_L2DiaND_00958a_140906_B10004r_200103151559.h5", "filename": "oco2_L2DiaND_00958a_140906_B10004r_200103151559.h5", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"CMS_Flux_FossilFuelPrior_2010_v2.nc": {"collection": "CMSFluxFossilFuelPrior", "version": "2", "direct_link": "s3://gesdisc-cumulus-prod-protected/CMS/CMSFluxFossilFuelPrior.2/CMS_Flux_FossilFuelPrior_2010_v2.nc", "filename": "CMS_Flux_FossilFuelPrior_2010_v2.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"GOZ-Source-MLP_N2O_ev1-01_2004.nc4": {"collection": "GozSmlpN2O", "version": "1", "direct_link": "s3://gesdisc-cumulus-prod-protected/GOZCARDS/GozSmlpN2O.1/GOZ-Source-MLP_N2O_ev1-01_2004.nc4", "filename": "GOZ-Source-MLP_N2O_ev1-01_2004.nc4", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"MODIS_CR.EqualAngle_daily.C61.V1.0.L3.2003.nc4": {"collection": "MODIS_CR_Equal_Angle_Daily", "version": "1.0", "direct_link": "s3://gesdisc-cumulus-prod-protected/CloudRegimes/MODIS_CR_Equal_Angle_Daily.1.0/MODIS_CR.EqualAngle_daily.C61.V1.0.L3.2003.nc4", "filename": "MODIS_CR.EqualAngle_daily.C61.V1.0.L3.2003.nc4", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"MCD18C1.A2000055.061.2020070171616.hdf": {"collection": "MCD18C1", "version": "061", "direct_link": "s3://lp-prod-protected/MCD18C1.061/MCD18C1.A2000055.061.2020070171616/MCD18C1.A2000055.061.2020070171616.hdf", "filename": "MCD18C1.A2000055.061.2020070171616.hdf", "data_center": "LPDAAC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"SNDR.SS1330.CHIRP.20151102T1606.m06.g162.L1_SN_CAL.std.v02_48.G.200323151311.nc": {"collection": "SNDR13CHRP1SNCal", "version": "2", "direct_link": "s3://gesdisc-cumulus-prod-protected/CHIRP/SNDR13CHRP1SNCal.2/2015/306/SNDR.SS1330.CHIRP.20151102T1606.m06.g162.L1_SN_CAL.std.v02_48.G.200323151311.nc", "filename": "SNDR.SS1330.CHIRP.20151102T1606.m06.g162.L1_SN_CAL.std.v02_48.G.200323151311.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"ARMCAS1995-car_C131A_19950605001435_R1_CAR1677_Level1D-20190526.nc": {"collection": "CAR_ARMCAS_BRDF", "version": "2", "direct_link": "s3://gesdisc-cumulus-prod-protected/CAR/CAR_ARMCAS_BRDF.2/1995/ARMCAS1995-car_C131A_19950605001435_R1_CAR1677_Level1D-20190526.nc", "filename": "ARMCAS1995-car_C131A_19950605001435_R1_CAR1677_Level1D-20190526.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"1C.GPM.GMI.XCAL2016-C.20140304-S175932-E193159.000079.V07A.HDF5": {"collection": "GPM_1CGPMGMI", "version": "07", "direct_link": "s3://gesdisc-cumulus-prod-protected/GPM_L1C/GPM_1CGPMGMI.07/2014/063/1C.GPM.GMI.XCAL2016-C.20140304-S175932-E193159.000079.V07A.HDF5", "filename": "1C.GPM.GMI.XCAL2016-C.20140304-S175932-E193159.000079.V07A.HDF5", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, "Caught exception An error occurred (403) when calling the HeadObject operation: Forbidden while trying to process file from collection SWOT_L2_RAD_OGDR_1.0, version 1.0", {"TROPESS_CrIS-SNPP_L2_Standard_H2O_20160103_MUSES_R1p12_SC_MGLAG_F0p6.nc": {"collection": "TRPSDL2ALLCRSMGLAG", "version": "1", "direct_link": "s3://gesdisc-cumulus-prod-protected/TROPESS_MegaCities_Standard/TRPSDL2ALLCRSMGLAG.1/2016/TROPESS_CrIS-SNPP_L2_Standard_H2O_20160103_MUSES_R1p12_SC_MGLAG_F0p6.nc", "filename": "TROPESS_CrIS-SNPP_L2_Standard_H2O_20160103_MUSES_R1p12_SC_MGLAG_F0p6.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"NSIFv2.6.1.19950701_v2.9.1_all.nc": {"collection": "ERS2_GOME_SIF_1758", "version": "1", "direct_link": "s3://ornl-cumulus-prod-protected/sif-esdr/17-MEASURES-0032/ERS2_GOME_SIF/data/NSIFv2.6.1.19950701_v2.9.1_all.nc", "filename": "NSIFv2.6.1.19950701_v2.9.1_all.nc", "data_center": "ORNLDAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"MODIS_CR.EqualArea_3h.C61.V1.0.L3.2003.nc4": {"collection": "MODIS_CR_Equal_Area_3h", "version": "1.0", "direct_link": "s3://gesdisc-cumulus-prod-protected/CloudRegimes/MODIS_CR_Equal_Area_3h.1.0/MODIS_CR.EqualArea_3h.C61.V1.0.L3.2003.nc4", "filename": "MODIS_CR.EqualArea_3h.C61.V1.0.L3.2003.nc4", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"S6A_P4_2__LR_RED__NR_022_215_20210622T065556_20210622T085149_F02.nc": {"collection": "JASON_CS_S6A_L2_ALT_LR_RED_OST_NRT_F", "version": "F", "direct_link": "s3://podaac-ops-cumulus-protected/JASON_CS_S6A_L2_ALT_LR_RED_OST_NRT_F/S6A_P4_2__LR_RED__NR_022_215_20210622T065556_20210622T085149_F02.nc", "filename": "S6A_P4_2__LR_RED__NR_022_215_20210622T065556_20210622T085149_F02.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"PRIM_20150331_r01.nc": {"collection": "PRIM_SMAP_L2_V1", "version": "1.0", "direct_link": "s3://podaac-ops-cumulus-protected/PRIM_SMAP_L2_V1/PRIM_20150331_r01.nc", "filename": "PRIM_20150331_r01.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"20181204000000-STAR-L2P_GHRSST-SSTsubskin-AVHRRF_MC-ACSPO_V2.80-v02.0-fv01.0.nc": {"collection": "AVHRRF_MC-STAR-L2P-v2.80", "version": "2.80", "direct_link": "s3://podaac-ops-cumulus-protected/AVHRRF_MC-STAR-L2P-v2.80/2018/338/20181204000000-STAR-L2P_GHRSST-SSTsubskin-AVHRRF_MC-ACSPO_V2.80-v02.0-fv01.0.nc", "filename": "20181204000000-STAR-L2P_GHRSST-SSTsubskin-AVHRRF_MC-ACSPO_V2.80-v02.0-fv01.0.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"S6A_P4_2__HR_STD__NR_038_241_20211128T225521_20211128T230521_F04.nc": {"collection": "JASON_CS_S6A_L2_ALT_HR_STD_OST_NRT_F", "version": "F", "direct_link": "s3://podaac-ops-cumulus-protected/JASON_CS_S6A_L2_ALT_HR_STD_OST_NRT_F/S6A_P4_2__HR_STD__NR_038_241_20211128T225521_20211128T230521_F04.nc", "filename": "S6A_P4_2__HR_STD__NR_038_241_20211128T225521_20211128T230521_F04.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"GRD-3_2018152-2018181_GRFO_JPLEM_BA01_0601_LND_v04.nc": {"collection": "TELLUS_GRFO_L3_JPL_RL06.1_LND_v04", "version": "RL06.1v04", "direct_link": "s3://podaac-ops-cumulus-protected/TELLUS_GRFO_L3_JPL_RL06.1_LND_v04/GRD-3_2018152-2018181_GRFO_JPLEM_BA01_0601_LND_v04.nc", "filename": "GRD-3_2018152-2018181_GRFO_JPLEM_BA01_0601_LND_v04.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"GSSTFM_NCEP.3.1987.07.01.he5": {"collection": "GSSTFM_NCEP", "version": "3", "direct_link": "s3://gesdisc-cumulus-prod-protected/GSSTF/GSSTFM_NCEP.3/1987/GSSTFM_NCEP.3.1987.07.01.he5", "filename": "GSSTFM_NCEP.3.1987.07.01.he5", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"MLS-Aura_L3DB-CH3Cl_v05-01-c06_2004d215.nc": {"collection": "ML3DBCH3CL", "version": "005", "direct_link": "s3://gesdisc-cumulus-prod-protected/Aura_MLS_Level3/ML3DBCH3CL.005/2004/MLS-Aura_L3DB-CH3Cl_v05-01-c06_2004d215.nc", "filename": "MLS-Aura_L3DB-CH3Cl_v05-01-c06_2004d215.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"NLDAS_VIC0125_MC.ACLIM01.020.nc": {"collection": "NLDAS_VIC0125_MC", "version": "2.0", "direct_link": "s3://gesdisc-cumulus-prod-protected/NLDAS/NLDAS_VIC0125_MC.2.0/NLDAS_VIC0125_MC.ACLIM01.020.nc", "filename": "NLDAS_VIC0125_MC.ACLIM01.020.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"S6A_MW_2__AMR_____NR_022_215_20210622T065557_20210622T085150_F02.nc": {"collection": "JASON_CS_S6A_L2_AMR_RAD_NRT", "version": "F", "direct_link": "s3://podaac-ops-cumulus-protected/JASON_CS_S6A_L2_AMR_RAD_NRT/S6A_MW_2__AMR_____NR_022_215_20210622T065557_20210622T085150_F02.nc", "filename": "S6A_MW_2__AMR_____NR_022_215_20210622T065557_20210622T085150_F02.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, "Caught exception An error occurred (403) when calling the HeadObject operation: Forbidden while trying to process file from collection SWOT_L2_RAD_IGDR_1.0, version 1.0", {"stnxvalmeta_prcp_pr_1950.txt": {"collection": "Daymet_xval_V4R1_2132", "version": "4.5", "direct_link": "s3://ornl-cumulus-prod-protected/daymet/Daymet_xval_V4R1/data/stnxvalmeta_prcp_pr_1950.txt", "filename": "stnxvalmeta_prcp_pr_1950.txt", "data_center": "ORNLDAAC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"OMPS-NPP_LP-L2-O3-DAILY_v2.6_2012m0207_2023m0207t124509.h5": {"collection": "OMPS_NPP_LP_L2_O3_DAILY", "version": "2.6", "direct_link": "s3://gesdisc-cumulus-prod-protected/SNPP_OMPS_Level2/OMPS_NPP_LP_L2_O3_DAILY.2.6/2012/OMPS-NPP_LP-L2-O3-DAILY_v2.6_2012m0207_2023m0207t124509.h5", "filename": "OMPS-NPP_LP-L2-O3-DAILY_v2.6_2012m0207_2023m0207t124509.h5", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"BLWV_D_V02.00_2002d185.nc4": {"collection": "AMDBLWV", "version": "2", "direct_link": "s3://gesdisc-cumulus-prod-protected/BLWV/AMDBLWV.2/2002/BLWV_D_V02.00_2002d185.nc4", "filename": "BLWV_D_V02.00_2002d185.nc4", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"3B-ORBIT.GPM.DPRGMI.3GCSHv7-0.20140308-S220950-E234217.000144.V07A.HDF5": {"collection": "GPM_3GCSH", "version": "07", "direct_link": "s3://gesdisc-cumulus-prod-protected/GPM_L3/GPM_3GCSH.07/2014/03/3B-ORBIT.GPM.DPRGMI.3GCSHv7-0.20140308-S220950-E234217.000144.V07A.HDF5", "filename": "3B-ORBIT.GPM.DPRGMI.3GCSHv7-0.20140308-S220950-E234217.000144.V07A.HDF5", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"S6A_MW_2__AMR_____ST_036_214_20211108T005326_20211108T014938_F03.nc": {"collection": "JASON_CS_S6A_L2_AMR_RAD_STC", "version": "F", "direct_link": "s3://podaac-ops-cumulus-protected/JASON_CS_S6A_L2_AMR_RAD_STC/S6A_MW_2__AMR_____ST_036_214_20211108T005326_20211108T014938_F03.nc", "filename": "S6A_MW_2__AMR_____ST_036_214_20211108T005326_20211108T014938_F03.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"MERRA2_100.tavg3_3d_rad_Np.19800101.nc4": {"collection": "M2T3NPRAD", 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{"TROPESS_CrIS-SNPP_L2_Standard_NH3_20191101_MUSES_R1p9_SC_AUS_F0p1.nc": {"collection": "TRPSDL2NH3CRSAUS", "version": "1", "direct_link": "s3://gesdisc-cumulus-prod-protected/TROPESS_Special/TRPSDL2NH3CRSAUS.1/2019/TROPESS_CrIS-SNPP_L2_Standard_NH3_20191101_MUSES_R1p9_SC_AUS_F0p1.nc", "filename": "TROPESS_CrIS-SNPP_L2_Standard_NH3_20191101_MUSES_R1p9_SC_AUS_F0p1.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"L4RZSM_Walnut_20120921_v5.nc4": {"collection": "AirMOSS_L4_RZ_Soil_Moisture_1421", "version": "1", "direct_link": "s3://ornl-cumulus-prod-protected/airmoss/campaign/AirMOSS_L4_RZ_Soil_Moisture/data/L4RZSM_Walnut_20120921_v5.nc4", "filename": "L4RZSM_Walnut_20120921_v5.nc4", "data_center": "ORNLDAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"2A-CLIM.F18.SSMIS.GPROF2021v1.20100308-S003216-E021415.001982.V07A.HDF5": {"collection": "GPM_2AGPROFF18SSMIS_CLIM", "version": "07", "direct_link": 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"s3://lp-prod-protected/MCD19A1CMGL.061/MCD19A1CMGL.A2000055.061.2022315175328/MCD19A1CMGL.A2000055.061.2022315175328.hdf", "filename": "MCD19A1CMGL.A2000055.061.2022315175328.hdf", "data_center": "LPDAAC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"19980101120000-REMSS-L4_GHRSST-SSTfnd-MW_OI-GLOB-v02.0-fv05.0.nc": {"collection": "MW_OI-REMSS-L4-GLOB-v5.0", "version": "5.0", "direct_link": "s3://podaac-ops-cumulus-protected/MW_OI-REMSS-L4-GLOB-v5.0/19980101120000-REMSS-L4_GHRSST-SSTfnd-MW_OI-GLOB-v02.0-fv05.0.nc", "filename": "19980101120000-REMSS-L4_GHRSST-SSTfnd-MW_OI-GLOB-v02.0-fv05.0.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"OMI-Aura_L2-OMCLDO2Z_2004m1006t0656-o01209_v003-2011m0906t130009.he5": {"collection": "OMCLDO2Z", "version": "003", "direct_link": "s3://gesdisc-cumulus-prod-protected/Aura_OMI_Level2/OMCLDO2Z.003/2004/280/OMI-Aura_L2-OMCLDO2Z_2004m1006t0656-o01209_v003-2011m0906t130009.he5", "filename": "OMI-Aura_L2-OMCLDO2Z_2004m1006t0656-o01209_v003-2011m0906t130009.he5", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"OMI-Aura_L1-OML1BRVZ_2004m1006t0656-o001209_v0401-2022m0615t1331.nc": {"collection": "OML1BRVZ", "version": "004", "direct_link": "s3://gesdisc-cumulus-prod-protected/Aura_OMI_Level1/OML1BRVZ.004/2004/280/OMI-Aura_L1-OML1BRVZ_2004m1006t0656-o001209_v0401-2022m0615t1331.nc", "filename": "OMI-Aura_L1-OML1BRVZ_2004m1006t0656-o001209_v0401-2022m0615t1331.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"OMPS-NPP_NMSO2-L2_2012m0126t215217_o01285_2017m0517t103813.h5": {"collection": "OMPS_NPP_NMSO2_L2", "version": "2", "direct_link": "s3://gesdisc-cumulus-prod-protected/SNPP_OMPS_Level2/OMPS_NPP_NMSO2_L2.2/2012/026/OMPS-NPP_NMSO2-L2_2012m0126t215217_o01285_2017m0517t103813.h5", "filename": "OMPS-NPP_NMSO2-L2_2012m0126t215217_o01285_2017m0517t103813.h5", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"cyg.ddmi.s20180801-003000-e20180801-233000.l3.grid-wind.a31.d32.nc": {"collection": "CYGNSS_L3_V3.1", "version": "3.1", "direct_link": "s3://podaac-ops-cumulus-protected/CYGNSS_L3_V3.1/cyg.ddmi.s20180801-003000-e20180801-233000.l3.grid-wind.a31.d32.nc", "filename": "cyg.ddmi.s20180801-003000-e20180801-233000.l3.grid-wind.a31.d32.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"S6A_P4_2__HR_STD__NT_084_001_20230218T160856_20230218T170509_F08.nc": {"collection": "JASON_CS_S6A_L2_ALT_HR_STD_OST_NTC_F08", "version": "F08", "direct_link": "s3://podaac-ops-cumulus-protected/JASON_CS_S6A_L2_ALT_HR_STD_OST_NTC_F08/S6A_P4_2__HR_STD__NT_084_001_20230218T160856_20230218T170509_F08.nc", "filename": "S6A_P4_2__HR_STD__NT_084_001_20230218T160856_20230218T170509_F08.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"MERRA2.tavgC_2d_ltm_Nx.v2_0.199101_202001.nc4": {"collection": "M2TCNXLTM", "version": "2", "direct_link": "s3://gesdisc-cumulus-prod-protected/MERRA2_CLIM/M2TCNXLTM.2/1991/MERRA2.tavgC_2d_ltm_Nx.v2_0.199101_202001.nc4", "filename": "MERRA2.tavgC_2d_ltm_Nx.v2_0.199101_202001.nc4", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"MLS-Aura_L3DZ-CH3Cl_v04-23-c02_2004.nc": {"collection": "ML3DZCH3CL", "version": "004", "direct_link": "s3://gesdisc-cumulus-prod-protected/Aura_MLS_Level3/ML3DZCH3CL.004/2004/MLS-Aura_L3DZ-CH3Cl_v04-23-c02_2004.nc", "filename": "MLS-Aura_L3DZ-CH3Cl_v04-23-c02_2004.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"MYD11B1.A2002185.h24v15.061.2020128175028.hdf": {"collection": "MYD11B1", "version": "061", "direct_link": "s3://lp-prod-protected/MYD11B1.061/MYD11B1.A2002185.h24v15.061.2020128175028/MYD11B1.A2002185.h24v15.061.2020128175028.hdf", "filename": "MYD11B1.A2002185.h24v15.061.2020128175028.hdf", "data_center": "LPDAAC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"NCALDAS_NOAH0125_Trends.A198010_201509.002.nc": {"collection": "NCALDAS_NOAH0125_Trends", "version": "2.0", "direct_link": "s3://gesdisc-cumulus-prod-protected/NCALDAS/NCALDAS_NOAH0125_Trends.2.0/NCALDAS_NOAH0125_Trends.A198010_201509.002.nc", "filename": "NCALDAS_NOAH0125_Trends.A198010_201509.002.nc", "data_center": "GES_DISC", "fsm_strategy": "Not found", "page_size": "Not found"}}, "Caught exception 'accessKeyId' while trying to process file from collection TEMPO_RAD_L1, version V02", {"CMS_Lake_Superior_PP_Yearly_2010-2013.nc": {"collection": "CMSLakeSuperiorPPY", "version": "1", "direct_link": "s3://gesdisc-cumulus-prod-protected/CMS/CMSLakeSuperiorPPY.1/CMS_Lake_Superior_PP_Yearly_2010-2013.nc", "filename": "CMS_Lake_Superior_PP_Yearly_2010-2013.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"MOD28C2.A2000057.061.2021071112856.hdf": {"collection": "MOD28C2", "version": "061", "direct_link": "s3://lp-prod-protected/MOD28C2.061/MOD28C2.A2000057.061.2021071112856/MOD28C2.A2000057.061.2021071112856.hdf", "filename": "MOD28C2.A2000057.061.2021071112856.hdf", "data_center": "LPDAAC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"midwest_par_2018.nc": {"collection": "SIF_PAR_fPAR_US_Midwest_2018_1813", "version": "1", "direct_link": "s3://ornl-cumulus-prod-protected/cms/SIF_PAR_fPAR_US_Midwest_2018/data/midwest_par_2018.nc", "filename": "midwest_par_2018.nc", "data_center": "ORNLDAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, "Caught exception An error occurred (403) when calling the HeadObject operation: Forbidden while trying to process file from collection SWOT_L2_HR_PIXCVec_1.1, version 1.1", {"GRD-3_2018152-2018181_GRFO_UTCSR_BA01_0601_LND_v04.nc": {"collection": "TELLUS_GRFO_L3_CSR_RL06.1_LND_v04", "version": "RL06.1v04", "direct_link": "s3://podaac-ops-cumulus-protected/TELLUS_GRFO_L3_CSR_RL06.1_LND_v04/GRD-3_2018152-2018181_GRFO_UTCSR_BA01_0601_LND_v04.nc", "filename": "GRD-3_2018152-2018181_GRFO_UTCSR_BA01_0601_LND_v04.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"lis_vhrfc_1998_2013_v01.nc.gz": {"collection": "lisvhrfc", "version": "1", "direct_link": "s3://ghrcw-protected/lisvhrfc__1/lis_vhrfc_1998_2013_v01.nc.gz", "filename": "lis_vhrfc_1998_2013_v01.nc.gz", "data_center": "GHRCDAAC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"ACTAmerica-MFLL-lev2_C130_2016-05-27T145325_R2.nc": {"collection": "ACTAMERICA_MFFLL_1649", "version": "1.1", "direct_link": "s3://ornl-cumulus-prod-protected/actamerica/ACTAMERICA_MFFLL/data/summer2016/ACTAmerica-MFLL-lev2_C130_2016-05-27T145325_R2.nc", "filename": "ACTAmerica-MFLL-lev2_C130_2016-05-27T145325_R2.nc", "data_center": "ORNLDAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"ATL04_20181014000347_02350101_006_02.h5": {"collection": "ATL04", "version": "006", "direct_link": "s3://nsidc-cumulus-prod-protected/ATLAS/ATL04/006/2018/10/14/ATL04_20181014000347_02350101_006_02.h5", "filename": "ATL04_20181014000347_02350101_006_02.h5", "data_center": "NSIDC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"CLM-FUTURE-SHALLOW_Monthly.nc": {"collection": "Alaskan_CO2_Flux_1325", "version": "1.1", "direct_link": "s3://ornl-cumulus-prod-protected/carve/Alaskan_CO2_Flux/data/CLM-FUTURE-SHALLOW_Monthly.nc", "filename": "CLM-FUTURE-SHALLOW_Monthly.nc", "data_center": "ORNLDAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"DiscoverAQ2014-car_p3b_20140708180026_R1_CAR2037_Level1D.v2-20190127.nc": {"collection": "CAR_DISCOVERAQ_BRDF", "version": "2", "direct_link": "s3://gesdisc-cumulus-prod-protected/CAR/CAR_DISCOVERAQ_BRDF.2/2014/DiscoverAQ2014-car_p3b_20140708180026_R1_CAR2037_Level1D.v2-20190127.nc", "filename": "DiscoverAQ2014-car_p3b_20140708180026_R1_CAR2037_Level1D.v2-20190127.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"LEADEX1992-car_c131A_19920414225533_R1_CAR1544_Level1D-20190407.nc": {"collection": "CAR_LEADEX_BRDF", "version": "2", "direct_link": "s3://gesdisc-cumulus-prod-protected/CAR/CAR_LEADEX_BRDF.2/1992/LEADEX1992-car_c131A_19920414225533_R1_CAR1544_Level1D-20190407.nc", "filename": "LEADEX1992-car_c131A_19920414225533_R1_CAR1544_Level1D-20190407.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"sabgom_output_2005_rho.nc4": {"collection": "CMS_SABGOM_Model_Simulations_1510", "version": "1", "direct_link": "s3://ornl-cumulus-prod-protected/cms/CMS_SABGOM_Model_Simulations/data/sabgom_output_2005_rho.nc4", "filename": "sabgom_output_2005_rho.nc4", "data_center": "ORNLDAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"historical_global_1-degree_forest_biomass.nc4": {"collection": "Global_Biomass_1950-2010_1296", "version": "1", "direct_link": "s3://ornl-cumulus-prod-protected/global_vegetation/Global_Biomass_1950-2010/data/historical_global_1-degree_forest_biomass.nc4", "filename": "historical_global_1-degree_forest_biomass.nc4", "data_center": "ORNLDAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"20020704120000-STAR-L3S_GHRSST-SSTsubskin-LEO_PM_N-ACSPO_V2.81-v02.0-fv01.0.nc": {"collection": "L3S_LEO_PM-STAR-v2.81", "version": "2.81", "direct_link": "s3://podaac-ops-cumulus-protected/L3S_LEO_PM-STAR-v2.81/20020704120000-STAR-L3S_GHRSST-SSTsubskin-LEO_PM_N-ACSPO_V2.81-v02.0-fv01.0.nc", "filename": "20020704120000-STAR-L3S_GHRSST-SSTsubskin-LEO_PM_N-ACSPO_V2.81-v02.0-fv01.0.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"MLS-Aura_L3MB-HOCl_v05-01-c06_2004.nc": {"collection": "ML3MBHOCL", "version": "005", "direct_link": "s3://gesdisc-cumulus-prod-protected/Aura_MLS_Level3/ML3MBHOCL.005/2004/MLS-Aura_L3MB-HOCl_v05-01-c06_2004.nc", "filename": "MLS-Aura_L3MB-HOCl_v05-01-c06_2004.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"WetCHARTs_v1_3_1_2011.nc": {"collection": "MonthlyWetland_CH4_WetCHARTs_1915", "version": "1.3.1.1", "direct_link": "s3://ornl-cumulus-prod-protected/cms/MonthlyWetland_CH4_WetCHARTs/data/WetCHARTs_v1_3_1_2011.nc", "filename": "WetCHARTs_v1_3_1_2011.nc", "data_center": "ORNLDAAC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"OMG_Bathy_MBES_L2_20150725000000.nc": {"collection": "OMG_L2_Bathy_MBES_Gridded", "version": "1", "direct_link": "s3://podaac-ops-cumulus-protected/OMG_L2_Bathy_MBES_Gridded/OMG_Bathy_MBES_L2_20150725000000.nc", "filename": "OMG_Bathy_MBES_L2_20150725000000.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"S5P_RPRO_L2__AER_LH_20180430T001851_20180430T020219_02818_01_010301_20190513T141137.nc": {"collection": "S5P_L2__AER_LH", "version": "1", "direct_link": "s3://gesdisc-cumulus-prod-protected/S5P_TROPOMI_Level2/S5P_L2__AER_LH.1/2018/120/S5P_RPRO_L2__AER_LH_20180430T001851_20180430T020219_02818_01_010301_20190513T141137.nc", "filename": "S5P_RPRO_L2__AER_LH_20180430T001851_20180430T020219_02818_01_010301_20190513T141137.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"Eco3D2011-car_p3b_20110822175912_R1_CAR2025_Level1D.v2-20190127.nc": {"collection": "CAR_ECO3D_BRDF", "version": "2", "direct_link": "s3://gesdisc-cumulus-prod-protected/CAR/CAR_ECO3D_BRDF.2/2011/Eco3D2011-car_p3b_20110822175912_R1_CAR2025_Level1D.v2-20190127.nc", "filename": "Eco3D2011-car_p3b_20110822175912_R1_CAR2025_Level1D.v2-20190127.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"Global_Fuel_Exploitation_Inventory_GFEI_CH4_v1_2016.nc": {"collection": "GFEI_CH4", "version": "1", "direct_link": "s3://gesdisc-cumulus-prod-protected/CMS/GFEI_CH4.1/Global_Fuel_Exploitation_Inventory_GFEI_CH4_v1_2016.nc", "filename": "Global_Fuel_Exploitation_Inventory_GFEI_CH4_v1_2016.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"global_sla_l2p_ntc_s6a_hr_C0083_P0009_20230209T014008_20230209T022812_20230323T111815.nc": {"collection": "JASON_CS_S6A_L2P_ALT_HR_OST_NTC_F08", "version": "F08", "direct_link": "s3://podaac-ops-cumulus-protected/JASON_CS_S6A_L2P_ALT_HR_OST_NTC_F08/global_sla_l2p_ntc_s6a_hr_C0083_P0009_20230209T014008_20230209T022812_20230323T111815.nc", "filename": "global_sla_l2p_ntc_s6a_hr_C0083_P0009_20230209T014008_20230209T022812_20230323T111815.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"S6A_P4_2__HR_STD__NT_004_013_20201217T212131_20201217T221743_F08_unvalidated.nc": {"collection": "JASON_CS_S6A_L2_ALT_HR_STD_OST_NTC_F08_UNVALIDATED", "version": "F08", "direct_link": "s3://podaac-ops-cumulus-protected/JASON_CS_S6A_L2_ALT_HR_STD_OST_NTC_F08_UNVALIDATED/S6A_P4_2__HR_STD__NT_004_013_20201217T212131_20201217T221743_F08_unvalidated.nc", "filename": "S6A_P4_2__HR_STD__NT_004_013_20201217T212131_20201217T221743_F08_unvalidated.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, "Caught exception An error occurred (403) when calling the HeadObject operation: Forbidden while trying to process file from collection SWOT_L2_HR_PIXCVec_2.0, version 2.0", {"TROPESS_CrIS-JPSS1_L2_Standard_TATM_20210401_MUSES_R1p12_FS_F0p1.nc": {"collection": "TRPSDL2TATMCRS1FS", "version": "1", "direct_link": "s3://gesdisc-cumulus-prod-protected/TROPESS_Standard/TRPSDL2TATMCRS1FS.1/2021/TROPESS_CrIS-JPSS1_L2_Standard_TATM_20210401_MUSES_R1p12_FS_F0p1.nc", "filename": "TROPESS_CrIS-JPSS1_L2_Standard_TATM_20210401_MUSES_R1p12_FS_F0p1.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"VNP09H1.A2012017.h02v11.002.2024106202816.h5": {"collection": "VNP09H1", "version": "002", "direct_link": "s3://lp-prod-protected/VNP09H1.002/VNP09H1.A2012017.h02v11.002.2024106202816/VNP09H1.A2012017.h02v11.002.2024106202816.h5", "filename": "VNP09H1.A2012017.h02v11.002.2024106202816.h5", "data_center": "LPDAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"L1C-CS-OLYMPEX.GPM.GMI.XCAL2015-C.20151101-S012615-E012745.009512.V04A.HDF5": {"collection": "gpmopassolyx", "version": "4", "direct_link": 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{"MOD28C3.A2000061.061.2022044072810.hdf": {"collection": "MOD28C3", "version": "061", "direct_link": "s3://lp-prod-protected/MOD28C3.061/MOD28C3.A2000061.061.2022044072810/MOD28C3.A2000061.061.2022044072810.hdf", "filename": "MOD28C3.A2000061.061.2022044072810.hdf", "data_center": "LPDAAC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"MSLERLSTL3d10_v01-02-2013m0701t213228.he5": {"collection": "MSLERLSTL3d10", "version": "1", "direct_link": "s3://gesdisc-cumulus-prod-protected/LER/MSLERLSTL3d10.1/MSLERLSTL3d10_v01-02-2013m0701t213228.he5", "filename": "MSLERLSTL3d10_v01-02-2013m0701t213228.he5", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"MSO3L3zm5_v01-02-2013m0907t142428.h5": {"collection": "MSO3L3zm5", "version": "1", "direct_link": "s3://gesdisc-cumulus-prod-protected/Ozone/MSO3L3zm5.1/MSO3L3zm5_v01-02-2013m0907t142428.h5", "filename": "MSO3L3zm5_v01-02-2013m0907t142428.h5", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"surface_temperature_monthly.nc4": {"collection": "Monthly_Hydrological_Fluxes_1647", "version": "1", "direct_link": "s3://ornl-cumulus-prod-protected/above/Monthly_Hydrological_Fluxes/data/surface_temperature_monthly.nc4", "filename": "surface_temperature_monthly.nc4", "data_center": "ORNLDAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"F08_SSMI_FCDR2021_L2_V1_19870709-S125514-E143711.000274.V01E.nc": {"collection": "PRECIP_SSMI_F08", "version": "1", "direct_link": "s3://gesdisc-cumulus-prod-protected/Precipitation/PRECIP_SSMI_F08.1/1987/190/F08_SSMI_FCDR2021_L2_V1_19870709-S125514-E143711.000274.V01E.nc", "filename": "F08_SSMI_FCDR2021_L2_V1_19870709-S125514-E143711.000274.V01E.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"SBUV2-NOAA18_L3zm_v01-02-2013m0403t071112.h5": {"collection": "SBUV2N18L3zm", "version": "1", "direct_link": "s3://gesdisc-cumulus-prod-protected/Ozone/SBUV2N18L3zm.1/SBUV2-NOAA18_L3zm_v01-02-2013m0403t071112.h5", "filename": "SBUV2-NOAA18_L3zm_v01-02-2013m0403t071112.h5", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, "Caught exception An error occurred (403) when calling the HeadObject operation: Forbidden while trying to process file from collection SWOT_L1B_LR_INTF_1.0, version 1.0", "Caught exception An error occurred (403) when calling the HeadObject operation: Forbidden while trying to process file from collection SWOT_L1B_LR_INTF_2.0, version 2.0", {"Tellus_GIA_L3_A-WAHR_ICE5G-VM2_0.5-DEG_v1.0.nc": {"collection": "TELLUS_GIA_L3_0.5-DEG_V1.0", "version": "1.0", "direct_link": "s3://podaac-ops-cumulus-protected/TELLUS_GIA_L3_0.5-DEG_V1.0/Tellus_GIA_L3_A-WAHR_ICE5G-VM2_0.5-DEG_v1.0.nc", "filename": "Tellus_GIA_L3_A-WAHR_ICE5G-VM2_0.5-DEG_v1.0.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"1C51.971201.1.HSTN.3.HDF": {"collection": "TRMM_1C51", "version": "7", "direct_link": "s3://gesdisc-cumulus-prod-protected/TRMM_GV_L1/TRMM_1C51.7/1997/335/1C51.971201.1.HSTN.3.HDF", "filename": "1C51.971201.1.HSTN.3.HDF", "data_center": "GES_DISC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"TROPESS_AIRS-Aqua_L2_Summary_HDO_20210201_MUSES_R1p11_FS_F0p6.nc": {"collection": "TRPSYL2HDOAIRSFS", "version": "1", "direct_link": "s3://gesdisc-cumulus-prod-protected/TROPESS_Summary/TRPSYL2HDOAIRSFS.1/2021/TROPESS_AIRS-Aqua_L2_Summary_HDO_20210201_MUSES_R1p11_FS_F0p6.nc", "filename": "TROPESS_AIRS-Aqua_L2_Summary_HDO_20210201_MUSES_R1p11_FS_F0p6.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"TROPESS_OMI-Aura_L2_Summary_O3_20210201_MUSES_R1p11_FS_F0p6.nc": {"collection": "TRPSYL2O3OMIFS", "version": "1", "direct_link": "s3://gesdisc-cumulus-prod-protected/TROPESS_Summary/TRPSYL2O3OMIFS.1/2021/TROPESS_OMI-Aura_L2_Summary_O3_20210201_MUSES_R1p11_FS_F0p6.nc", "filename": "TROPESS_OMI-Aura_L2_Summary_O3_20210201_MUSES_R1p11_FS_F0p6.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"VJ109A1.A2018001.h13v01.002.2022349164539.h5": {"collection": "VJ109A1", "version": "002", "direct_link": "s3://lp-prod-protected/VJ109A1.002/VJ109A1.A2018001.h13v01.002.2022349164539/VJ109A1.A2018001.h13v01.002.2022349164539.h5", "filename": "VJ109A1.A2018001.h13v01.002.2022349164539.h5", "data_center": "LPDAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"f16_ssmis_20031026v7.nc": {"collection": "rssmif16d", "version": "7", "direct_link": "s3://ghrcw-protected/rssmif16d__7/ssmis/f16/daily/data/2003/f16_ssmis_20031026v7.nc", "filename": "f16_ssmis_20031026v7.nc", "data_center": "GHRCDAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"f16_ssmis_200310v7.nc": {"collection": "rssmif16m", "version": "7", "direct_link": "s3://ghrcw-protected/rssmif16m__7/f16_ssmis_200310v7.nc", "filename": "f16_ssmis_200310v7.nc", "data_center": "GHRCDAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"ABoVE_2017_insitu_10sec.nc": {"collection": "ABoVE_Arctic_CAP_1658", "version": "1", "direct_link": "s3://ornl-cumulus-prod-protected/above/ABoVE_Arctic_CAP/data/ABoVE_2017_insitu_10sec.nc", "filename": "ABoVE_2017_insitu_10sec.nc", "data_center": "ORNLDAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"AIRS.2002.08.30.225.L2.CC_H.v7.0.1.0.G20190071029.hdf": {"collection": "AIRH2CCF", "version": "7.0", "direct_link": "s3://gesdisc-cumulus-prod-protected/Aqua_AIRS_Level2/AIRH2CCF.7.0/2002/242/AIRS.2002.08.30.225.L2.CC_H.v7.0.1.0.G20190071029.hdf", "filename": "AIRS.2002.08.30.225.L2.CC_H.v7.0.1.0.G20190071029.hdf", "data_center": "GES_DISC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"Q2011_09_RFI.h5": {"collection": "AQUARIUS_ANCILLARY_RFI_V1", "version": "1", "direct_link": "s3://podaac-ops-cumulus-protected/AQUARIUS_ANCILLARY_RFI_V1/Q2011_09_RFI.h5", "filename": "Q2011_09_RFI.h5", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"carve_FLIR_L1A_b23_20130403_000034_20160304012051738.nc": {"collection": "CARVE_L1_Infrared_1428", "version": "1", "direct_link": "s3://ornl-cumulus-prod-protected/carve/campaign/CARVE_L1_Infrared/data/carve_FLIR_L1A_b23_20130403_000034_20160304012051738.nc", "filename": "carve_FLIR_L1A_b23_20130403_000034_20160304012051738.nc", "data_center": "ORNLDAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"cyg.ddmi.s20180806-213629-e20180806-214633.l1.power-brcs-full.a30.d31.nc": {"collection": "CYGNSS_L1_FULL_DDM_V3.0", "version": "3.0", "direct_link": "s3://podaac-ops-cumulus-protected/CYGNSS_L1_FULL_DDM_V3.0/2018/218/cyg.ddmi.s20180806-213629-e20180806-214633.l1.power-brcs-full.a30.d31.nc", "filename": "cyg.ddmi.s20180806-213629-e20180806-214633.l1.power-brcs-full.a30.d31.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"3A-MO.F16.SSMIS.GRID2021R1.20220501-S000000-E235959.05.V07A.HDF5": {"collection": "GPM_3GPROFF16SSMIS", "version": "07", "direct_link": "s3://gesdisc-cumulus-prod-protected/GPM_L3/GPM_3GPROFF16SSMIS.07/2022/3A-MO.F16.SSMIS.GRID2021R1.20220501-S000000-E235959.05.V07A.HDF5", "filename": "3A-MO.F16.SSMIS.GRID2021R1.20220501-S000000-E235959.05.V07A.HDF5", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"reservoir_methane_emissions.nc": {"collection": "Global_Reservoirs_Methane_1918", "version": "1", "direct_link": "s3://ornl-cumulus-prod-protected/nacp/Global_Reservoirs_Methane/data/reservoir_methane_emissions.nc", "filename": "reservoir_methane_emissions.nc", "data_center": "ORNLDAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"MCD18A2.A2000063.h22v15.062.2023152174340.hdf": {"collection": "MCD18A2", "version": "062", "direct_link": "s3://lp-prod-protected/MCD18A2.062/MCD18A2.A2000063.h22v15.062.2023152174340/MCD18A2.A2000063.h22v15.062.2023152174340.hdf", "filename": "MCD18A2.A2000063.h22v15.062.2023152174340.hdf", "data_center": "LPDAAC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"LLC4320_pre-SWOT_ACC_SMST_20110913.nc": {"collection": "MITgcm_LLC4320_Pre-SWOT_JPL_L4_ACC_SMST_v1.0", "version": "1.0", "direct_link": "s3://podaac-ops-cumulus-protected/MITgcm_LLC4320_Pre-SWOT_JPL_L4_ACC_SMST_v1.0/LLC4320_pre-SWOT_ACC_SMST_20110913.nc", "filename": "LLC4320_pre-SWOT_ACC_SMST_20110913.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"AQUA_MODIS.20020704.L3m.DAY.SST4.sst4.4km.nc": {"collection": "MODIS_AQUA_L3_SST_MID-IR_DAILY_4KM_NIGHTTIME_V2019.0", "version": "2019.0", "direct_link": "s3://podaac-ops-cumulus-protected/MODIS_AQUA_L3_SST_MID-IR_DAILY_4KM_NIGHTTIME_V2019.0/AQUA_MODIS.20020704.L3m.DAY.SST4.sst4.4km.nc", "filename": "AQUA_MODIS.20020704.L3m.DAY.SST4.sst4.4km.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"ersst.v5.185401.nc": {"collection": "REYNOLDS_NCDC_L4_MONTHLY_V5", "version": "5", "direct_link": "s3://podaac-ops-cumulus-protected/REYNOLDS_NCDC_L4_MONTHLY_V5/ersst.v5.185401.nc", "filename": "ersst.v5.185401.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"SBUV2-NOAA14_L3zm_v01-02-2013m0422t101841.h5": {"collection": "SBUV2N14L3zm", "version": "1", "direct_link": "s3://gesdisc-cumulus-prod-protected/Ozone/SBUV2N14L3zm.1/SBUV2-NOAA14_L3zm_v01-02-2013m0422t101841.h5", "filename": "SBUV2-NOAA14_L3zm_v01-02-2013m0422t101841.h5", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"Alaska_active_layer_thickness_1km_2001-2015.nc4": {"collection": "Sat_ActiveLayer_Thickness_Maps_1760", "version": "1", "direct_link": "s3://ornl-cumulus-prod-protected/above/Sat_ActiveLayer_Thickness_Maps/data/Alaska_active_layer_thickness_1km_2001-2015.nc4", "filename": "Alaska_active_layer_thickness_1km_2001-2015.nc4", "data_center": "ORNLDAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, "Caught exception 'accessKeyId' while trying to process file from collection TEMPO_RAD_L1, version V01", {"19971208000000-REMSS-L3U_GHRSST-SSTsubskin-TMI-f12_19971208v7.1-v02.0-fv01.0.nc": {"collection": "TMI-REMSS-L3U-v7.1a", "version": "7.1a", "direct_link": "s3://podaac-ops-cumulus-protected/TMI-REMSS-L3U-v7.1a/19971208000000-REMSS-L3U_GHRSST-SSTsubskin-TMI-f12_19971208v7.1-v02.0-fv01.0.nc", "filename": "19971208000000-REMSS-L3U_GHRSST-SSTsubskin-TMI-f12_19971208v7.1-v02.0-fv01.0.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"TOVS.PathA.L3.TIROSN.tn.etirosn.Dec.1978.V2.nc": {"collection": "TOVSAMTN", "version": "02", "direct_link": "s3://gesdisc-cumulus-prod-protected/TOVS/TOVSAMTN.02/1978/TOVS.PathA.L3.TIROSN.tn.etirosn.Dec.1978.V2.nc", "filename": "TOVS.PathA.L3.TIROSN.tn.etirosn.Dec.1978.V2.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"TROPESS_CrIS-JPSS1_L2_Standard_HDO_20210401_MUSES_R1p12_FS_F0p1.nc": {"collection": "TRPSDL2HDOCRS1FS", "version": "1", "direct_link": "s3://gesdisc-cumulus-prod-protected/TROPESS_Standard/TRPSDL2HDOCRS1FS.1/2021/TROPESS_CrIS-JPSS1_L2_Standard_HDO_20210401_MUSES_R1p12_FS_F0p1.nc", "filename": "TROPESS_CrIS-JPSS1_L2_Standard_HDO_20210401_MUSES_R1p12_FS_F0p1.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"TROPESS_AIRS-Aqua_L2_Summary_CH4_20210201_MUSES_R1p11_FS_F0p6.nc": {"collection": "TRPSYL2CH4AIRSFS", "version": "1", "direct_link": "s3://gesdisc-cumulus-prod-protected/TROPESS_Summary/TRPSYL2CH4AIRSFS.1/2021/TROPESS_AIRS-Aqua_L2_Summary_CH4_20210201_MUSES_R1p11_FS_F0p6.nc", "filename": "TROPESS_AIRS-Aqua_L2_Summary_CH4_20210201_MUSES_R1p11_FS_F0p6.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"20120201000000-STAR-L3U_GHRSST-SSTsubskin-VIIRS_NPP-ACSPO_V2.80-v02.0-fv01.0.nc": {"collection": "VIIRS_NPP-STAR-L3U-v2.80", "version": "2.80", "direct_link": "s3://podaac-ops-cumulus-protected/VIIRS_NPP-STAR-L3U-v2.80/20120201000000-STAR-L3U_GHRSST-SSTsubskin-VIIRS_NPP-ACSPO_V2.80-v02.0-fv01.0.nc", "filename": "20120201000000-STAR-L3U_GHRSST-SSTsubskin-VIIRS_NPP-ACSPO_V2.80-v02.0-fv01.0.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"VNP09A1.A2012017.h30v10.002.2024106202818.h5": 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"MCD43D01", "version": "061", "direct_link": "s3://lp-prod-protected/MCD43D01.061/MCD43D01.A2000055.061.2020038223721/MCD43D01.A2000055.061.2020038223721.hdf", "filename": "MCD43D01.A2000055.061.2020038223721.hdf", "data_center": "LPDAAC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"MCD43D08.A2000055.061.2020038223724.hdf": {"collection": "MCD43D08", "version": "061", "direct_link": "s3://lp-prod-protected/MCD43D08.061/MCD43D08.A2000055.061.2020038223724/MCD43D08.A2000055.061.2020038223724.hdf", "filename": "MCD43D08.A2000055.061.2020038223724.hdf", "data_center": "LPDAAC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"MCD43D11.A2000055.061.2020038223724.hdf": {"collection": "MCD43D11", "version": "061", "direct_link": "s3://lp-prod-protected/MCD43D11.061/MCD43D11.A2000055.061.2020038223724/MCD43D11.A2000055.061.2020038223724.hdf", "filename": "MCD43D11.A2000055.061.2020038223724.hdf", "data_center": "LPDAAC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"MCD43D13.A2000055.061.2020038223722.hdf": {"collection": "MCD43D13", "version": "061", "direct_link": "s3://lp-prod-protected/MCD43D13.061/MCD43D13.A2000055.061.2020038223722/MCD43D13.A2000055.061.2020038223722.hdf", "filename": "MCD43D13.A2000055.061.2020038223722.hdf", "data_center": "LPDAAC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"MCD43D15.A2000055.061.2020038223726.hdf": {"collection": "MCD43D15", "version": "061", "direct_link": "s3://lp-prod-protected/MCD43D15.061/MCD43D15.A2000055.061.2020038223726/MCD43D15.A2000055.061.2020038223726.hdf", "filename": "MCD43D15.A2000055.061.2020038223726.hdf", "data_center": "LPDAAC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"MCD43D21.A2000055.061.2020038223726.hdf": {"collection": "MCD43D21", "version": "061", "direct_link": "s3://lp-prod-protected/MCD43D21.061/MCD43D21.A2000055.061.2020038223726/MCD43D21.A2000055.061.2020038223726.hdf", "filename": "MCD43D21.A2000055.061.2020038223726.hdf", "data_center": "LPDAAC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"MCD43D51.A2000055.061.2020038223730.hdf": {"collection": "MCD43D51", "version": "061", "direct_link": "s3://lp-prod-protected/MCD43D51.061/MCD43D51.A2000055.061.2020038223730/MCD43D51.A2000055.061.2020038223730.hdf", "filename": "MCD43D51.A2000055.061.2020038223730.hdf", "data_center": "LPDAAC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"N09_AVH02C1.A1985004.006.2022276085112.nc": {"collection": "N09_AVH02C1", "version": "6", "direct_link": "s3://prod-lads/N09_AVH02C1/N09_AVH02C1.A1985004.006.2022276085112.nc", "filename": "N09_AVH02C1.A1985004.006.2022276085112.nc", "data_center": "LAADS", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"N11_AVH09C1.A1988313.006.2022279134244.nc": {"collection": "N11_AVH09C1", "version": "6", "direct_link": "s3://prod-lads/N11_AVH09C1/N11_AVH09C1.A1988313.006.2022279134244.nc", "filename": "N11_AVH09C1.A1988313.006.2022279134244.nc", "data_center": "LAADS", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"N14_AVH09C1.A1995001.006.2022284092356.nc": {"collection": "N14_AVH09C1", "version": "6", "direct_link": "s3://prod-lads/N14_AVH09C1/N14_AVH09C1.A1995001.006.2022284092356.nc", "filename": "N14_AVH09C1.A1995001.006.2022284092356.nc", "data_center": "LAADS", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"S_MODE_saildroneL1.tar.gz": {"collection": "SMODE_L1_SAILDRONES_V1", "version": "1", "direct_link": "s3://podaac-ops-cumulus-protected/SMODE_L1_SAILDRONES_V1/S_MODE_saildroneL1.tar.gz", "filename": "S_MODE_saildroneL1.tar.gz", "data_center": "PODAAC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"S_MODE_IOP2_navoFloat_4903095.nc": {"collection": "SMODE_L2_APEX_FLOAT_V1", "version": "1", "direct_link": "s3://podaac-ops-cumulus-protected/SMODE_L2_APEX_FLOAT_V1/S_MODE_IOP2_navoFloat_4903095.nc", "filename": "S_MODE_IOP2_navoFloat_4903095.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"S_MODE_PFC_OC2108A_radiosonde_001.nc": {"collection": "SMODE_L2_SHIPBOARD_RADIOSONDES_METEOROLOGY_V1", "version": "1", "direct_link": "s3://podaac-ops-cumulus-protected/SMODE_L2_SHIPBOARD_RADIOSONDES_METEOROLOGY_V1/S_MODE_PFC_OC2108A_radiosonde_001.nc", "filename": "S_MODE_PFC_OC2108A_radiosonde_001.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"S_MODE_PFC_OC2108A_shipboard_SUNA.nc": {"collection": "SMODE_L2_SHIPBOARD_SUNA_V1", "version": "1", "direct_link": "s3://podaac-ops-cumulus-protected/SMODE_L2_SHIPBOARD_SUNA_V1/S_MODE_PFC_OC2108A_shipboard_SUNA.nc", "filename": "S_MODE_PFC_OC2108A_shipboard_SUNA.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"SPURS2_Xband_marine_radar_2017_1021_1716.nc": {"collection": "SPURS2_XBAND", "version": "1.0", "direct_link": "s3://podaac-ops-cumulus-protected/SPURS2_XBAND/SPURS2_Xband_marine_radar_2017_1021_1716.nc", "filename": "SPURS2_Xband_marine_radar_2017_1021_1716.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, "Caught exception 'accessKeyId' while trying to process file from collection TEMPO_DRK_L1, version V02", {"TOVS.PathA.L3.NOAA7.nc.en6n7.Aug.1981.V2.nc": {"collection": "TOVSAMNC", "version": "02", "direct_link": "s3://gesdisc-cumulus-prod-protected/TOVS/TOVSAMNC.02/1981/TOVS.PathA.L3.NOAA7.nc.en6n7.Aug.1981.V2.nc", "filename": "TOVS.PathA.L3.NOAA7.nc.en6n7.Aug.1981.V2.nc", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"3A53.971127.DARW.3.HDF": {"collection": "TRMM_3A53", "version": "7", "direct_link": "s3://gesdisc-cumulus-prod-protected/TRMM_GV_L3/TRMM_3A53.7/1997/331/3A53.971127.DARW.3.HDF", "filename": "3A53.971127.DARW.3.HDF", "data_center": "GES_DISC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"20240221193002-NAVO-L2P_GHRSST-SST1m-VIIRS_N21-v02.0-fv03.0.nc": {"collection": "VIIRS_N21-NAVO-L2P-v3.0", "version": "3.0", "direct_link": "s3://podaac-ops-cumulus-protected/VIIRS_N21-NAVO-L2P-v3.0/20240221193002-NAVO-L2P_GHRSST-SST1m-VIIRS_N21-v02.0-fv03.0.nc", "filename": "20240221193002-NAVO-L2P_GHRSST-SST1m-VIIRS_N21-v02.0-fv03.0.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"VJ113A1.A2018001.h15v01.002.2022352115601.h5": {"collection": "VJ113A1", "version": "002", "direct_link": "s3://lp-prod-protected/VJ113A1.002/VJ113A1.A2018001.h15v01.002.2022352115601/VJ113A1.A2018001.h15v01.002.2022352115601.h5", "filename": "VJ113A1.A2018001.h15v01.002.2022352115601.h5", "data_center": "LPDAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"VJ121.A2018011.0100.002.2022255145406.nc": {"collection": "VJ121", "version": "002", "direct_link": "s3://lp-prod-protected/VJ121.002/VJ121.A2018011.0100.002.2022255145406/VJ121.A2018011.0100.002.2022255145406.nc", "filename": "VJ121.A2018011.0100.002.2022255145406.nc", "data_center": "LPDAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"VJ121C1.A2018005.002.2023120234443.h5": {"collection": "VJ121C1", "version": "002", "direct_link": "s3://lp-prod-protected/VJ121C1.002/VJ121C1.A2018005.002.2023120234443/VJ121C1.A2018005.002.2023120234443.h5", "filename": "VJ121C1.A2018005.002.2023120234443.h5", "data_center": "LPDAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"IMPACTS_HIWRAP_L1B_RevC_20200125.h5": {"collection": "hiwrapimpacts", "version": "1", "direct_link": "s3://ghrcw-protected/hiwrapimpacts__1/IMPACTS_HIWRAP_L1B_RevC_20200125.h5", "filename": "IMPACTS_HIWRAP_L1B_RevC_20200125.h5", "data_center": "GHRCDAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"IMPACTS_UIUC_Mobile_research_sounding_20200118_1600.nc": {"collection": "uiucsndimpacts", "version": "1", "direct_link": "s3://ghrcw-protected/uiucsndimpacts__1/IMPACTS_UIUC_Mobile_research_sounding_20200118_1600.nc", "filename": "IMPACTS_UIUC_Mobile_research_sounding_20200118_1600.nc", "data_center": "GHRCDAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"ECOv002_L1B_RAD_20799_001_20220307T163638_0700_02.h5": {"collection": "ECO_L1B_RAD", "version": "002", "direct_link": "s3://lp-prod-protected/ECO_L1B_RAD.002/ECOv002_L1B_RAD_20799_001_20220307T163638_0700_02/ECOv002_L1B_RAD_20799_001_20220307T163638_0700_02.h5", "filename": "ECOv002_L1B_RAD_20799_001_20220307T163638_0700_02.h5", "data_center": "LPDAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, "Caught exception An error occurred (404) when calling the HeadObject operation: Not Found while trying to process file from collection ECO_L1CG_RAD, version 002", "Caught exception An error occurred (404) when calling the HeadObject operation: Not Found while trying to process file from collection ECO_L2G_CLOUD, version 002", {"GLAH09_633_1102_001_0071_0_01_0001.H5": {"collection": "GLAH09", "version": "033", "direct_link": "s3://nsidc-cumulus-prod-protected/GLAS/GLAH09/033/2003/2/GLAH09_633_1102_001_0071_0_01_0001.H5", "filename": "GLAH09_633_1102_001_0071_0_01_0001.H5", "data_center": "NSIDC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"2A.TRMM.PR.TRMM-SLH.19971207-S235717-E012836.000160.V07A.HDF5": {"collection": "GPM_2HSLH_TRMM", "version": "07", "direct_link": "s3://gesdisc-cumulus-prod-protected/TRMM_L2/GPM_2HSLH_TRMM.07/1997/341/2A.TRMM.PR.TRMM-SLH.19971207-S235717-E012836.000160.V07A.HDF5", "filename": "2A.TRMM.PR.TRMM-SLH.19971207-S235717-E012836.000160.V07A.HDF5", "data_center": "GES_DISC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"MCD43D04.A2000055.061.2020038223722.hdf": {"collection": "MCD43D04", "version": "061", "direct_link": "s3://lp-prod-protected/MCD43D04.061/MCD43D04.A2000055.061.2020038223722/MCD43D04.A2000055.061.2020038223722.hdf", "filename": "MCD43D04.A2000055.061.2020038223722.hdf", "data_center": "LPDAAC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"MCD43D05.A2000055.061.2020038223723.hdf": {"collection": "MCD43D05", "version": "061", "direct_link": "s3://lp-prod-protected/MCD43D05.061/MCD43D05.A2000055.061.2020038223723/MCD43D05.A2000055.061.2020038223723.hdf", "filename": "MCD43D05.A2000055.061.2020038223723.hdf", "data_center": "LPDAAC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"MCD43D06.A2000055.061.2020038223725.hdf": {"collection": "MCD43D06", "version": "061", "direct_link": "s3://lp-prod-protected/MCD43D06.061/MCD43D06.A2000055.061.2020038223725/MCD43D06.A2000055.061.2020038223725.hdf", "filename": "MCD43D06.A2000055.061.2020038223725.hdf", "data_center": "LPDAAC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"MCD43D12.A2000055.061.2020038223726.hdf": {"collection": "MCD43D12", "version": "061", "direct_link": "s3://lp-prod-protected/MCD43D12.061/MCD43D12.A2000055.061.2020038223726/MCD43D12.A2000055.061.2020038223726.hdf", "filename": "MCD43D12.A2000055.061.2020038223726.hdf", "data_center": "LPDAAC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"MCD43D14.A2000055.061.2020038223724.hdf": {"collection": "MCD43D14", "version": "061", "direct_link": "s3://lp-prod-protected/MCD43D14.061/MCD43D14.A2000055.061.2020038223724/MCD43D14.A2000055.061.2020038223724.hdf", "filename": "MCD43D14.A2000055.061.2020038223724.hdf", "data_center": "LPDAAC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"MCD43D26.A2000055.061.2020038223725.hdf": {"collection": "MCD43D26", "version": "061", "direct_link": "s3://lp-prod-protected/MCD43D26.061/MCD43D26.A2000055.061.2020038223725/MCD43D26.A2000055.061.2020038223725.hdf", "filename": "MCD43D26.A2000055.061.2020038223725.hdf", "data_center": "LPDAAC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"MCD43D27.A2000055.061.2020038223726.hdf": {"collection": "MCD43D27", "version": "061", "direct_link": "s3://lp-prod-protected/MCD43D27.061/MCD43D27.A2000055.061.2020038223726/MCD43D27.A2000055.061.2020038223726.hdf", "filename": "MCD43D27.A2000055.061.2020038223726.hdf", "data_center": "LPDAAC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"MCD43D42.A2000055.061.2020038223729.hdf": {"collection": "MCD43D42", "version": "061", "direct_link": "s3://lp-prod-protected/MCD43D42.061/MCD43D42.A2000055.061.2020038223729/MCD43D42.A2000055.061.2020038223729.hdf", "filename": "MCD43D42.A2000055.061.2020038223729.hdf", "data_center": "LPDAAC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"MYD02HKM.A2002185.0045.061.2017362175852.hdf": {"collection": "MYD02HKM", "version": "6.1", "direct_link": "s3://prod-lads/MYD02HKM/MYD02HKM.A2002185.0045.061.2017362175852.hdf", "filename": "MYD02HKM.A2002185.0045.061.2017362175852.hdf", "data_center": "LAADS", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"N07_AVH13C1.A1981175.006.2022270161458.nc": {"collection": "N07_AVH13C1", "version": "6", "direct_link": "s3://prod-lads/N07_AVH13C1/N07_AVH13C1.A1981175.006.2022270161458.nc", "filename": "N07_AVH13C1.A1981175.006.2022270161458.nc", "data_center": "LAADS", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"N16_AVH02C1.A2000306.006.2022287103329.nc": {"collection": "N16_AVH02C1", "version": "6", "direct_link": "s3://prod-lads/N16_AVH02C1/N16_AVH02C1.A2000306.006.2022287103329.nc", "filename": "N16_AVH02C1.A2000306.006.2022287103329.nc", "data_center": "LAADS", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"N19_AVH09C1.A2009151.006.2022296170410.nc": {"collection": "N19_AVH09C1", "version": "6", "direct_link": "s3://prod-lads/N19_AVH09C1/N19_AVH09C1.A2009151.006.2022296170410.nc", "filename": "N19_AVH09C1.A2009151.006.2022296170410.nc", "data_center": "LAADS", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"OMG_Ocean_AXBT_L2_20200902175210.nc": {"collection": "OMG_L2_AXBT", "version": "1", "direct_link": "s3://podaac-ops-cumulus-protected/OMG_L2_AXBT/OMG_Ocean_AXBT_L2_20200902175210.nc", "filename": "OMG_Ocean_AXBT_L2_20200902175210.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"luarea_hyde32u.nc": {"collection": "Peatland_carbon_balance_1382", "version": "1", "direct_link": "s3://ornl-cumulus-prod-protected/global_soil/Peatland_carbon_balance/data/luarea_hyde32u.nc", "filename": "luarea_hyde32u.nc", "data_center": "ORNLDAAC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"QS_S1B00430.20070620043": {"collection": "QSCAT_LEVEL_1B_V2", "version": "2", "direct_link": "s3://podaac-ops-cumulus-protected/QSCAT_LEVEL_1B_V2/QS_S1B00430.20070620043", "filename": "QS_S1B00430.20070620043", 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{"f11_ssmi_19911203v7.nc": {"collection": "rssmif11d", "version": "7", "direct_link": "s3://ghrcw-protected/rssmif11d__7/f11_ssmi_19911203v7.nc", "filename": "f11_ssmi_19911203v7.nc", "data_center": "GHRCDAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"f17_ssmis_20061216v7_wk.nc": {"collection": "rssmif17w", "version": "7", "direct_link": "s3://ghrcw-protected/rssmif17w__7/ssmis/f17/weekly/data/2006/f17_ssmis_20061216v7_wk.nc", "filename": "f17_ssmis_20061216v7_wk.nc", "data_center": "GHRCDAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"IMPACTS_SBU_dopplerlidar_20200101_rhi_BNL.nc": {"collection": "sbulidarimpacts", "version": "1", "direct_link": "s3://ghrcw-protected/sbulidarimpacts__1/IMPACTS_SBU_dopplerlidar_20200101_rhi_BNL.nc", "filename": "IMPACTS_SBU_dopplerlidar_20200101_rhi_BNL.nc", "data_center": "GHRCDAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"IMPACTS_SBU_parsivel_20200101_MAN.nc": {"collection": "sbuparsimpacts", "version": "1", "direct_link": "s3://ghrcw-protected/sbuparsimpacts__1/IMPACTS_SBU_parsivel_20200101_MAN.nc", "filename": "IMPACTS_SBU_parsivel_20200101_MAN.nc", "data_center": "GHRCDAAC", "fsm_strategy": "Not found", "page_size": "Not found"}}, "Caught exception list index out of range while trying to process file from collection AERDB_L2_VIIRS_SNPP, version 1.1", {"20191016000000-STAR-L3C_GHRSST-SSTsubskin-AHI_H08-ACSPO_V2.70-v02.0-fv01.0.nc": {"collection": "AHI_H08-STAR-L3C-v2.70", "version": "2.70", "direct_link": "s3://podaac-ops-cumulus-protected/AHI_H08-STAR-L3C-v2.70/20191016000000-STAR-L3C_GHRSST-SSTsubskin-AHI_H08-ACSPO_V2.70-v02.0-fv01.0.nc", "filename": "20191016000000-STAR-L3C_GHRSST-SSTsubskin-AHI_H08-ACSPO_V2.70-v02.0-fv01.0.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"CLDPROP_D3_VIIRS_SNPP.A2012061.011.2019253051646.nc": {"collection": 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{"MCD43D66.A2000055.061.2020038223733.hdf": {"collection": "MCD43D66", "version": "061", "direct_link": "s3://lp-prod-protected/MCD43D66.061/MCD43D66.A2000055.061.2020038223733/MCD43D66.A2000055.061.2020038223733.hdf", "filename": "MCD43D66.A2000055.061.2020038223733.hdf", "data_center": "LPDAAC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"MOD05_L2.A2000055.0000.061.2017205183337.hdf": {"collection": "MOD05_L2", "version": "6.1", "direct_link": "s3://prod-lads/MOD05_L2/MOD05_L2.A2000055.0000.061.2017205183337.hdf", "filename": "MOD05_L2.A2000055.0000.061.2017205183337.hdf", "data_center": "LAADS", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"MOD07_L2.A2000055.0000.061.2017202185924.hdf": {"collection": "MOD07_L2", "version": "6.1", "direct_link": "s3://prod-lads/MOD07_L2/MOD07_L2.A2000055.0000.061.2017202185924.hdf", "filename": "MOD07_L2.A2000055.0000.061.2017202185924.hdf", "data_center": "LAADS", "fsm_strategy": "Not found", "page_size": "Not found"}}, "Caught exception list index out of range while trying to process file from collection MODATML2, version 6.1", {"MYD04_3K.A2002185.0045.061.2018003214416.hdf": {"collection": "MYD04_3K", "version": "6.1", "direct_link": "s3://prod-lads/MYD04_3K/MYD04_3K.A2002185.0045.061.2018003214416.hdf", "filename": "MYD04_3K.A2002185.0045.061.2018003214416.hdf", "data_center": "LAADS", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"MYD07_L2.A2002185.0000.061.2017363141927.hdf": {"collection": "MYD07_L2", "version": "6.1", "direct_link": "s3://prod-lads/MYD07_L2/MYD07_L2.A2002185.0000.061.2017363141927.hdf", "filename": "MYD07_L2.A2002185.0000.061.2017363141927.hdf", "data_center": "LAADS", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"MODIS_LST_LC15.nc4": {"collection": "NA_MODIS_Surface_Biophysics_1210", "version": "1", "direct_link": "s3://ornl-cumulus-prod-protected/global_vegetation/NA_MODIS_Surface_Biophysics/data/MODIS_LST_LC15.nc4", "filename": "MODIS_LST_LC15.nc4", 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{"collection": "TRMM_2A53UW", "version": "7", "direct_link": "s3://gesdisc-cumulus-prod-protected/TRMM_GV_L2/TRMM_2A53UW.7/1999/009/2A53UW.19990109.6.kwaj.4.tar", "filename": "2A53UW.19990109.6.kwaj.4.tar", "data_center": "GES_DISC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"2A54UW.19990109.6.kwaj.4.tar": {"collection": "TRMM_2A54UW", "version": "7", "direct_link": "s3://gesdisc-cumulus-prod-protected/TRMM_GV_L2/TRMM_2A54UW.7/1999/009/2A54UW.19990109.6.kwaj.4.tar", "filename": "2A54UW.19990109.6.kwaj.4.tar", "data_center": "GES_DISC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"3A55.971201.DARW.5.HDF": {"collection": "TRMM_3A55", "version": "7", "direct_link": "s3://gesdisc-cumulus-prod-protected/TRMM_GV_L3/TRMM_3A55.7/1997/335/3A55.971201.DARW.5.HDF", "filename": "3A55.971201.DARW.5.HDF", "data_center": "GES_DISC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"baseUW.19990109.6.kwaj.4.tar": {"collection": "TRMM_baseUW", "version": "7", 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"LLC4320_pre-SWOT_LabradorSea_20110913.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"LLC4320_pre-SWOT_MarmaraSea_20110913.nc": {"collection": "MITgcm_LLC4320_Pre-SWOT_JPL_L4_MarmaraSea_v1.0", "version": "1.0", "direct_link": "s3://podaac-ops-cumulus-protected/MITgcm_LLC4320_Pre-SWOT_JPL_L4_MarmaraSea_v1.0/LLC4320_pre-SWOT_MarmaraSea_20110913.nc", "filename": "LLC4320_pre-SWOT_MarmaraSea_20110913.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"LLC4320_pre-SWOT_NWAustralia_20110913.nc": {"collection": "MITgcm_LLC4320_Pre-SWOT_JPL_L4_NWAustralia_v1.0", "version": "1.0", "direct_link": "s3://podaac-ops-cumulus-protected/MITgcm_LLC4320_Pre-SWOT_JPL_L4_NWAustralia_v1.0/LLC4320_pre-SWOT_NWAustralia_20110913.nc", "filename": "LLC4320_pre-SWOT_NWAustralia_20110913.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"LLC4320_pre-SWOT_NWPacific_20110913.nc": {"collection": "MITgcm_LLC4320_Pre-SWOT_JPL_L4_NWPacific_v1.0", "version": "1.0", "direct_link": "s3://podaac-ops-cumulus-protected/MITgcm_LLC4320_Pre-SWOT_JPL_L4_NWPacific_v1.0/LLC4320_pre-SWOT_NWPacific_20110913.nc", "filename": "LLC4320_pre-SWOT_NWPacific_20110913.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"LLC4320_pre-SWOT_NewCaledonia_20110913.nc": {"collection": "MITgcm_LLC4320_Pre-SWOT_JPL_L4_NewCaledonia_v1.0", "version": "1.0", "direct_link": "s3://podaac-ops-cumulus-protected/MITgcm_LLC4320_Pre-SWOT_JPL_L4_NewCaledonia_v1.0/LLC4320_pre-SWOT_NewCaledonia_20110913.nc", "filename": "LLC4320_pre-SWOT_NewCaledonia_20110913.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"LLC4320_pre-SWOT_ROAM_MIZ_20110913.nc": {"collection": "MITgcm_LLC4320_Pre-SWOT_JPL_L4_ROAM_MIZ_v1.0", "version": "1.0", "direct_link": "s3://podaac-ops-cumulus-protected/MITgcm_LLC4320_Pre-SWOT_JPL_L4_ROAM_MIZ_v1.0/LLC4320_pre-SWOT_ROAM_MIZ_20110913.nc", "filename": "LLC4320_pre-SWOT_ROAM_MIZ_20110913.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"LLC4320_pre-SWOT_RockallTrough_20110913.nc": {"collection": "MITgcm_LLC4320_Pre-SWOT_JPL_L4_RockallTrough_v1.0", "version": "1.0", "direct_link": "s3://podaac-ops-cumulus-protected/MITgcm_LLC4320_Pre-SWOT_JPL_L4_RockallTrough_v1.0/LLC4320_pre-SWOT_RockallTrough_20110913.nc", "filename": "LLC4320_pre-SWOT_RockallTrough_20110913.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"LLC4320_pre-SWOT_WestAtlantic_20110913.nc": {"collection": "MITgcm_LLC4320_Pre-SWOT_JPL_L4_WestAtlantic_v1.0", "version": "1.0", "direct_link": "s3://podaac-ops-cumulus-protected/MITgcm_LLC4320_Pre-SWOT_JPL_L4_WestAtlantic_v1.0/LLC4320_pre-SWOT_WestAtlantic_20110913.nc", "filename": "LLC4320_pre-SWOT_WestAtlantic_20110913.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"LLC4320_pre-SWOT_WesternMed_20110913.nc": {"collection": "MITgcm_LLC4320_Pre-SWOT_JPL_L4_WesternMed_v1.0", "version": "1.0", "direct_link": "s3://podaac-ops-cumulus-protected/MITgcm_LLC4320_Pre-SWOT_JPL_L4_WesternMed_v1.0/LLC4320_pre-SWOT_WesternMed_20110913.nc", "filename": "LLC4320_pre-SWOT_WesternMed_20110913.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"LLC4320_pre-SWOT_Yongala_20110913.nc": {"collection": "MITgcm_LLC4320_Pre-SWOT_JPL_L4_Yongala_v1.0", "version": "1.0", "direct_link": "s3://podaac-ops-cumulus-protected/MITgcm_LLC4320_Pre-SWOT_JPL_L4_Yongala_v1.0/LLC4320_pre-SWOT_Yongala_20110913.nc", "filename": "LLC4320_pre-SWOT_Yongala_20110913.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"MOD021KM.A2023309.1555.061.2023310011432.hdf": {"collection": "MOD021KM_cloud", "version": "6.1", "direct_link": "s3://prod-lads/MOD021KM_cloud/MOD021KM.A2023309.1555.061.2023310011432.hdf", "filename": "MOD021KM.A2023309.1555.061.2023310011432.hdf", "data_center": "LAADS", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"MOD02HKM.A2000055.0005.061.2017171194850.hdf": {"collection": "MOD02HKM", "version": "6.1", "direct_link": "s3://prod-lads/MOD02HKM/MOD02HKM.A2000055.0005.061.2017171194850.hdf", "filename": "MOD02HKM.A2000055.0005.061.2017171194850.hdf", "data_center": "LAADS", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"MOD02QKM.A2000055.0005.061.2017171194850.hdf": {"collection": "MOD02QKM", "version": "6.1", "direct_link": "s3://prod-lads/MOD02QKM/MOD02QKM.A2000055.0005.061.2017171194850.hdf", "filename": "MOD02QKM.A2000055.0005.061.2017171194850.hdf", "data_center": "LAADS", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"MOD03.A2000054.2355.061.2017171190730.hdf": {"collection": "MOD03", "version": "6.1", "direct_link": "s3://prod-lads/MOD03/MOD03.A2000054.2355.061.2017171190730.hdf", "filename": "MOD03.A2000054.2355.061.2017171190730.hdf", "data_center": "LAADS", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"MOD04_3K.A2000055.0005.061.2017205182659.hdf": {"collection": "MOD04_3K", "version": "6.1", "direct_link": "s3://prod-lads/MOD04_3K/MOD04_3K.A2000055.0005.061.2017205182659.hdf", "filename": "MOD04_3K.A2000055.0005.061.2017205182659.hdf", "data_center": "LAADS", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"MOD06_L2.A2000055.0000.061.2017272125816.hdf": {"collection": "MOD06_L2", "version": "6.1", "direct_link": "s3://prod-lads/MOD06_L2/MOD06_L2.A2000055.0000.061.2017272125816.hdf", "filename": "MOD06_L2.A2000055.0000.061.2017272125816.hdf", "data_center": "LAADS", "fsm_strategy": "Not found", "page_size": "Not found"}}, "Caught exception list index out of range while trying to process file from collection MOD08_D3, version 6.1", "Caught exception list index out of range while trying to process file from collection MOD08_E3, version 6.1", "Caught exception list index out of range while trying to process file from collection MOD08_M3, version 6.1", {"MOD09.A2000055.0005.061.2020037150809.hdf": {"collection": "MOD09", "version": "6.1", "direct_link": "s3://prod-lads/MOD09/MOD09.A2000055.0005.061.2020037150809.hdf", "filename": "MOD09.A2000055.0005.061.2020037150809.hdf", "data_center": "LAADS", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"MOD35_L2.A2000055.0000.061.2017202185902.hdf": {"collection": "MOD35_L2", "version": "6.1", "direct_link": "s3://prod-lads/MOD35_L2/MOD35_L2.A2000055.0000.061.2017202185902.hdf", "filename": "MOD35_L2.A2000055.0000.061.2017202185902.hdf", "data_center": "LAADS", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"20130801133200-OSPO-L2P_GHRSST-SSTskin-MTSAT2-v02.0-fv01.0.nc": {"collection": "MTSAT2-OSPO-L2P-v1.0", "version": "1.0", "direct_link": "s3://podaac-ops-cumulus-protected/MTSAT2-OSPO-L2P-v1.0/2013/213/20130801133200-OSPO-L2P_GHRSST-SSTskin-MTSAT2-v02.0-fv01.0.nc", "filename": "20130801133200-OSPO-L2P_GHRSST-SSTskin-MTSAT2-v02.0-fv01.0.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"MYD05_L2.A2002185.0000.061.2018003214404.hdf": {"collection": "MYD05_L2", "version": "6.1", "direct_link": "s3://prod-lads/MYD05_L2/MYD05_L2.A2002185.0000.061.2018003214404.hdf", "filename": "MYD05_L2.A2002185.0000.061.2018003214404.hdf", "data_center": "LAADS", "fsm_strategy": "Not found", "page_size": "Not found"}}, "Caught exception list index out of range while trying to process file from collection MYD08_E3, version 6.1", "Caught exception list index out of range while trying to process file from collection MYD08_M3, version 6.1", {"MYD09.A2002185.0045.061.2020071150821.hdf": {"collection": "MYD09", "version": "6.1", "direct_link": "s3://prod-lads/MYD09/MYD09.A2002185.0045.061.2020071150821.hdf", "filename": "MYD09.A2002185.0045.061.2020071150821.hdf", "data_center": "LAADS", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"MYD35_L2.A2002185.0000.061.2017363141846.hdf": {"collection": "MYD35_L2", "version": "6.1", "direct_link": "s3://prod-lads/MYD35_L2/MYD35_L2.A2002185.0000.061.2017363141846.hdf", "filename": "MYD35_L2.A2002185.0000.061.2017363141846.hdf", "data_center": "LAADS", "fsm_strategy": "Not found", "page_size": "Not found"}}, "Caught exception list index out of range while trying to process file from collection MYDATML2, version 6.1", {"NSIFv2.6.2.GOME-2B.20130401_all.nc": {"collection": "MetOpB_GOME2_SIF_2182", "version": "1", "direct_link": "s3://ornl-cumulus-prod-protected/sif-esdr/17-MEASURES-0032/MetOpB_GOME2_SIF/data/NSIFv2.6.2.GOME-2B.20130401_all.nc", "filename": "NSIFv2.6.2.GOME-2B.20130401_all.nc", "data_center": "ORNLDAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"mstmip_driver_global_hd_c4_rfrac_presentveg_v1.nc4": {"collection": "NACP_MsTMIP_Model_Driver_1220", "version": "1", "direct_link": "s3://ornl-cumulus-prod-protected/nacp/NACP_MsTMIP_Model_Driver/data/mstmip_driver_global_hd_c4_rfrac_presentveg_v1.nc4", "filename": "mstmip_driver_global_hd_c4_rfrac_presentveg_v1.nc4", "data_center": "ORNLDAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"paleon_reg-env-dri_lulcc.nc4": {"collection": "NACP_PalEON_MIP_1779", "version": "1", "direct_link": "s3://ornl-cumulus-prod-protected/nacp/NACP_PalEON_MIP/data/paleon_reg-env-dri_lulcc.nc4", "filename": "paleon_reg-env-dri_lulcc.nc4", "data_center": "ORNLDAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"PODAAC-NSSDR-17X02_1996-09-15_1997-06-29.zip": {"collection": "NSCAT_LEVEL_1.7_V2", "version": "2", "direct_link": "s3://podaac-ops-cumulus-protected/NSCAT_LEVEL_1.7_V2/PODAAC-NSSDR-17X02_1996-09-15_1997-06-29.zip", "filename": "PODAAC-NSSDR-17X02_1996-09-15_1997-06-29.zip", "data_center": "PODAAC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"PODAAC-NSGDR-L2X02_1996-09-15_1997-06-29.zip": {"collection": "NSCAT_LEVEL_2_V2", "version": "2", "direct_link": "s3://podaac-ops-cumulus-protected/NSCAT_LEVEL_2_V2/PODAAC-NSGDR-L2X02_1996-09-15_1997-06-29.zip", "filename": "PODAAC-NSGDR-L2X02_1996-09-15_1997-06-29.zip", "data_center": "PODAAC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"PODAAC-NSJPL-L3X02_1996-09-15_1997-06-29.zip": {"collection": "NSCAT_LEVEL_3_V2", "version": "2", "direct_link": "s3://podaac-ops-cumulus-protected/NSCAT_LEVEL_3_V2/PODAAC-NSJPL-L3X02_1996-09-15_1997-06-29.zip", "filename": "PODAAC-NSJPL-L3X02_1996-09-15_1997-06-29.zip", "data_center": "PODAAC", "fsm_strategy": "Not found", "page_size": "Not found"}}, "Caught exception An error occurred (403) when calling the HeadObject operation: Forbidden while trying to process file from collection OMG_NARWHALS_MOORING_TEMP_CTD_1.0, version 1.0", "Caught exception An error occurred (403) when calling the HeadObject operation: Forbidden while trying to process file from collection OMG_NARWHALS_SHIPBOARD_CTD_1.0, version 1.0", "Caught exception An error occurred (403) when calling the HeadObject operation: Forbidden while trying to process file from collection OPERA_L2_CSLC-S1-STATIC_V1, version 1", "Caught exception An error occurred (403) when calling the HeadObject operation: Forbidden while trying to process file from collection OPERA_L2_CSLC-S1_CALVAL_V1, version 1", "Caught exception An error occurred (403) when calling the HeadObject operation: Forbidden while trying to process file from collection OPERA_L2_CSLC-S1_V1, version 1", "Caught exception An error occurred (403) when calling the HeadObject operation: Forbidden while trying to process file from collection OPERA_L2_RTC-S1_CALVAL_V1, version 1", "Caught exception An error occurred (403) when calling the HeadObject operation: Forbidden while trying to process file from collection OPERA_L2_RTC-S1_V1, version 1", {"os2_l2b2010016_01665_01666.nc": {"collection": "OS2_OSCAT_LEVEL_2B_OWV_COMP_12_V2", "version": "2", "direct_link": "s3://podaac-ops-cumulus-protected/OS2_OSCAT_LEVEL_2B_OWV_COMP_12_V2/os2_l2b2010016_01665_01666.nc", "filename": "os2_l2b2010016_01665_01666.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"oscar_currents_final_19930101.nc": {"collection": "OSCAR_L4_OC_FINAL_V2.0", "version": "2.0", "direct_link": "s3://podaac-ops-cumulus-protected/OSCAR_L4_OC_FINAL_V2.0/oscar_currents_final_19930101.nc", "filename": "oscar_currents_final_19930101.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, "Caught exception 'accessKeyId' while trying to process file from collection PACE_HARP2_L0_D1, version 1", "Caught exception 'accessKeyId' while trying to process file from collection PACE_HARP2_L0_D2, version 1", "Caught exception 'accessKeyId' while trying to process file from collection PACE_HARP2_L0_D3, version 1", "Caught exception 'accessKeyId' while trying to process file from collection PACE_HARP2_L1A_SCI, version 1", "Caught exception 'accessKeyId' while trying to process file from collection PACE_HARP2_L1B_SCI, version V1.0", "Caught exception 'accessKeyId' while trying to process file from collection PACE_HARP2_L1C_SCI, version V1.0", "Caught exception 'accessKeyId' while trying to process file from collection PACE_HKT, version 1", "Caught exception 'accessKeyId' while trying to process file from collection PACE_HSK, version 1", "Caught exception 'accessKeyId' while trying to process file from collection PACE_OCI_L0_SCI, version 1", "Caught exception 'accessKeyId' while trying to process file from collection PACE_OCI_L1A_SCI, version 1", "Caught exception 'accessKeyId' while trying to process file from collection PACE_OCI_L1B_SCI, version V1.0", "Caught exception 'accessKeyId' while trying to process file from collection PACE_OCI_L1C_SCI, version V1.0", "Caught exception 'accessKeyId' while trying to process file from collection PACE_OCI_L2_AOP_NRT, version V1.0", "Caught exception 'accessKeyId' while trying to process file from collection PACE_OCI_L2_BGC_NRT, version V1.0", "Caught exception 'accessKeyId' while trying to process file from collection PACE_OCI_L2_IOP_NRT, version V1.0", "Caught exception 'accessKeyId' while trying to process file from collection PACE_OCI_L2_PAR_NRT, version V1.0", "Caught exception 'accessKeyId' while trying to process file from collection PACE_OCI_L3B_CHL_NRT, version V1.0", "Caught exception 'accessKeyId' while trying to process file from collection PACE_OCI_L3B_IOP_NRT, version V1.0", "Caught exception 'accessKeyId' while trying to process file from collection PACE_OCI_L3B_KD_NRT, version V1.0", "Caught exception 'accessKeyId' while trying to process file from collection PACE_OCI_L3B_PAR_NRT, version V1.0", "Caught exception 'accessKeyId' while trying to process file from collection PACE_OCI_L3B_POC_NRT, version V1.0", "Caught exception 'accessKeyId' while trying to process file from collection PACE_OCI_L3B_RRS_NRT, version V1.0", "Caught exception 'accessKeyId' while trying to process file from collection PACE_OCI_L3M_CHL_NRT, version V1.0", "Caught exception 'accessKeyId' while trying to process file from collection PACE_OCI_L3M_IOP_NRT, version V1.0", "Caught exception 'accessKeyId' while trying to process file from collection PACE_OCI_L3M_KD_NRT, version V1.0", "Caught exception 'accessKeyId' while trying to process file from collection PACE_OCI_L3M_PAR_NRT, version V1.0", "Caught exception 'accessKeyId' while trying to process file from collection PACE_OCI_L3M_POC_NRT, version V1.0", "Caught exception 'accessKeyId' while trying to process file from collection PACE_OCI_L3M_RRS_NRT, version V1.0", "Caught exception 'accessKeyId' while trying to process file from collection PACE_SPEXONE_L0, version 1", "Caught exception 'accessKeyId' while trying to process file from collection PACE_SPEXONE_L1A_SCI, version 1", "Caught exception 'accessKeyId' while trying to process file from collection PACE_SPEXONE_L1B_SCI, version V1.0", "Caught exception 'accessKeyId' while trying to process file from collection PACE_SPEXONE_L1C_SCI, version V1.0", {"Asia_Yenisei1kmdaily.nc": {"collection": "PRESWOT_HYDRO_GRRATS_L2_DAILY_VIRTUAL_STATION_HEIGHTS_V2", "version": "2", "direct_link": "s3://podaac-ops-cumulus-protected/PRESWOT_HYDRO_GRRATS_L2_DAILY_VIRTUAL_STATION_HEIGHTS_V2/Asia_Yenisei1kmdaily.nc", "filename": "Asia_Yenisei1kmdaily.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"Asia_Ganges_ERS1c_16.nc": {"collection": "PRESWOT_HYDRO_GRRATS_L2_VIRTUAL_STATION_HEIGHTS_V2", "version": "2", "direct_link": "s3://podaac-ops-cumulus-protected/PRESWOT_HYDRO_GRRATS_L2_VIRTUAL_STATION_HEIGHTS_V2/Asia_Ganges_ERS1c_16.nc", "filename": "Asia_Ganges_ERS1c_16.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"South_America_FuroSantaMaria_WaterAreaV2_1765.nc": {"collection": "PRESWOT_HYDRO_L3_LAKE_RESEVOIR_AREA_V2", "version": "2", "direct_link": "s3://podaac-ops-cumulus-protected/PRESWOT_HYDRO_L3_LAKE_RESEVOIR_AREA_V2/South_America_FuroSantaMaria_WaterAreaV2_1765.nc", "filename": "South_America_FuroSantaMaria_WaterAreaV2_1765.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"US-MMS_Morgan_Monroe_State_Forest_interactive_map.html": {"collection": "Phenology_AmeriFlux_Neon_Sites_2033", "version": "1", "direct_link": "s3://ornl-cumulus-prod-protected/global_vegetation/Phenology_AmeriFlux_Neon_Sites/data/US-MMS_Morgan_Monroe_State_Forest_interactive_map.html", "filename": "US-MMS_Morgan_Monroe_State_Forest_interactive_map.html", "data_center": "ORNLDAAC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"measures_esdr_qs_l2_wind_stress_39239_v1.0_s20070101-002110-e20070101-020210_ancillary.nc": {"collection": "QSCAT_ESDR_MODELED_L2_AUX_V1.0", "version": "1.0", "direct_link": "s3://podaac-ops-cumulus-protected/QSCAT_ESDR_MODELED_L2_AUX_V1.0/2007/001/measures_esdr_qs_l2_wind_stress_39239_v1.0_s20070101-002110-e20070101-020210_ancillary.nc", "filename": "measures_esdr_qs_l2_wind_stress_39239_v1.0_s20070101-002110-e20070101-020210_ancillary.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"qs_l2b_01853_v3_199910271518.nc": {"collection": "QSCAT_LEVEL_2B_OWV_COMP_12", "version": "3", "direct_link": "s3://podaac-ops-cumulus-protected/QSCAT_LEVEL_2B_OWV_COMP_12/1999/300/qs_l2b_01853_v3_199910271518.nc", "filename": "qs_l2b_01853_v3_199910271518.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"qs_l2b_01853_v4.1_199910271518.nc": {"collection": "QSCAT_LEVEL_2B_OWV_COMP_12_KUSST_LCRES_4.1", "version": "4.1", "direct_link": "s3://podaac-ops-cumulus-protected/QSCAT_LEVEL_2B_OWV_COMP_12_KUSST_LCRES_4.1/qs_l2b_01853_v4.1_199910271518.nc", "filename": "qs_l2b_01853_v4.1_199910271518.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, "Caught exception HTTPSConnectionPool(host='urs.earthdata.nasa.gov', port=443): Read timed out. (read timeout=15) while trying to process file from collection QSCAT_LEVEL_2B_OWV_COMP_12_LCR_3.1, version 3.1", {"rs_radrain_l2b_v1_00161_201608251425.nc": {"collection": "RSCAT_COLOCATED_RSS_RADIOMETER_LEVEL_2B_V1", "version": "1.0", "direct_link": "s3://podaac-ops-cumulus-protected/RSCAT_COLOCATED_RSS_RADIOMETER_LEVEL_2B_V1/2014/276/rs_radrain_l2b_v1_00161_201608251425.nc", "filename": "rs_radrain_l2b_v1_00161_201608251425.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"RS_S1B00161.20150990917.hdf": {"collection": "RSCAT_L1B_V2.0", "version": "2.0", "direct_link": "s3://podaac-ops-cumulus-protected/RSCAT_L1B_V2.0/RS_S1B00161.20150990917.hdf", "filename": "RS_S1B00161.20150990917.hdf", "data_center": "PODAAC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"RS_S2A00161.20150990920.hdf": {"collection": "RSCAT_L2A_25KM_V2.0", "version": "2.0", "direct_link": "s3://podaac-ops-cumulus-protected/RSCAT_L2A_25KM_V2.0/RS_S2A00161.20150990920.hdf", "filename": "RS_S2A00161.20150990920.hdf", "data_center": "PODAAC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"rs_l2b_v1.0_climate_00161_201603171006.nc": {"collection": "RSCAT_LEVEL_2B_OWV_CLIM_12_V1", "version": "1.0", "direct_link": "s3://podaac-ops-cumulus-protected/RSCAT_LEVEL_2B_OWV_CLIM_12_V1/2014/276/rs_l2b_v1.0_climate_00161_201603171006.nc", "filename": "rs_l2b_v1.0_climate_00161_201603171006.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"rs_l2b_v2.0_climate_00228_201801260652.nc": {"collection": "RSCAT_LEVEL_2B_OWV_CLIM_12_V2", "version": "2.0", "direct_link": "s3://podaac-ops-cumulus-protected/RSCAT_LEVEL_2B_OWV_CLIM_12_V2/rs_l2b_v2.0_climate_00228_201801260652.nc", "filename": "rs_l2b_v2.0_climate_00228_201801260652.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"rs_l2b_v1.2_05127_201603171005.nc": {"collection": "RSCAT_LEVEL_2B_OWV_COMP_12_V1.2", "version": "1.2", "direct_link": "s3://podaac-ops-cumulus-protected/RSCAT_LEVEL_2B_OWV_COMP_12_V1.2/2015/231/rs_l2b_v1.2_05127_201603171005.nc", "filename": "rs_l2b_v1.2_05127_201603171005.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"rs_l2b_v1.3_07873_201609280704.nc": {"collection": "RSCAT_LEVEL_2B_OWV_COMP_12_V1.3", "version": "1.3", "direct_link": "s3://podaac-ops-cumulus-protected/RSCAT_LEVEL_2B_OWV_COMP_12_V1.3/2016/042/rs_l2b_v1.3_07873_201609280704.nc", "filename": "rs_l2b_v1.3_07873_201609280704.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"saildrone-gen_4-baja_2018-sd1002-20180411T180000-20180611T055959-1_minutes-v1.nc": {"collection": "SAILDRONE_BAJA_SURFACE", "version": "1.0", "direct_link": "s3://podaac-ops-cumulus-protected/SAILDRONE_BAJA_SURFACE/saildrone-gen_4-baja_2018-sd1002-20180411T180000-20180611T055959-1_minutes-v1.nc", "filename": "saildrone-gen_4-baja_2018-sd1002-20180411T180000-20180611T055959-1_minutes-v1.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"measures_esdr_scatsat_l2_wind_stress_08002_v1.0_s20180401-011908-e20180401-025826.nc": {"collection": "SCATSAT1_ESDR_L2_WIND_STRESS_V1.0", "version": "1.0", "direct_link": "s3://podaac-ops-cumulus-protected/SCATSAT1_ESDR_L2_WIND_STRESS_V1.0/2018/091/measures_esdr_scatsat_l2_wind_stress_08002_v1.0_s20180401-011908-e20180401-025826.nc", "filename": "measures_esdr_scatsat_l2_wind_stress_08002_v1.0_s20180401-011908-e20180401-025826.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"measures_esdr_scatsat_l2_wind_stress_08002_v1.0_s20180401-011908-e20180401-025826_ancillary.nc": {"collection": "SCATSAT1_ESDR_MODELED_L2_AUX_V1.0", "version": "1.0", "direct_link": "s3://podaac-ops-cumulus-protected/SCATSAT1_ESDR_MODELED_L2_AUX_V1.0/2018/091/measures_esdr_scatsat_l2_wind_stress_08002_v1.0_s20180401-011908-e20180401-025826_ancillary.nc", "filename": "measures_esdr_scatsat_l2_wind_stress_08002_v1.0_s20180401-011908-e20180401-025826_ancillary.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"sg178_Oct2019_data_L2.nc": {"collection": "SEAGLIDER_GUAM_2019", "version": "V1", "direct_link": "s3://podaac-ops-cumulus-protected/SEAGLIDER_GUAM_2019/sg178_Oct2019_data_L2.nc", "filename": "sg178_Oct2019_data_L2.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"20040119120000-OSISAF-L3C_GHRSST-SSTsubskin-SEVIRI_SST-dr_ssteqc_meteosat08_20040119_120000-v02.0-fv01.0.nc": {"collection": "SEVIRI_SST_DR-OSISAF-L3C-v1.0", "version": "1.0", "direct_link": "s3://podaac-ops-cumulus-protected/SEVIRI_SST_DR-OSISAF-L3C-v1.0/2004/019/20040119120000-OSISAF-L3C_GHRSST-SSTsubskin-SEVIRI_SST-dr_ssteqc_meteosat08_20040119_120000-v02.0-fv01.0.nc", "filename": "20040119120000-OSISAF-L3C_GHRSST-SSTsubskin-SEVIRI_SST-dr_ssteqc_meteosat08_20040119_120000-v02.0-fv01.0.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, "Caught exception list index out of range while trying to process file from collection SMAP_RSS_L3_SSS_SMI_MONTHLY_V4, version 4.0", {"SMODE_IOP1_prm20221019t184425_rdn_img": {"collection": "SMODE_L1_PRISM_V1", "version": "1", "direct_link": "s3://podaac-ops-cumulus-protected/SMODE_L1_PRISM_V1/SMODE_IOP1_prm20221019t184425_rdn_img", "filename": "SMODE_IOP1_prm20221019t184425_rdn_img", "data_center": "PODAAC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"dopplerscatt_20211020_140315.tomoL2CF.nc": {"collection": "SMODE_L2_DOPPLERSCATT_WINDS_CURRENT_V1", "version": "1", "direct_link": "s3://podaac-ops-cumulus-protected/SMODE_L2_DOPPLERSCATT_WINDS_CURRENT_V1/dopplerscatt_20211020_140315.tomoL2CF.nc", "filename": "dopplerscatt_20211020_140315.tomoL2CF.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"SPURS_knorr_ADCP_os75nb.nc": {"collection": "SPURS1_ADCP", "version": "1.0", "direct_link": "s3://podaac-ops-cumulus-protected/SPURS1_ADCP/SPURS_knorr_ADCP_os75nb.nc", "filename": "SPURS_knorr_ADCP_os75nb.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"argo-profiles-5903997.nc": {"collection": "SPURS1_ARGO", "version": "1.0", "direct_link": "s3://podaac-ops-cumulus-protected/SPURS1_ARGO/argo-profiles-5903997.nc", "filename": "argo-profiles-5903997.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"SPURS_Thalassa_CTD.nc": {"collection": "SPURS1_CTD", "version": "1.0", "direct_link": "s3://podaac-ops-cumulus-protected/SPURS1_CTD/SPURS_Thalassa_CTD.nc", "filename": "SPURS_Thalassa_CTD.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"SPURS_drifter_all.nc": {"collection": "SPURS1_DRIFTER", "version": "1.0", "direct_link": "s3://podaac-ops-cumulus-protected/SPURS1_DRIFTER/SPURS_drifter_all.nc", "filename": "SPURS_drifter_all.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"SPURS_Knorr_Ecomapper2.nc": {"collection": "SPURS1_ECOMAPPER", "version": "1.0", "direct_link": "s3://podaac-ops-cumulus-protected/SPURS1_ECOMAPPER/SPURS_Knorr_Ecomapper2.nc", "filename": "SPURS_Knorr_Ecomapper2.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"SPURS_Neutrally_Buoyant_Float_73.nc": {"collection": "SPURS1_FLOAT_NEUTRALLYBUOYANT", "version": "1.0", "direct_link": "s3://podaac-ops-cumulus-protected/SPURS1_FLOAT_NEUTRALLYBUOYANT/SPURS_Neutrally_Buoyant_Float_73.nc", "filename": "SPURS_Neutrally_Buoyant_Float_73.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"SPURS_Endeavor1_meteorological.nc": {"collection": "SPURS1_METEO", "version": "1.0", "direct_link": "s3://podaac-ops-cumulus-protected/SPURS1_METEO/SPURS_Endeavor1_meteorological.nc", "filename": "SPURS_Endeavor1_meteorological.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"spurs_pico1000_ctd.nc": {"collection": "SPURS1_MOORING_PICO", "version": "1.0", "direct_link": "s3://podaac-ops-cumulus-protected/SPURS1_MOORING_PICO/spurs_pico1000_ctd.nc", "filename": "spurs_pico1000_ctd.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"SPURS_Sarmiento_seasoar.nc": {"collection": "SPURS1_SEASOAR", "version": "1.0", "direct_link": "s3://podaac-ops-cumulus-protected/SPURS1_SEASOAR/SPURS_Sarmiento_seasoar.nc", "filename": "SPURS_Sarmiento_seasoar.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"SPURS_wg_ASL32.nc": {"collection": "SPURS1_WAVEGLIDER", "version": "1.0", "direct_link": "s3://podaac-ops-cumulus-protected/SPURS1_WAVEGLIDER/SPURS_wg_ASL32.nc", "filename": "SPURS_wg_ASL32.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"SPURS2_RR1610_CTD_01.nc": {"collection": "SPURS2_CTD", "version": "1.0", "direct_link": "s3://podaac-ops-cumulus-protected/SPURS2_CTD/SPURS2_RR1610_CTD_01.nc", "filename": "SPURS2_RR1610_CTD_01.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"SPURS2_RR1610_WHOI_Met.nc": {"collection": "SPURS2_METEO", "version": "1.0", "direct_link": "s3://podaac-ops-cumulus-protected/SPURS2_METEO/SPURS2_RR1610_WHOI_Met.nc", "filename": "SPURS2_RR1610_WHOI_Met.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"SPURS2_CentralMooring_SubsurfaceTemperature.nc": {"collection": "SPURS2_MOORING_CENTRAL", "version": "1.0", "direct_link": "s3://podaac-ops-cumulus-protected/SPURS2_MOORING_CENTRAL/SPURS2_CentralMooring_SubsurfaceTemperature.nc", "filename": "SPURS2_CentralMooring_SubsurfaceTemperature.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"SPURS2_Saildrone1005.nc": {"collection": "SPURS2_SAILDRONE", "version": "1.0", "direct_link": "s3://podaac-ops-cumulus-protected/SPURS2_SAILDRONE/SPURS2_Saildrone1005.nc", "filename": "SPURS2_Saildrone1005.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"SPURS2_RR1720_wamoswaves.nc": {"collection": "SPURS2_WAMOS", "version": "1.0", "direct_link": "s3://podaac-ops-cumulus-protected/SPURS2_WAMOS/SPURS2_RR1720_wamoswaves.nc", "filename": "SPURS2_RR1720_wamoswaves.nc", "data_center": "PODAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, "Caught exception An error occurred (403) when calling the HeadObject operation: Forbidden while trying to process file from collection SWOT_L2_HR_Raster_100m_2.0, version 2.0", "Caught exception An error occurred (403) when calling the HeadObject operation: Forbidden while trying to process file from collection SWOT_L2_HR_Raster_250m_2.0, version 2.0", "Caught exception An error occurred (403) when calling the HeadObject operation: Forbidden while trying to process file from collection SWOT_L2_LR_SSH_BASIC_2.0, version 2.0", "Caught exception An error occurred (403) when calling the HeadObject operation: Forbidden while trying to process file from collection SWOT_L2_LR_SSH_EXPERT_2.0, version 2.0", "Caught exception An error occurred (403) when calling the HeadObject operation: Forbidden while trying to process file from collection SWOT_L2_LR_SSH_UNSMOOTHED_2.0, version 2.0", "Caught exception An error occurred (403) when calling the HeadObject operation: Forbidden while trying to process file from collection SWOT_L2_LR_SSH_WINDWAVE_2.0, version 2.0", "Caught exception An error occurred (403) when calling the HeadObject operation: Forbidden while trying to process file from collection SWOT_L2_NALT_GDR_GDR_2.0, version 2.0", "Caught exception An error occurred (403) when calling the HeadObject operation: Forbidden while trying to process file from collection SWOT_L2_NALT_GDR_SGDR_2.0, version 2.0", "Caught exception An error occurred (403) when calling the HeadObject operation: Forbidden while trying to process file from collection SWOT_L2_NALT_GDR_SSHA_2.0, version 2.0", "Caught exception An error occurred (403) when calling the HeadObject operation: Forbidden while trying to process file from collection SWOT_L2_NALT_IGDR_GDR_1.0, version 1.0", "Caught exception An error occurred (403) when calling the HeadObject operation: Forbidden while trying to process file from collection SWOT_L2_NALT_IGDR_GDR_2.0, version 2.0", "Caught exception An error occurred (403) when calling the HeadObject operation: Forbidden while trying to process file from collection SWOT_L2_NALT_IGDR_SGDR_1.0, version 1.0", "Caught exception An error occurred (403) when calling the HeadObject operation: Forbidden while trying to process file from collection SWOT_L2_NALT_IGDR_SGDR_2.0, version 2.0", "Caught exception An error occurred (403) when calling the HeadObject operation: Forbidden while trying to process file from collection SWOT_L2_NALT_IGDR_SSHA_1.0, version 1.0", "Caught exception An error occurred (403) when calling the HeadObject operation: Forbidden while trying to process file from collection SWOT_L2_NALT_IGDR_SSHA_2.0, version 2.0", "Caught exception An error occurred (403) when calling the HeadObject operation: Forbidden while trying to process file from collection SWOT_L2_NALT_OGDR_GDR_1.0, version 1.0", "Caught exception An error occurred (403) when calling the HeadObject operation: Forbidden while trying to process file from collection SWOT_L2_NALT_OGDR_GDR_2.0, version 2.0", "Caught exception An error occurred (403) when calling the HeadObject operation: Forbidden while trying to process file from collection SWOT_L2_NALT_OGDR_SSHA_1.0, version 1.0", "Caught exception An error occurred (403) when calling the HeadObject operation: Forbidden while trying to process file from collection SWOT_L2_NALT_OGDR_SSHA_2.0, version 2.0", "Caught exception HTTPSConnectionPool(host='urs.earthdata.nasa.gov', port=443): Read timed out. 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{"f13_ssmi_199505v7.nc": {"collection": "rssmif13m", "version": "7", "direct_link": "s3://ghrcw-protected/rssmif13m__7/f13_ssmi_199505v7.nc", "filename": "f13_ssmi_199505v7.nc", "data_center": "GHRCDAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"f13_ssmi_19950506v7_wk.nc": {"collection": "rssmif13w", "version": "7", "direct_link": "s3://ghrcw-protected/rssmif13w__7/f13_ssmi_19950506v7_wk.nc", "filename": "f13_ssmi_19950506v7_wk.nc", "data_center": "GHRCDAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"f14_ssmi_19970508v7_d3d.nc": {"collection": "rssmif14d3d", "version": "7", "direct_link": "s3://ghrcw-protected/rssmif14d3d__7/f14_ssmi_19970508v7_d3d.nc", "filename": "f14_ssmi_19970508v7_d3d.nc", "data_center": "GHRCDAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"f14_ssmi_199705v7.nc": {"collection": "rssmif14m", "version": "7", "direct_link": "s3://ghrcw-protected/rssmif14m__7/f14_ssmi_199705v7.nc", "filename": "f14_ssmi_199705v7.nc", "data_center": "GHRCDAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"f14_ssmi_19970510v7_wk.nc": {"collection": "rssmif14w", "version": "7", "direct_link": "s3://ghrcw-protected/rssmif14w__7/f14_ssmi_19970510v7_wk.nc", "filename": "f14_ssmi_19970510v7_wk.nc", "data_center": "GHRCDAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"f15_ssmi_19991218v7_d3d.nc": {"collection": "rssmif15d3d", "version": "7", "direct_link": "s3://ghrcw-protected/rssmif15d3d__7/f15_ssmi_19991218v7_d3d.nc", "filename": "f15_ssmi_19991218v7_d3d.nc", "data_center": "GHRCDAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}, {"f15_ssmi_199912v7.nc": {"collection": "rssmif15m", "version": "7", "direct_link": "s3://ghrcw-protected/rssmif15m__7/f15_ssmi_199912v7.nc", "filename": "f15_ssmi_199912v7.nc", "data_center": "GHRCDAAC", 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found", "page_size": "Not found"}}, {"tcsp_hamsr_20050702_1426.hdf": {"collection": "tcsphamsr", "version": "1", "direct_link": "s3://ghrcw-protected/tcsphamsr__1/tcsp_hamsr_20050702_1426.hdf", "filename": "tcsp_hamsr_20050702_1426.hdf", "data_center": "GHRCDAAC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"TRMM_LBA_ER2_LIP_v1_1999.023_029.hdf": {"collection": "trmlbalip", "version": "1", "direct_link": "s3://ghrcw-protected/trmlbalip__1/TRMM_LBA_ER2_LIP_v1_1999.023_029.hdf", "filename": "TRMM_LBA_ER2_LIP_v1_1999.023_029.hdf", "data_center": "GHRCDAAC", "fsm_strategy": "Not found", "page_size": "Not found"}}, {"historical_climate_alaska_1922-1996.nc4": {"collection": "vemap-1_VEMAP_Alaska_1344", "version": "1", "direct_link": "s3://ornl-cumulus-prod-protected/vemap/vemap-1_VEMAP_Alaska/data/historical_climate_alaska_1922-1996.nc4", "filename": "historical_climate_alaska_1922-1996.nc4", "data_center": "ORNLDAAC", "fsm_strategy": "H5F_FSPACE_STRATEGY_FSM_AGGR", "page_size": "4096"}}]
\ No newline at end of file
diff --git a/testing.ipynb b/testing.ipynb
new file mode 100644
index 0000000..a34c672
--- /dev/null
+++ b/testing.ipynb
@@ -0,0 +1,118 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "a41ce147-ad98-458b-8b7e-0b4e0225e2e5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from h5cloud.test_config import TestConfig\n",
+    "from h5cloud.tests.h5py_arr_mean import H5pyArrMean"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "9295494d-3a0c-4f10-825f-a1518b6654f5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "tc = TestConfig.load_from_yaml(yaml_file=\"h5cloud/file_configs/atl03.yml\", results_bucket=\"eodc-scratch\", results_directory=\"h5cloud-tests/test-results\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "ad0bacb0-5411-4ae0-97c4-aa2ad616eeb5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "h5py_arr_test = H5pyArrMean(tc)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "d0d09814-311d-412a-9b8e-563a5c3c4066",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "og_result = h5py_arr_test.run('original')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "6e7a1b92-360f-4f38-b0a1-8afaf46e5e41",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "repacked_result = h5py_arr_test.run('repack_page_4gb')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "3a1e1e76-5a66-4458-8088-396d4b955853",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(210.20262049342506, 4.287616014480591)"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "og_result"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "d5caf12b-d703-43c5-b1ef-ccca578e467d",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(210.20262049342506, 0.8477990627288818)"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "repacked_result"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}