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DGGS-Zarr Pipeline Validation Results
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The claim is supported: EarthCARE Level-2 products from the Multi-Spectral Imager (MSI), Atmospheric Lidar (ATLID), and Cloud Profiling Radar (CPR) convert end-to-end to HEALPix Discrete Global Grid System cells on the WGS84 ellipsoid while preserving variable-type aggregation semantics. Cross-instrument co-location via shared cell identifiers is also demonstrated. All four data patterns (MSI 2D swath, ATLID 1D profiles, CPR 1D profiles, and co-located multi-instrument composites) round-trip successfully through DGGS-Zarr persistence.
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Seven executable Jupyter notebooks in the earthcare-dggs repository (archived at https://doi.org/10.5281/zenodo.19709327) demonstrate the full pipeline on nine operational Level-2A products (MSI_AOT_2A, MSI_COP_2A, ATL_AER_2A, ATL_ALD_2A, ATL_CTH_2A, ATL_EBD_2A, ATL_ICE_2A, CPR_CLD_2A, CPR_FMR_2A). Type-appropriate aggregation verified: mode for classification variables (cloud/aerosol flags), mean for continuous variables (optical depth, backscatter), quadrature for uncertainty variables. DGGS-Zarr round-trip verified. WGS84 geodetic placement provided by healpix-geo. Reproducible Pixi environment published with the release.
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This outcome reflects the first implementation of the claim. Independent third-party replication using different software stacks (e.g., alternative DGGS libraries, non-Python implementations) would strengthen confidence further. Performance characteristics (memory, throughput) have not been systematically benchmarked across full-orbit or multi-day product volumes. BBR products were not tested in the v0.1.0 release.
Github repository: https://github.com/annefou/earthcare-dggs
&
HTML pages: annefou.github.io/earthcare-dggs/
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Anne Fouilloux
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