GRACE-SeDA: A global total water storage anomaly product with a spatial resolution of 0.5 degrees from self-supervised data assimilation ...
The monthly total water storage anomaly products with a spatial resolution of 0.5 degrees cover global land areas except for Greenland and Antarctica. The products are generated by applying a self-supervised deep learning model, which assimilates the GRACE(-FO) products and hydrological models. For...
| Main Authors: | , |
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| Format: | Dataset |
| Language: | English |
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ETH Zurich
2023
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| Subjects: | |
| Online Access: | https://dx.doi.org/10.3929/ethz-b-000648738 http://hdl.handle.net/20.500.11850/648738 |
| Summary: | The monthly total water storage anomaly products with a spatial resolution of 0.5 degrees cover global land areas except for Greenland and Antarctica. The products are generated by applying a self-supervised deep learning model, which assimilates the GRACE(-FO) products and hydrological models. For more details about methodology and evaluations, please refer to the associated paper "Global high-resolution total water storage anomalies from self-supervised data assimilation using deep learning algorithms" published in Nature Water (https://doi.org/10.1038/s44221-024-00194-w). ... |
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