Dataset Open Access
A Deep Learning-Based Hybrid Model of Global Terrestrial Evaporation
Koppa, Akash;
Rains, Dominik;
Hulsman, Petra;
Miralles, Diego G.
BibTeX Export
@dataset{koppa_akash_2021_5220753,
author = {Koppa, Akash and
Rains, Dominik and
Hulsman, Petra and
Miralles, Diego G.},
title = {{A Deep Learning-Based Hybrid Model of Global
Terrestrial Evaporation}},
month = aug,
year = 2021,
publisher = {Zenodo},
doi = {10.5281/zenodo.5220753},
url = {https://doi.org/10.5281/zenodo.5220753}
}
924
6,466
views
downloads
| All versions | This version | |
|---|---|---|
| Views | 924 | 512 |
| Downloads | 6,466 | 5,969 |
| Data volume | 181.2 TB | 169.5 TB |
| Unique views | 787 | 467 |
| Unique downloads | 255 | 125 |
Indexed in
- Publication date:
- August 19, 2021
- DOI:
-
- Keyword(s):
- Deep learning Hybrid Modeling Evaporation Evaporative Stress Transpiration GLEAM Machine Learning Earth System Modeling
- Grants:
-
European Commission:
-
DOWN2EARTH - DOWN2EARTH: Translation of climate information into multilevel decision support for social adaptation, policy development, and resilience to water scarcity in the Horn of Africa Drylands (869550)
- DRY-2-DRY - Do droughts self-propagate and self-intensify? (715254)
-
DOWN2EARTH - DOWN2EARTH: Translation of climate information into multilevel decision support for social adaptation, policy development, and resilience to water scarcity in the Horn of Africa Drylands (869550)
- License (for files):
- Creative Commons Attribution 4.0 International