NeurOST-SSH Maps for Ocean Data Challenge 2023a_SSH_mapping_OSE
- zenodo.org
zipUpdated Sep 12, 2024
Share
Facebook
Twitter
EmailClick to copy linkLink copiedCiteScott Martin; Scott Martin (2024). NeurOST-SSH Maps for Ocean Data Challenge 2023a_SSH_mapping_OSE [Dataset]. http://doi.org/10.5281/zenodo.13755409zipAvailable download formatsUnique identifierhttps://doi.org/10.5281/zenodo.13755409Dataset updatedSep 12, 2024AuthorsScott Martin; Scott MartinLicenseAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automaticallyDescriptionGlobal maps of sea surface height (SSH) and surface geostrophic currents generated using NeurOST, a deep learning for mapping SSH from nadir satellite altimetry and sea surface temperature, generated for the observing system experiment outlined in the Ocean Data Challenge '2023a_SSH_mapping_OSE'.
Ocean Data Challenge link: https://github.com/ocean-data-challenges/2023a_SSH_mapping_OSE/tree/main
These maps were made using only L3 SSH (not including SST).
NeurOST citations:
- Martin, S. A., Manucharyan, G. E., and Klein, P. (2024). Deep Learning Improves Global Satellite Observations of Ocean Eddy Dynamics. Geophysical Research Letters, 51, e2024GL110059. https://doi.org/10.1029/2024GL110059
- Martin, S. A., Manucharyan, G. E., and Klein, P. (2023). Synthesizing Sea Surface Temperature and Satellite Altimetry Observations Using Deep Learning Improves the Accuracy and Resolution of Gridded Sea Surface Height Anomalies. Journal of Advances in Modeling Earth Systems, 15, e2022MS003589. https://doi.org/10.1029/2022MS003589
Not seeing a result you expected?
Learn how you can add new datasets to our index.
FacebookTwitterEmailAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Global maps of sea surface height (SSH) and surface geostrophic currents generated using NeurOST, a deep learning for mapping SSH from nadir satellite altimetry and sea surface temperature, generated for the observing system experiment outlined in the Ocean Data Challenge '2023a_SSH_mapping_OSE'.
Ocean Data Challenge link: https://github.com/ocean-data-challenges/2023a_SSH_mapping_OSE/tree/main
These maps were made using only L3 SSH (not including SST).
NeurOST citations:
- Martin, S. A., Manucharyan, G. E., and Klein, P. (2024). Deep Learning Improves Global Satellite Observations of Ocean Eddy Dynamics. Geophysical Research Letters, 51, e2024GL110059. https://doi.org/10.1029/2024GL110059
- Martin, S. A., Manucharyan, G. E., and Klein, P. (2023). Synthesizing Sea Surface Temperature and Satellite Altimetry Observations Using Deep Learning Improves the Accuracy and Resolution of Gridded Sea Surface Height Anomalies. Journal of Advances in Modeling Earth Systems, 15, e2022MS003589. https://doi.org/10.1029/2022MS003589