SimVP Global SSH Maps 2019
收藏DataCite Commons2024-11-12 更新2025-04-15 收录
下载链接：
https://dataverse.harvard.edu/citation?persistentId=doi:10.7910/DVN/H4HQGD
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资源简介：
High-resolution global maps of sea surface height, surface geostrophic currents, relative vorticity, and strain rate created using deep learning neural network, SimVP, from satellite altimeter and sea surface temperature observations. Maps are provided for the year 2019 (which was never seen during training) and were created using all altimeters apart from Saral/Altika to allow independent evaluation of the mapped SSH. For more details, see our paper (https://doi.org/10.31223/X5W676). A longer time-series of these maps is under development and we plan to distribute these through NASA PO.DAAC in the future.
提供机构：
Harvard Dataverse
创建时间：
2023-12-11
