Learning Global Evapotranspiration Dataset Corrections from a Water Cycle Closure Supervision

Learning Global Evapotranspiration Dataset Corrections from a Water Cycle Closure Supervision

Evapotranspiration (<i>E</i>) is one of the most uncertain components of the global water cycle (WC). Improving global <i>E</i> estimates is necessary to improve our understanding of climate and its impact on available surface water resources. This work presents a methodology...

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Bibliographic Details
Main Authors: Tristan Hascoet, Victor Pellet, Filipe Aires, Tetsuya Takiguchi
Format: Article
Language:English
Published: MDPI AG 2023-12-01
Series:Remote Sensing
Subjects:
water cycle
machine learning
optimal interpolation
Online Access:https://www.mdpi.com/2072-4292/16/1/170

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