Articles | Volume 30, issue 15
https://doi.org/10.5194/hess-30-4927-2026
https://doi.org/10.5194/hess-30-4927-2026
Research article
 | 
05 Aug 2026
Research article |  | 05 Aug 2026

Near real-time estimation of daytime and nighttime evapotranspiration using GOES-R observations and machine learning models

Sadegh Ranjbar, Danielle Losos, Sophie Hoffman, Yafang Zhong, Jason A. Otkin, Ankur R. Desai, Martha C. Anderson, Christopher R. Hain, and Paul C. Stoy

Data sets

GOES-R Land Surface Products at AmeriFlux and NEON, Inc. Eddy Covariance Tower Locations Danielle Losos et al. https://doi.org/10.6073/pasta/c3bb20a62edbf8548cbb30e79a689a5b

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Short summary
Water moves from land to air in a process called evapotranspiration, which affects weather, crops, and water supply. Using satellites and AI, we created a system that tracks this water movement every five minutes, day and night, even through clouds. This provides continuous insights that can help manage water, predict weather, and better understand the water cycle.
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