Articles | Volume 17, issue 10
https://doi.org/10.5194/essd-17-5039-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-17-5039-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
01 Oct 2025
Data description paper |
| 01 Oct 2025
| 01 Oct 2025
P-LSHv2: a multi-decadal global daily evapotranspiration dataset enhanced with explicit soil moisture constraints
Jin Feng
State Key Laboratory of Water Disaster Prevention, and College of Hydrology and Water Resources, Hohai University, Nanjing, Jiangsu, 210024, China
China Meteorological Administration Hydro-Meteorology Key Laboratory, Hohai University, Nanjing, Jiangsu, 210024, China
Hydrology Management Center of Zhejiang Province, Hangzhou, Zhejiang, 310009, China
State Key Laboratory of Water Disaster Prevention, and College of Hydrology and Water Resources, Hohai University, Nanjing, Jiangsu, 210024, China
Yangtze Institute for Conservation and Development, Hohai University, Nanjing, Jiangsu, 210024, China
China Meteorological Administration Hydro-Meteorology Key Laboratory, Hohai University, Nanjing, Jiangsu, 210024, China
Key Laboratory of Water Big Data Technology of Ministry of Water Resources, Hohai University, Nanjing, Jiangsu, 210024, China
Lijun Chao
State Key Laboratory of Water Disaster Prevention, and College of Hydrology and Water Resources, Hohai University, Nanjing, Jiangsu, 210024, China
China Meteorological Administration Hydro-Meteorology Key Laboratory, Hohai University, Nanjing, Jiangsu, 210024, China
Huijie Zhan
State Key Laboratory of Water Disaster Prevention, and College of Hydrology and Water Resources, Hohai University, Nanjing, Jiangsu, 210024, China
Yunping Li
State Key Laboratory of Water Disaster Prevention, and College of Hydrology and Water Resources, Hohai University, Nanjing, Jiangsu, 210024, China
China Meteorological Administration Hydro-Meteorology Key Laboratory, Hohai University, Nanjing, Jiangsu, 210024, China
College of Water Resources, North China University of Water Resources and Electric Power, Zhengzhou, 450046, China
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Short summary
Understanding how soil moisture affects evapotranspiration (ET) is essential for improving ET estimates. However, many global ET datasets overlook soil moisture constraints, causing large uncertainties. In this study, we developed an improved model that better captures the influence of soil moisture on vegetation and soil evaporation. Our model significantly improves ET estimation accuracy and provides a new long-term global ET dataset to support water cycle and climate research.
Understanding how soil moisture affects evapotranspiration (ET) is essential for improving ET...
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