P-LSHv2: a multi-decadal global daily evapotranspiration dataset enhanced with explicit soil moisture constraints

作者：Feng Jin, Ke Zhang, Lijun Chao, Huijie Zhan, Yunping Li · 发表于：Earth system science data · 年份：2025 · DOI：10.5194/essd-17-5039-2025 · 被引用次数：6 · 研究领域：Plant Water Relations and Carbon Dynamics、Soil Moisture and Remote Sensing、Hydrology and Watershed Management Studies

Abstract. Accurately quantifying the impact of soil water availability on evapotranspiration (ET) is crucial for improving ET retrieval accuracy. However, most global satellite-derived ET datasets do not explicitly incorporate soil moisture constraints, leading to significant uncertainties, particularly in water-limited regions. In this study, we propose an enhanced soil moisture constraint scheme that effectively captures soil moisture's influence on vegetation transpiration and soil evaporation using a quantile-based approach. Unlike previous methods, this scheme relies solely on soil moisture data, reducing uncertainties associated with heterogeneous soil hydraulic properties. We integrated this approach into the process-based land surface ET/heat fluxes algorithm (P-LSH, or P-LSHv1), developing an improved version, P-LSHv2. Using observations from 106 global flux towers, we calibrated biome- and climate-specific parameters and quantified moisture constraints across diverse climates and land cover types. P-LSHv2 achieves notable improvements in ET estimation, with a reduced Root Mean Square Error (RMSE) of 0.67 mm d−1 and an increased Pearson correlation coefficient (R) of 0.81, indicating strong agreement with flux tower observations. As a result of these improvements, P-LSHv2 outperforming its predecessor, P-LSHv1, particularly in arid regions. Comparative analyses show that P-LSHv2 surpasses the Penman-Monteith-Leuning model and the Global Land Evaporation Amsterdam Mod...