A multimodal machine learning fused global 0.1° daily evapotranspiration dataset from 1950-2022
Xu Q, Li L, Wei Z, Lu X, Wei N, Lee X, Dai Y. A multimodal machine learning fused global 0.1° daily evapotranspiration dataset from 1950-2022. Agricultural And Forest Meteorology 2025, 372: 110645. DOI: 10.1016/j.agrformet.2025.110645.Peer-Reviewed Original ResearchET datasetsET productsShort temporal coverageLand surface modelsCoarse spatial resolutionIn situ observationsIn situ measurementsFlux tower observationsAtmospheric forcingReanalysis dataEvapotranspiration datasetsRegional hydrologyHydrological fluxesGeoscience datasetsLand surfaceTower observationsSpatiotemporal variabilityTemporal coverageCarbon cycleRemote sensingWet regionsAncillary dataCycle applicationsMachine learningSurface model
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