Soil Moisture and Atmospheric Aridity Impact Spatio-Temporal Changes in Evapotranspiration at a Global Scale

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Evapotranspiration (ET) constitutes the water exchange from land to the atmosphere, which in turn modulates precipitation and soil moisture (SM). Multiple lines of evidence document complex feedbacks between changes in ET and temperature, atmospheric CO2 and vegetation greening. However, the existing analyses on global changes in ET do not account for the direct effects of SM supply and atmospheric water demand, expressed by vapor pressure deficit (VPD), while considering multiple environmental variables. Here we evaluated the performance of ET products using 140 flux towers included in the FLUXNET database. All ET products show reasonable performance, with an overall correlation higher than 0.7 and better performance at a higher latitude. From analysis of the ensemble mean of annual ET, we show insignificant (P = 0.06) trends in global ET during 1982–2020 and a significantly (P < 0.01) increasing trend during 2002–2020. Changes in GLEAM ET generally exert a positive response to changes in SM and a negative response to changes in VPD. Yet, these effects are not globally consistent and are largely determined by changes in vegetation transpiration. Using our finding as a benchmark, Earth System Models mostly reproduce the positive response of ET to SM with less coupling strength, while showing negative effects of VPD on ET with stronger coupling strength. Our study highlights that concurrent soil drying and atmospheric aridity could intensify water exchanges and the importance of realistically representing SM-VPD-ET interactions in models for accurate predictions of the hydrological cycle.

OriginalsprogEngelsk
Artikelnummere2022JD038046
TidsskriftJournal of Geophysical Research: Atmospheres
Vol/bind128
Udgave nummer8
Antal sider15
ISSN2169-897X
DOI
StatusUdgivet - 2023

Bibliografisk note

Funding Information:
W.Z. acknowledges funding from the National Natural Science Foundation of China (Grant 42001349) and is supported by ERC project TOFDRY (Grant 947757). RF acknowledges support by the Villum Foundation through the project “Deep Learning and Remote Sensing for Unlocking Global Ecosystem Resource Dynamics” (DeReEco). Z.F. is funded by the China Scholarship Council (CSC) (Grant 201906410082).

Publisher Copyright:
© 2023 The Authors.

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