Partitioning evapotranspiration over the continental United States using weather station data

Accurately characterizing evapotranspiration is critical when predicting the response of the hydrologic cycle to climate change. Although Earth system models estimate similar magnitudes of global evapotranspiration, the magnitude of each contributing source varies considerably between models due to...

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Bibliographic Details
Main Authors: Rigden, Angela J. (Author), Salvucci, Guido D. (Author), Entekhabi, Dara (Author), Gianotti, Daniel J (Author)
Other Authors: Massachusetts Institute of Technology. Department of Civil and Environmental Engineering (Contributor)
Format: Article
Language:English
Published: American Geophysical Union (AGU), 2020-06-02T18:57:39Z.
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Online Access:Get fulltext
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100 1 0 |a Rigden, Angela J.  |e author 
100 1 0 |a Massachusetts Institute of Technology. Department of Civil and Environmental Engineering  |e contributor 
700 1 0 |a Salvucci, Guido D.  |e author 
700 1 0 |a Entekhabi, Dara  |e author 
700 1 0 |a Gianotti, Daniel J  |e author 
245 0 0 |a Partitioning evapotranspiration over the continental United States using weather station data 
260 |b American Geophysical Union (AGU),   |c 2020-06-02T18:57:39Z. 
856 |z Get fulltext  |u https://hdl.handle.net/1721.1/125631 
520 |a Accurately characterizing evapotranspiration is critical when predicting the response of the hydrologic cycle to climate change. Although Earth system models estimate similar magnitudes of global evapotranspiration, the magnitude of each contributing source varies considerably between models due to the lack of evapotranspiration partitioning data. Here we develop an observation-based method to partition evapotranspiration into soil evaporation and transpiration using meteorological data and satellite soil moisture retrievals. We apply the methodology at 1,614 weather stations across the continental United States during the summers of 2015 and 2016. We evaluate the method using vegetation indices inferred from satellites, finding strong spatial correlations between modeled transpiration and solar-induced fluorescence (r2 = 0.87), and modeled vegetation fraction and leaf area index (r2 = 0.70). Since the sensitivity of evapotranspiration to environmental factors depends on the contribution of each source component, understanding the partitioning of evapotranspiration is increasingly important with climate change. ©2018. American Geophysical Union. All Rights Reserved. 
520 |a National Science Foundation (grant no. EAR-1446798) 
546 |a en 
655 7 |a Article 
773 |t Geophysical Research Letters