Articles | Volume 24, issue 4
Hydrol. Earth Syst. Sci., 24, 1927–1938, 2020
https://doi.org/10.5194/hess-24-1927-2020
Hydrol. Earth Syst. Sci., 24, 1927–1938, 2020
https://doi.org/10.5194/hess-24-1927-2020

Research article 16 Apr 2020

Research article | 16 Apr 2020

Global assessment of how averaging over spatial heterogeneity in precipitation and potential evapotranspiration affects modeled evapotranspiration rates

Elham Rouholahnejad Freund et al.

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Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
ED: Reconsider after major revisions (further review by editor and referees) (04 Jul 2019) by Miriam Coenders-Gerrits
AR by Anna Mirena Feist-Polner on behalf of the Authors (21 Aug 2019)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (27 Aug 2019) by Miriam Coenders-Gerrits
RR by Anonymous Referee #3 (01 Sep 2019)
RR by Anonymous Referee #1 (01 Oct 2019)
ED: Reconsider after major revisions (further review by editor and referees) (15 Oct 2019) by Miriam Coenders-Gerrits
AR by Elham Rouholahnejad Freund on behalf of the Authors (26 Nov 2019)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (05 Dec 2019) by Miriam Coenders-Gerrits
RR by Anonymous Referee #3 (03 Jan 2020)
RR by Anonymous Referee #1 (07 Jan 2020)
ED: Publish subject to minor revisions (review by editor) (23 Jan 2020) by Miriam Coenders-Gerrits
AR by Anna Mirena Feist-Polner on behalf of the Authors (27 Jan 2020)  Author's response    Manuscript
ED: Publish as is (10 Feb 2020) by Miriam Coenders-Gerrits
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Short summary
Evapotranspiration (ET) rates and properties that regulate them are spatially heterogeneous. Averaging over spatial heterogeneity in precipitation (P) and potential evapotranspiration (PET) as the main drivers of ET may lead to biased estimates of energy and water fluxes from the land to the atmosphere. We show that this bias is largest in mountainous terrains, in regions with temperate climates and dry summers, and in landscapes where spatial variations in P and PET are inversely correlated.