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Drivers of variability in atmospheric evaporative demand: Multiscale spectral analysis based on observations and physically based modeling

Drivers of variability in atmospheric evaporative demand: Multiscale spectral analysis based on observations and physically based modeling
Drivers of variability in atmospheric evaporative demand: Multiscale spectral analysis based on observations and physically based modeling

Atmospheric evaporative demand (AED) is an important variable linking climate with the terrestrial water cycle and the biosphere. Understanding the dynamics of AED has substantial economic, ecological, and social implications. However, how AED varies at different time scales and the drivers of variability remain elusive. This study used spectral coherence analysis to analyze the relationships between observed and modeled AED and climate drivers across multiple time scales at 228 Chinese stations and explored the cross-scale effects of climate forcings on AED. The results highlight the crucial role of vapor pressure deficit (VPD) in both energy-limited and water-limited regions, therefore models that do not incorporate VPD or underestimate the relative importance of VPD have relatively lower skill in predicting AED. Short-term forcing variability has potential impacts on the long-term AED changes through temperature and associated land-atmosphere feedbacks. Our study implies that model predictions for AED and associated hydrologic impacts may not be valid in a changing climate when the key controls on AED and their relative importance are not appropriately represented.

dryness, net radiation, potential evapotranspiration, time scale, vapor pressure deficit
0043-1397
3510-3529
Peng, Liqing
5a4984ff-9082-4a4c-8e17-991d9eda35cc
Li, Dan
276851c4-71b0-4fa3-b215-f3f1348fd256
Sheffield, Justin
dd66575b-a4dc-4190-ad95-df2d6aaaaa6b
Peng, Liqing
5a4984ff-9082-4a4c-8e17-991d9eda35cc
Li, Dan
276851c4-71b0-4fa3-b215-f3f1348fd256
Sheffield, Justin
dd66575b-a4dc-4190-ad95-df2d6aaaaa6b

Peng, Liqing, Li, Dan and Sheffield, Justin (2018) Drivers of variability in atmospheric evaporative demand: Multiscale spectral analysis based on observations and physically based modeling. Water Resources Research, 54 (5), 3510-3529. (doi:10.1029/2017WR022104).

Record type: Article

Abstract

Atmospheric evaporative demand (AED) is an important variable linking climate with the terrestrial water cycle and the biosphere. Understanding the dynamics of AED has substantial economic, ecological, and social implications. However, how AED varies at different time scales and the drivers of variability remain elusive. This study used spectral coherence analysis to analyze the relationships between observed and modeled AED and climate drivers across multiple time scales at 228 Chinese stations and explored the cross-scale effects of climate forcings on AED. The results highlight the crucial role of vapor pressure deficit (VPD) in both energy-limited and water-limited regions, therefore models that do not incorporate VPD or underestimate the relative importance of VPD have relatively lower skill in predicting AED. Short-term forcing variability has potential impacts on the long-term AED changes through temperature and associated land-atmosphere feedbacks. Our study implies that model predictions for AED and associated hydrologic impacts may not be valid in a changing climate when the key controls on AED and their relative importance are not appropriately represented.

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Accepted/In Press date: 22 April 2018
e-pub ahead of print date: 25 April 2018
Published date: 1 May 2018
Additional Information: An edited version of this paper was published by AGU. Copyright (2018) American Geophysical Union
Keywords: dryness, net radiation, potential evapotranspiration, time scale, vapor pressure deficit

Identifiers

Local EPrints ID: 422220
URI: http://eprints.soton.ac.uk/id/eprint/422220
ISSN: 0043-1397
PURE UUID: 244b729d-4dc4-44a0-8595-4dcd56970f7c
ORCID for Justin Sheffield: ORCID iD orcid.org/0000-0003-2400-0630

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Date deposited: 19 Jul 2018 16:30
Last modified: 18 Mar 2024 05:19

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Author: Liqing Peng
Author: Dan Li

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