File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

Article: Drivers of Variability in Atmospheric Evaporative Demand: Multiscale Spectral Analysis Based on Observations and Physically Based Modeling

TitleDrivers of Variability in Atmospheric Evaporative Demand: Multiscale Spectral Analysis Based on Observations and Physically Based Modeling
Authors
Keywordsdryness
net radiation
potential evapotranspiration
time scale
vapor pressure deficit
Issue Date2018
Citation
Water Resources Research, 2018, v. 54, n. 5, p. 3510-3529 How to Cite?
AbstractAtmospheric 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.
Persistent Identifierhttp://hdl.handle.net/10722/349259
ISSN
2023 Impact Factor: 4.6
2023 SCImago Journal Rankings: 1.574

 

DC FieldValueLanguage
dc.contributor.authorPeng, Liqing-
dc.contributor.authorLi, Dan-
dc.contributor.authorSheffield, Justin-
dc.date.accessioned2024-10-17T06:57:21Z-
dc.date.available2024-10-17T06:57:21Z-
dc.date.issued2018-
dc.identifier.citationWater Resources Research, 2018, v. 54, n. 5, p. 3510-3529-
dc.identifier.issn0043-1397-
dc.identifier.urihttp://hdl.handle.net/10722/349259-
dc.description.abstractAtmospheric 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.-
dc.languageeng-
dc.relation.ispartofWater Resources Research-
dc.subjectdryness-
dc.subjectnet radiation-
dc.subjectpotential evapotranspiration-
dc.subjecttime scale-
dc.subjectvapor pressure deficit-
dc.titleDrivers of Variability in Atmospheric Evaporative Demand: Multiscale Spectral Analysis Based on Observations and Physically Based Modeling-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1029/2017WR022104-
dc.identifier.scopuseid_2-s2.0-85049095471-
dc.identifier.volume54-
dc.identifier.issue5-
dc.identifier.spage3510-
dc.identifier.epage3529-
dc.identifier.eissn1944-7973-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats