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contributor authorSeneviratne, Sonia I.
contributor authorKoster, Randal D.
contributor authorGuo, Zhichang
contributor authorDirmeyer, Paul A.
contributor authorKowalczyk, Eva
contributor authorLawrence, David
contributor authorLiu, Ping
contributor authorMocko, David
contributor authorLu, Cheng-Hsuan
contributor authorOleson, Keith W.
contributor authorVerseghy, Diana
date accessioned2017-06-09T17:14:04Z
date available2017-06-09T17:14:04Z
date copyright2006/10/01
date issued2006
identifier issn1525-755X
identifier otherams-81539.pdf
identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4224553
description abstractSoil moisture memory is a key aspect of land?atmosphere interaction and has major implications for seasonal forecasting. Because of a severe lack of soil moisture observations on most continents, existing analyses of global-scale soil moisture memory have relied previously on atmospheric general circulation model (AGCM) experiments, with derived conclusions that are probably model dependent. The present study is the first survey examining and contrasting global-scale (near) monthly soil moisture memory characteristics across a broad range of AGCMs. The investigated simulations, performed with eight different AGCMs, were generated as part of the Global Land?Atmosphere Coupling Experiment. Overall, the AGCMs present relatively similar global patterns of soil moisture memory. Outliers are generally characterized by anomalous water-holding capacity or biases in radiation forcing. Water-holding capacity is highly variable among the analyzed AGCMs and is the main factor responsible for intermodel differences in soil moisture memory. Therefore, further studies on this topic should focus on the accurate characterization of this parameter for present AGCMs. Despite the range in the AGCMs? behavior, the average soil moisture memory characteristics of the models appear realistic when compared to available in situ soil moisture observations. An analysis of the processes controlling soil moisture memory in the AGCMs demonstrates that it is mostly controlled by two effects: evaporation?s sensitivity to soil moisture, which increases with decreasing soil moisture content, and runoff?s sensitivity to soil moisture, which increases with increasing soil moisture content. Soil moisture memory is highest in regions of medium soil moisture content, where both effects are small.
publisherAmerican Meteorological Society
titleSoil Moisture Memory in AGCM Simulations: Analysis of Global Land–Atmosphere Coupling Experiment (GLACE) Data
typeJournal Paper
journal volume7
journal issue5
journal titleJournal of Hydrometeorology
identifier doi10.1175/JHM533.1
journal fristpage1090
journal lastpage1112
treeJournal of Hydrometeorology:;2006:;Volume( 007 ):;issue: 005
contenttypeFulltext


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