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contributor authorSchubert, Siegfried
contributor authorGutzler, David
contributor authorWang, Hailan
contributor authorDai, Aiguo
contributor authorDelworth, Tom
contributor authorDeser, Clara
contributor authorFindell, Kirsten
contributor authorFu, Rong
contributor authorHiggins, Wayne
contributor authorHoerling, Martin
contributor authorKirtman, Ben
contributor authorKoster, Randal
contributor authorKumar, Arun
contributor authorLegler, David
contributor authorLettenmaier, Dennis
contributor authorLyon, Bradfield
contributor authorMagana, Victor
contributor authorMo, Kingtse
contributor authorNigam, Sumant
contributor authorPegion, Philip
contributor authorPhillips, Adam
contributor authorPulwarty, Roger
contributor authorRind, David
contributor authorRuiz-Barradas, Alfredo
contributor authorSchemm, Jae
contributor authorSeager, Richard
contributor authorStewart, Ronald
contributor authorSuarez, Max
contributor authorSyktus, Jozef
contributor authorTing, Mingfang
contributor authorWang, Chunzai
contributor authorWeaver, Scott
contributor authorZeng, Ning
date accessioned2017-06-09T16:29:40Z
date available2017-06-09T16:29:40Z
date copyright2009/10/01
date issued2009
identifier issn0894-8755
identifier otherams-68877.pdf
identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4210483
description abstractThe U.S. Climate Variability and Predictability (CLIVAR) working group on drought recently initiated a series of global climate model simulations forced with idealized SST anomaly patterns, designed to address a number of uncertainties regarding the impact of SST forcing and the role of land?atmosphere feedbacks on regional drought. The runs were carried out with five different atmospheric general circulation models (AGCMs) and one coupled atmosphere?ocean model in which the model was continuously nudged to the imposed SST forcing. This paper provides an overview of the experiments and some initial results focusing on the responses to the leading patterns of annual mean SST variability consisting of a Pacific El Niño?Southern Oscillation (ENSO)-like pattern, a pattern that resembles the Atlantic multidecadal oscillation (AMO), and a global trend pattern. One of the key findings is that all of the AGCMs produce broadly similar (though different in detail) precipitation responses to the Pacific forcing pattern, with a cold Pacific leading to reduced precipitation and a warm Pacific leading to enhanced precipitation over most of the United States. While the response to the Atlantic pattern is less robust, there is general agreement among the models that the largest precipitation response over the United States tends to occur when the two oceans have anomalies of opposite signs. Further highlights of the response over the United States to the Pacific forcing include precipitation signal-to-noise ratios that peak in spring, and surface temperature signal-to-noise ratios that are both lower and show less agreement among the models than those found for the precipitation response. The response to the positive SST trend forcing pattern is an overall surface warming over the world?s land areas, with substantial regional variations that are in part reproduced in runs forced with a globally uniform SST trend forcing. The precipitation response to the trend forcing is weak in all of the models. It is hoped that these early results, as well as those reported in the other contributions to this special issue on drought, will serve to stimulate further analysis of these simulations, as well as suggest new research on the physical mechanisms contributing to hydroclimatic variability and change throughout the world.
publisherAmerican Meteorological Society
titleA U.S. CLIVAR Project to Assess and Compare the Responses of Global Climate Models to Drought-Related SST Forcing Patterns: Overview and Results
typeJournal Paper
journal volume22
journal issue19
journal titleJournal of Climate
identifier doi10.1175/2009JCLI3060.1
journal fristpage5251
journal lastpage5272
treeJournal of Climate:;2009:;volume( 022 ):;issue: 019
contenttypeFulltext


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