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A USCLIVAR Project to Assess and Compare the Responses of Global Climate Models to Drought-Related SST Forcing Patterns: Overview and ResultsThe USCLI VAR 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. Specific questions that the runs are designed to address include: What are the mechanisms that maintain drought across the seasonal cycle and from one year to the next? What is the role of the leading patterns of SST variability, and what are the physical mechanisms linking the remote SST forcing to regional drought, including the role of land-atmosphere coupling? The runs were carried out with five different atmospheric general circulation models (AGCM5), 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 Nino/Southern Oscillation (ENSO)-like pattern, a pattern that resembles the Atlantic Multi-decadal Oscillation (AMO), and a global trend pattern. One of the key findings is that all 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 U.S. tends to occur when the two oceans have anomalies of opposite sign. That is, a cold Pacific and warm Atlantic tend to produce the largest precipitation reductions, whereas a warm Pacific and cold Atlantic tend to produce the greatest precipitation enhancements. Further analysis of the response over the U.S. to the Pacific forcing highlights a number of noteworthy and to some extent unexpected results. These include a seasonal dependence of the precipitation response that is characterized by 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. Another interesting result concerns what appears to be a substantially different character in the surface temperature response over the U.S. to the Pacific forcing by the only model examined here that was developed for use in numerical weather prediction. 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 the models.
Document ID
20090009347
Acquisition Source
Goddard Space Flight Center
Document Type
Preprint (Draft being sent to journal)
Authors
Schubert, Siegfried
(NASA Goddard Space Flight Center Greenbelt, MD, United States)
Wang, Hailan
(NASA Goddard Space Flight Center Greenbelt, MD, United States)
Koster, Randal
(NASA Goddard Space Flight Center Greenbelt, MD, United States)
Weaver, Scott
(NASA Goddard Space Flight Center Greenbelt, MD, United States)
Gutzler, David
(New Mexico Univ. Albuquerque, NM, United States)
Dai, Aiguo
(National Center for Atmospheric Research Boulder, CO, United States)
Delworth, Tom
(National Oceanic and Atmospheric Administration Princeton, NJ, United States)
Deser, Clara
(National Center for Atmospheric Research Boulder, CO, United States)
Findell, Kristen
(National Oceanic and Atmospheric Administration Princeton, NJ, United States)
Fu, Rong
(Texas Univ. Austin, TX, United States)
Higgins, Wayne
(National Oceanic and Atmospheric Administration Washington, DC, United States)
Hoerline, Martin
(National Center for Atmospheric Research Boulder, CO, United States)
Kirtman, Ben
(Miami Univ. Miami, FL, United States)
Kumar, Arun
(National Oceanic and Atmospheric Administration Washington, DC, United States)
Mo, Kingtse
(National Oceanic and Atmospheric Administration Washington, DC, United States)
Pegion, Philip
(National Oceanic and Atmospheric Administration Washington, DC, United States)
Phillips, Adam
(National Center for Atmospheric Research Boulder, CO, United States)
Suarez, Max
(NASA Goddard Space Flight Center Greenbelt, MD, United States)
Legler, David
(U.S. Climate Variability and Predictability Research Program Washington, DC)
Lettenmaier, Dennis
(Washington Univ. Seattle, WA, United States)
Lyon, Bradfield
(Columbia Univ. Palisades, NY, United States)
Magana, Victor
(Universidad Nacional Autonoma de Mexico Mexico City, Mexico)
Nigam, Sumant
(Maryland Univ. College Park, MD, United States)
Pulwarty, Roger
(National Oceanic and Atmospheric Administration Washington, DC, United States)
Rind, David
(NASA Goddard Space Flight Center Greenbelt, MD, United States)
Date Acquired
August 24, 2013
Publication Date
January 12, 2009
Subject Category
Meteorology And Climatology
Distribution Limits
Public
Copyright
Public Use Permitted.
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