A U.S. CLIVAR Project to Assess and Compare the Responses of Global Climate Models to Drought-Related SST Forcing Patterns: Overview and Results

Siegfried Schubert Global Modeling and Assimilation Office, Science and Exploration Directorate, NASA GSFC, Greenbelt, Maryland

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David Gutzler Department of Earth and Planetary Sciences, University of New Mexico, Albuquerque, New Mexico

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Hailan Wang Global Modeling and Assimilation Office, Science and Exploration Directorate, NASA GSFC, Greenbelt, Maryland
Goddard Earth Sciences and Technology Center, University of Maryland, Baltimore County, Baltimore, Maryland

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Aiguo Dai National Center for Atmospheric Research, Boulder, Colorado

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Tom Delworth National Oceanic and Atmospheric Administration/Geophysical Fluid Dynamics Laboratory, Princeton University, Princeton, New Jersey

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Clara Deser National Center for Atmospheric Research, Boulder, Colorado

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Kirsten Findell National Oceanic and Atmospheric Administration/Geophysical Fluid Dynamics Laboratory, Princeton University, Princeton, New Jersey

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Rong Fu Jackson School of Geosciences, The University of Texas at Austin, Austin, Texas

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Wayne Higgins NOAA/NWS/NCEP/Climate Prediction Center, Washington, D.C

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Martin Hoerling NOAA/Earth System Research Laboratory, Boulder, Colorado

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Ben Kirtman Rosenstiel School of Marine and Atmospheric Science, University of Miami, Miami, Florida

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Randal Koster Global Modeling and Assimilation Office, Science and Exploration Directorate, NASA GSFC, Greenbelt, Maryland

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Arun Kumar NOAA/NWS/NCEP/Climate Prediction Center, Washington, D.C

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David Legler U.S. Climate Variability and Predictability Research Program, Washington, D.C

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Dennis Lettenmaier Department of Civil and Environmental Engineering, University of Washington, Seattle, Washington

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Bradfield Lyon International Research Institute for Climate and Society, Lamont-Doherty Earth Observatory, Columbia University, Palisades, New York

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Victor Magana Center for Atmospheric Sciences, National Autonomous University of Mexico, Mexico City, Mexico

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Kingtse Mo NOAA/NWS/NCEP/Climate Prediction Center, Washington, D.C

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Sumant Nigam Department of Atmospheric and Oceanic Science, University of Maryland, College Park, College Park, Maryland

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Philip Pegion NOAA/NWS/NCEP/Climate Prediction Center, Washington, D.C

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Adam Phillips National Center for Atmospheric Research, Boulder, Colorado

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Roger Pulwarty NOAA/National Integrated Drought Information System, Boulder, Colorado

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David Rind NASA Goddard Institute for Space Studies, New York, New York

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Alfredo Ruiz-Barradas Department of Atmospheric and Oceanic Science, University of Maryland, College Park, College Park, Maryland

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Jae Schemm NOAA/NWS/NCEP/Climate Prediction Center, Washington, D.C

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Richard Seager Lamont-Doherty Earth Observatory, Columbia University, Palisades, New York

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Ronald Stewart Department of Environment and Geography, University of Manitoba, Winnipeg, Manitoba, Canada

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Max Suarez Global Modeling and Assimilation Office, Science and Exploration Directorate, NASA GSFC, Greenbelt, Maryland

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Jozef Syktus Environmental Protection Agency, Indooroopilly, Queensland, Australia

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Mingfang Ting Lamont-Doherty Earth Observatory, Columbia University, Palisades, New York

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Chunzai Wang NOAA/Atlantic Oceanographic and Meteorological Laboratory/Physical Oceanography Division, Miami, Florida

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Scott Weaver Global Modeling and Assimilation Office, Science and Exploration Directorate, NASA GSFC, Greenbelt, Maryland
Goddard Earth Sciences and Technology Center, University of Maryland, Baltimore County, Baltimore, Maryland

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Ning Zeng Department of Atmospheric and Oceanic Science, University of Maryland, College Park, College Park, Maryland

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Abstract

The 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.

Corresponding author address: Siegfried D. Schubert, Global Modeling and Assimilation Office, NASA GSFC, Greenbelt, MD 20771. Email: siegfried.d.schubert@nasa.gov

This article included in the U.S. CLIVAR Drought special collection.

Abstract

The 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.

Corresponding author address: Siegfried D. Schubert, Global Modeling and Assimilation Office, NASA GSFC, Greenbelt, MD 20771. Email: siegfried.d.schubert@nasa.gov

This article included in the U.S. CLIVAR Drought special collection.

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