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

Author:

Schubert Siegfried1,Gutzler David2,Wang Hailan13,Dai Aiguo4,Delworth Tom5,Deser Clara4,Findell Kirsten5,Fu Rong6,Higgins Wayne7,Hoerling Martin8,Kirtman Ben9,Koster Randal1,Kumar Arun7,Legler David10,Lettenmaier Dennis11,Lyon Bradfield12,Magana Victor13,Mo Kingtse7,Nigam Sumant14,Pegion Philip7,Phillips Adam4,Pulwarty Roger15,Rind David16,Ruiz-Barradas Alfredo14,Schemm Jae7,Seager Richard17,Stewart Ronald18,Suarez Max1,Syktus Jozef19,Ting Mingfang17,Wang Chunzai20,Weaver Scott13,Zeng Ning14

Affiliation:

1. Global Modeling and Assimilation Office, Science and Exploration Directorate, NASA GSFC, Greenbelt, Maryland

2. Department of Earth and Planetary Sciences, University of New Mexico, Albuquerque, New Mexico

3. Goddard Earth Sciences and Technology Center, University of Maryland, Baltimore County, Baltimore, Maryland

4. National Center for Atmospheric Research, Boulder, Colorado

5. National Oceanic and Atmospheric Administration/Geophysical Fluid Dynamics Laboratory, Princeton University, Princeton, New Jersey

6. Jackson School of Geosciences, The University of Texas at Austin, Austin, Texas

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

8. NOAA/Earth System Research Laboratory, Boulder, Colorado

9. Rosenstiel School of Marine and Atmospheric Science, University of Miami, Miami, Florida

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

11. Department of Civil and Environmental Engineering, University of Washington, Seattle, Washington

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

13. Center for Atmospheric Sciences, National Autonomous University of Mexico, Mexico City, Mexico

14. Department of Atmospheric and Oceanic Science, University of Maryland, College Park, College Park, Maryland

15. NOAA/National Integrated Drought Information System, Boulder, Colorado

16. NASA Goddard Institute for Space Studies, New York, New York

17. Lamont-Doherty Earth Observatory, Columbia University, Palisades, New York

18. Department of Environment and Geography, University of Manitoba, Winnipeg, Manitoba, Canada

19. Environmental Protection Agency, Indooroopilly, Queensland, Australia

20. NOAA/Atlantic Oceanographic and Meteorological Laboratory/Physical Oceanography Division, Miami, Florida

Abstract

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.

Publisher

American Meteorological Society

Subject

Atmospheric Science

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