The Subseasonal Experiment (SubX): A Multimodel Subseasonal Prediction Experiment-Reference-Cited by-同舟云学术

The Subseasonal Experiment (SubX): A Multimodel Subseasonal Prediction Experiment

Published:2019-10 Issue:10 Volume:100 Page:2043-2060
ISSN:0003-0007
Container-title:Bulletin of the American Meteorological Society
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Author:

Pegion Kathy¹,Kirtman Ben P.²,Becker Emily²,Collins Dan C.³,LaJoie Emerson⁴,Burgman Robert⁵,Bell Ray²,DelSole Timothy⁶,Min Dughong²,Zhu Yuejian⁷,Li Wei⁸,Sinsky Eric⁸,Guan Hong⁹,Gottschalck Jon³,Metzger E. Joseph¹⁰,Barton Neil P¹¹,Achuthavarier Deepthi¹²,Marshak Jelena¹³,Koster Randal D.¹³,Lin Hai¹⁴,Gagnon Normand¹⁵,Bell Michael¹⁶,Tippett Michael K.¹⁷,Robertson Andrew W.¹⁶,Sun Shan¹⁸,Benjamin Stanley G.¹⁹,Green Benjamin W.¹⁸,Bleck Rainer¹⁸,Kim Hyemi²⁰

Affiliation:

1. George Mason University, Fairfax, Virginia

2. Rosenstiel School for Marine and Atmospheric Sciences, University of Miami, Miami, Florida

3. NOAA/NCEP/Climate Prediction Center, College Park, Maryland

4. NOAA/NCEP/Climate Prediction Center, and Innovim, Inc., College Park, Maryland

5. Florida International University, Miami, Florida

6. George Mason University, and Center for Ocean–Land–Atmosphere Studies, Fairfax, Virginia

7. NOAA/NCEP/Environmental Modeling Center, College Park, Maryland

8. IMSG at NOAA/NCEP/Environmental Modeling Center, College Park, Maryland

9. SRG at NOAA/NCEP/Environmental Modeling Center, College Park, Maryland

10. Oceanography Division, Naval Research Laboratory, Stennis Space Center, Mississippi

11. Marine Meteorology Division, Naval Research Laboratory, Monterey, California

12. Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, and Universities Space Research Association, Columbia, Maryland

13. Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, Maryland

14. Recherche en prévision numérique atmosphérique, Environment and Climate Change Canada, Dorval, Quebec, Canada

15. Canadian Meteorological Centre, Environment and Climate Change Canada, Dorval, Quebec, Canada

16. International Research Institute for Climate and Society, Columbia University, Palisades, New York

17. Department of Applied Physics and Applied Mathematics, Columbia University, New York, New York

18. Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, and NOAA/OAR/ESRL/Global Systems Division, Boulder, Colorado

19. NOAA/OAR/ESRL/Global Systems Division, Boulder, Colorado

20. School of Marine and Atmospheric Sciences, Stony Brook University, State University of New York, Stony Brook, New York

Abstract

AbstractThe Subseasonal Experiment (SubX) is a multimodel subseasonal prediction experiment designed around operational requirements with the goal of improving subseasonal forecasts. Seven global models have produced 17 years of retrospective (re)forecasts and more than a year of weekly real-time forecasts. The reforecasts and forecasts are archived at the Data Library of the International Research Institute for Climate and Society, Columbia University, providing a comprehensive database for research on subseasonal to seasonal predictability and predictions. The SubX models show skill for temperature and precipitation 3 weeks ahead of time in specific regions. The SubX multimodel ensemble mean is more skillful than any individual model overall. Skill in simulating the Madden–Julian oscillation (MJO) and the North Atlantic Oscillation (NAO), two sources of subseasonal predictability, is also evaluated, with skillful predictions of the MJO 4 weeks in advance and of the NAO 2 weeks in advance. SubX is also able to make useful contributions to operational forecast guidance at the Climate Prediction Center. Additionally, SubX provides information on the potential for extreme precipitation associated with tropical cyclones, which can help emergency management and aid organizations to plan for disasters.

Publisher

American Meteorological Society

Subject

Atmospheric Science

Link

http://journals.ametsoc.org/bams/article-pdf/100/10/2043/4871537/bams-d-18-0270_1.pdf

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