GSTDTAP  > 气候变化
DOI10.1029/2019JD031767
GEOS-S2S Version 2: The GMAO High-Resolution Coupled Model and Assimilation System for Seasonal Prediction
Molod, Andrea1; Hackert, Eric1; Vikhliaev, Yury1,2; Zhao, Bin1,2; Barahona, Donifan1; Vernieres, Guillaume3,4; Borovikov, Anna1,2; Kovach, Robin M.1,2; Marshak, Jelena1; Schubert, Siegfried1,2; Li, Zhao1,2; Lim, Young-Kwon1,5; Andrews, Lauren C.1; Cullather, Richard1,6; Koster, Randal1; Achuthavarier, Deepthi1,7; Carton, James6; Coy, Lawrence1,2; Friere, Julliana L. M.1,8; Longo, Karla M.1,7; Nakada, Kazumi1,2; Pawson, Steven1
2020-03-16
发表期刊JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES
ISSN2169-897X
EISSN2169-8996
出版年2020
卷号125期号:5
文章类型Article
语种英语
国家USA; Brazil
英文摘要

The Global Modeling and Assimilation Office (GMAO) has recently released a new version of the Goddard Earth Observing System (GEOS) Subseasonal to Seasonal prediction (S2S) system, GEOS-S2S-2, that represents a substantial improvement in performance and infrastructure over the previous system. The system is described here in detail, and results are presented from forecasts, climate equillibrium simulations, and data assimilation experiments. The climate or equillibrium state of the atmosphere and ocean showed a substantial reduction in bias relative to GEOS-S2S-1. The GEOS-S2S-2 coupled reanalysis also showed substantial improvements, attributed to the assimilation of along-track absolute dynamic topography. The forecast skill on subseasonal scales showed a much improved prediction of the Madden-Julian Oscillation in GEOS-S2S-2, and on a seasonal scale the tropical Pacific forecasts show substantial improvement in the east and comparable skill to GEOS-S2S-1 in the central Pacific. GEOS-S2S-2 anomaly correlations of both land surface temperature and precipitation were comparable to GEOS-S2S-1 and showed substantially reduced root-mean-square error of surface temperature. The remaining issues described here are being addressed in the development of GEOS-S2S Version 3, and with that system GMAO will continue its tradition of maintaining a state-of-the-art seasonal prediction system for use in evaluating the impact on seasonal and decadal forecasts of assimilating newly available satellite observations, as well as evaluating additional sources of predictability in the Earth system through the expanded coupling of the Earth system model and assimilation components.


英文关键词Atmosphere-Ocean Modeling Atmosphere-Ocean Data Assimilation Seasonal and Subseasonal Prediction
领域气候变化
收录类别SCI-E
WOS记录号WOS:000519602000016
WOS关键词ARCTIC SEA-ICE ; OCEAN DATA ASSIMILATION ; GENERAL-CIRCULATION ; GLOBAL OCEAN ; ATMOSPHERIC RESPONSE ; NORTHERN-HEMISPHERE ; POTENTIAL PREDICTABILITY ; INDONESIAN THROUGHFLOW ; EQUATORIAL PACIFIC ; CLIMATE IMPACTS
WOS类目Meteorology & Atmospheric Sciences
WOS研究方向Meteorology & Atmospheric Sciences
引用统计
文献类型期刊论文
条目标识符http://119.78.100.173/C666/handle/2XK7JSWQ/280109
专题气候变化
作者单位1.NASA, Goddard Space Flight Ctr, Greenbelt, MD 20771 USA;
2.Sci Syst & Applicat Inc, SSAI, Lanham, MD USA;
3.UCAR, Boulder, CO USA;
4.UCAR, NOAA, JCSDA, College Pk, MD USA;
5.Goddard Earth Sci Technol & Res, IM Syst Grp, College Pk, MD USA;
6.Univ Maryland, Atmospher & Ocean Sci, College Pk, MD 20742 USA;
7.Univ Space Res Assoc, Goddard Earth Sci Technol & Res, Columbia, MD USA;
8.Natl Inst Space Res INPE, Ctr Weather Forecast & Climate Studies, Cachoeira Paulista, Brazil
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GB/T 7714
Molod, Andrea,Hackert, Eric,Vikhliaev, Yury,et al. GEOS-S2S Version 2: The GMAO High-Resolution Coupled Model and Assimilation System for Seasonal Prediction[J]. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES,2020,125(5).
APA Molod, Andrea.,Hackert, Eric.,Vikhliaev, Yury.,Zhao, Bin.,Barahona, Donifan.,...&Pawson, Steven.(2020).GEOS-S2S Version 2: The GMAO High-Resolution Coupled Model and Assimilation System for Seasonal Prediction.JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES,125(5).
MLA Molod, Andrea,et al."GEOS-S2S Version 2: The GMAO High-Resolution Coupled Model and Assimilation System for Seasonal Prediction".JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES 125.5(2020).
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