气候变化领域集成服务门户(CCPortal): GEOS-S2S Version 2: The GMAO High-Resolution Coupled Model and Assimilation System for Seasonal Prediction

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DOI	10.1029/2019JD031767
	GEOS-S2S Version 2: The GMAO High-Resolution Coupled Model and Assimilation System for Seasonal Prediction
	Molod A.; Hackert E.; Vikhliaev Y.; Zhao B.; Barahona D.; Vernieres G.; Borovikov A.; Kovach R.M.; Marshak J.; Schubert S.; Li Z.; Lim Y.-K.; Andrews L.C.; Cullather R.; Koster R.; Achuthavarier D.; Carton J.; Coy L.; Friere J.L.M.; Longo K.M.; Nakada K.; Pawson S.
发表日期	2020
ISSN	2169897X
卷号	125 期号:5
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. © 2020. American Geophysical Union. All Rights Reserved.
英文关键词	Atmosphere-Ocean Data Assimilation; Atmosphere-Ocean Modeling; Seasonal and Subseasonal Prediction
语种	英语
来源期刊	Journal of Geophysical Research: Atmospheres
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/186134
作者单位	Goddard Space Flight Center, NASA, Greenbelt, MD, United States; SSAI, Science Systems and Applications, Inc., Lanham, MD, United States; UCAR, Boulder, CO, United States; JCSDA/UCAR/NOAA, College Park, MD, United States; Goddard Earth Sciences Technology and Research, I. M. Systems Group, College Park, MD, United States; Atmospheric and Oceanic Sciences, University of Maryland, College Park, MD, United States; Goddard Earth Sciences Technology and Research, Universities Space Research Association, Columbia, MD, United States; Center for Weather Forecast and Climate Studies, National Institute for Space Research (INPE), Cachoeira Paulista, Brazil
推荐引用方式 GB/T 7714	Molod A.,Hackert E.,Vikhliaev Y.,et al. GEOS-S2S Version 2: The GMAO High-Resolution Coupled Model and Assimilation System for Seasonal Prediction[J],2020,125(5).
APA	Molod A..,Hackert E..,Vikhliaev Y..,Zhao B..,Barahona D..,...&Pawson S..(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 A.,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).