GEOS‐S2S Version 2: The GMAO high‐resolution coupled model and assimilation system for seasonal prediction

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.

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Author Molod, Andrea
Hackert, Eric
Vikhliaev, Yury
Zhao, Bin
Barahona, Donifan
Vernieres, Guillaume
Borovikov, Anna
Kovach, Robin M.
Marshak, Jelena
Schubert, Siegfried
Li, Zhao
Lim, Young‐Kwon
Andrews, Lauren C.
Cullather, Richard
Koster, Randal
Achuthavarier, Deepthi
Carton, James
Coy, Lawrence
Friere, Julliana L. M.
Longo, Karla M.
Nakada, Kazumi
Pawson, Steven
Publisher UCAR/NCAR - Library
Publication Date 2020-03-16T00:00:00
Digital Object Identifier (DOI) Not Assigned
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Topic Category geoscientificInformation
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Metadata Date 2023-08-18T18:24:53.183584
Metadata Record Identifier edu.ucar.opensky::articles:23204
Metadata Language eng; USA
Suggested Citation Molod, Andrea, Hackert, Eric, Vikhliaev, Yury, Zhao, Bin, Barahona, Donifan, Vernieres, Guillaume, Borovikov, Anna, Kovach, Robin M., Marshak, Jelena, Schubert, Siegfried, Li, Zhao, Lim, Young‐Kwon, Andrews, Lauren C., Cullather, Richard, Koster, Randal, Achuthavarier, Deepthi, Carton, James, Coy, Lawrence, Friere, Julliana L. M., Longo, Karla M., Nakada, Kazumi, Pawson, Steven. (2020). GEOS‐S2S Version 2: The GMAO high‐resolution coupled model and assimilation system for seasonal prediction. UCAR/NCAR - Library. http://n2t.net/ark:/85065/d7sb48xn. Accessed 22 June 2025.

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