EGU21-12759
https://doi.org/10.5194/egusphere-egu21-12759
EGU General Assembly 2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

The GMAO High‐Resolution Coupled Model and Assimilation System for Seasonal Prediction

Andrea Molod1 and the GMAO Seasonal Prediction Development Group*
Andrea Molod and the GMAO Seasonal Prediction Development Group
  • 1NASA, GMAO, Greenbelt, United States of America (andrea.molod@nasa.gov)
  • *A full list of authors appears at the end of the abstract

The Global Modeling and Assimilation Office (GMAO) is about to release a new version of the Goddard Earth Observing System (GEOS) Subseasonal to Seasonal prediction (S2S) system, GEOS‐S2S‐3, that represents an improvement in performance and infrastructure over the  previous system, GEOS-S2S-2. The system will be described briefly, highlighting some features unique to GEOS-S2S, such as the coupled interactive aerosol model and ensemble  perturbation strategy and size. Results are presented from forecasts and from climate  equillibrium simulations. GEOS-S2S-3 will be used to produce a long term weakly coupled reanalysis called MERRA-2 Ocean.

The climate or equillibrium state of the atmosphere and ocean shows a reduction in systematic error relative to GEOS‐S2S‐2, attributed in part to an increase in ocean resolution and to the upgrade in the glacier runoff scheme.  The forecast skill shows improved prediction  of the North Atlantic Oscillation, attributed to the increase in forecast ensemble members.  

With the release of GEOS-S2S-3 and MERRA-2 Ocean, 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.

GMAO Seasonal Prediction Development Group:

Santha Akella, Lauren Andrews, Donifan Barahona, Anna Borovikov, Yehui Chang, Richard Cullather, Eric Hackert, Robin Kovach, Randal Koster, Zhao Li, Young-Kwon Lim, Jelena Marshak, Kazumi Nakada, Siegfried Schubert, Yury Vikhliaev, Bin Zhao

How to cite: Molod, A. and the GMAO Seasonal Prediction Development Group: The GMAO High‐Resolution Coupled Model and Assimilation System for Seasonal Prediction, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-12759, https://doi.org/10.5194/egusphere-egu21-12759, 2021.

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