GEOS‐S2S Version 2: The GMAO High‐Resolution Coupled Model and Assimilation System for Seasonal Prediction. Issue 5 (6th March 2020) - 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; et al.
Abstract: 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. Key Points: GMAO's New Seasonal Prediction Model and Assimilation shows substantial improvement in forecast skill over the previous version