Seasonal-Decadal Analysis & Prediction
The NASA GMAO seasonal forecasts are currently produced with the Goddard Earth Observing System (GEOS) Atmosphere-Ocean General Circulation Model and Data Assimilation System Version 2 (GEOS-S2S-2). The new system replaces version 1 described in Borovikov et al (2017) and includes upgrades to many components of the system. GEOS-S2S-2 is described in detail in Molod et al., 2020.
The atmospheric model includes an upgrade from a pre-MERRA-2 version running a the latitude-longitude grid at ~1 degree resolution to a newer version running on a cubed sphere grid at approximately 1/2 degree resolution. The important atmospheric model developments are related to the dynamical core (Putman et al., 2011), the moist physics (“two-moment microphysics” of Barahona et al., 2014) and the cryosphere (Cullather et al., 2014). As in the previous GMAO S2S system, the land model is that of Koster et al (2000).
GMAO’s GEOS-S2S-2 also includes the Goddard Chemistry Aerosol Radiation and Transport model (GOCART, Colarco et al., 2010) single moment interactive aerosol model that includes prediction of dust, sea salt and several species of carbon and sulfate. The ocean model includes an upgrade from MOM4 to MOM5 (Griffies 2012), and continues to be run on a tripolar grid at approximately 1/2 degree resolution in the tropics with 40 vertical levels. As in S2S Version 1, the sea ice model is from the Los Alamos Sea Ice model (CICE4, Hunke and Lipscomb 2010). The Ocean Data Assimilation System (ODAS) has been upgraded from the one described in Borovikov et al., 2017 to one that uses the LETKF (Local Ensemble Transform Kalman Filter, Penny, 2014), and so now assimilates along-track altimetry, and does a nudging to MERRA-2 SST and sea ice boundary conditions. The “one-way” coupled assimilation includes a “replay” (Orbe et al., 2017 ; Takacs et al., 2018) to MERRA2 (GEOS-S2S-1 replayed to MERRA) atmospheric fields and an ODAS, all in the context of a coupled model. The atmospheric and oceanic fields for the seasonal and subseasonal forecasts are initialized from the coupled assimilation. Ensemble members are produced with initial states at 5-day intervals, with additional members at the end of the month based on perturbations of the atmospheric and ocean states.
Seasonal forecasts are submitted to the National MultiModel Ensemble (NMME) project, and are part of the US/Canada multi-model seasonal forecasts and used to produce NOAA’s seasonal outlook for the nation. Subseasonal forecasts are submitted to SubX, and used as part of their multi-model forecasts for week 3-4. A large suite of retrospective forecasts have been completed for both seasonal and subseasonal systems, and are used for forecast calibration and anomaly calculation (the calculation of the model’s baseline climatology and drift, anomalies from which are the basis of the seasonal forecasts) as well as for studies of predictability. Data collections from GMAO’s GEOS-S2S-2 are provided on a regular 0.5°×0.5° longitude-by-latitude grid with 720 points in the longitudinal direction and 361 points in the latitudinal direction. The file specification document for forecast output is available at: https://gmao.gsfc.nasa.gov/pubs/docs/Nakada1033.pdf
References
Molod, A., E. Hackert, Y. Vikhliaev, B. Zhao, D. Barahona, G. Vernieres, A. Borovikov, R. M. Kovach, J. Marshak, S. Schubert, Z. Li, Y.-K. Lim, L. C. Andrews, R. Cullather, R. Koster, D. Achuthavarier, J. Carton, L. Coy, J. L. M. Freire, K. M. Longo, K. Nakada, and S. Pawson, 2020. GEOS-S2S Version 2: The GMAO High Resolution Coupled Model and Assimilation System for Seasonal Prediction. J. Geophy. Res. - Atmos. , 125, e2019JD031767. doi: 10.1029/2019JD031767
Orbe, C., L. D. Oman, S. E. Strahan, D. W. Waugh, L. L. Takacs, S. Pawson, and A. M. Molod, 2017. Large-Scale Atmospheric Transport in GEOS Replay Simulations. J. Adv. Model. Earth Sy , 9 (7), 2545-2560. DOI: 10.1002/2017MS001053 Link to Published Version
Takacs, L. L., M. J. Suarez, and R. Todling, 2018. The Stability of Incremental Analysis Update. Monthly Weather Review, 146, 3259-3275. DOI: 10.1175/MWR-D-18-0117.1 Link to Published Version
