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Global Modeling and Assimilation Office NASA/GSFC GMAO Merger of NSIPP and the DAO offices at GSFC Science areas: Subseasonal-to-Seasonal-to-Decadal Prediction.

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Presentation on theme: "Global Modeling and Assimilation Office NASA/GSFC GMAO Merger of NSIPP and the DAO offices at GSFC Science areas: Subseasonal-to-Seasonal-to-Decadal Prediction."— Presentation transcript:

1 Global Modeling and Assimilation Office NASA/GSFC GMAO Merger of NSIPP and the DAO offices at GSFC Science areas: Subseasonal-to-Seasonal-to-Decadal Prediction Weather prediction Chemistry-climate connections Hydrological Cycle Technical areas: satellite data assimilation: usage, new mission design, instrument team products Agency Partnerships: NOAA/NCEP, JCSDA, ESMF, NCAR, GFDL, NOAA/CDEP Merger of NSIPP and the DAO offices at GSFC Science areas: Subseasonal-to-Seasonal-to-Decadal Prediction Weather prediction Chemistry-climate connections Hydrological Cycle Technical areas: satellite data assimilation: usage, new mission design, instrument team products Agency Partnerships: NOAA/NCEP, JCSDA, ESMF, NCAR, GFDL, NOAA/CDEP

2 Ensemble mean precipitation and ground temperature anomalies forecast for NDJ 2003 Rienecker, Suarez, et al. GSFC/GMAO (NSIPP) Seasonal forecasts with NSIPP CGCMv1: High resolution: 2° AGCM & 1/3° OGCM Ocean initial states from ocean data assimilation Ensembles used to indicate uncertainty Nino3 SST forecast, initialized in September 2003

3 NSIPP CGCMv1 Forecast Ensembles 12 month Coupled Integrations: 18 ensemble members AGCM (AMIP forced with Reynolds SST) Ocean DAS (Surface wind analysis from R. Atlas, Reynolds SST, Temperature profiles by TAO) Ocean state estimate perturbations:  ’s randomly from snapshots Atmospheric state perturbations:  ’s randomly from previous integrations AGCM: NSIPP1 AGCM, 2 x 2.5 x L34 LSM: Mosaic (SVAT) OGCM: Poseidon v4, 1/3 x 5/8 x L27, with embedded mixed layer physics CGCM: Full coupling, once per day ODAS: Optimal Interpolation of in situ temperature profiles - daily, salinity adjustment (Troccoli & Haines), Jan1993-present, starting in every month

4 NASA/GMAO Atmospheric Model NASA’s Seasonal-to-Interannual Prediction Project (NSIPP) version 1, Bacmeister et al. (2001) Operational prediction model and tested up to ½ degree resolutions NumericsFinite Difference (Suarez and Takacs 1995) Cumulus convection Relaxed Arakawa-Schubert (Moorthi and Suarez 1992) More detailed condensate budget in the updraft Large-scale condensation Diagnostic cloud scheme based on RH, similar to Slingo (1987) PBL/vertical diffusion Local diffusion by Louis et al. (1982) RadiationChou and Suarez (1999) for SW and Chou and Suarez (1994) for LW OthersGravity wave drag (Zhou et al., 1996) Mosaic LSM (Koster and Suarez, 1992,1996)

5 New approach: - weather capable climate model and climate-reliable weather model –Unified Goddard modeling system (GEOS-5) AGCM: FVcore + evolving physics: combining GSFC developments with NCAR, GFDL collaborations Working to include GISS under a common Goddard model “toolkit” (with Code 930) LSM: Catchment LSM + features required for carbon, NWP, long-term climate –Modular, ESMF-based development of atmospheric model and subcomponents New approach: - weather capable climate model and climate-reliable weather model –Unified Goddard modeling system (GEOS-5) AGCM: FVcore + evolving physics: combining GSFC developments with NCAR, GFDL collaborations Working to include GISS under a common Goddard model “toolkit” (with Code 930) LSM: Catchment LSM + features required for carbon, NWP, long-term climate –Modular, ESMF-based development of atmospheric model and subcomponents “Snapshot” of water vapor (white) and precipitation (orange) at 1/2 degree lat/lon resolution.


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