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The GMAO’s Ocean Data Assimilation & SI Forecasts. Michele Rienecker, Christian Keppenne, Robin Kovach Jossy Jacob, Jelena Marshak Global Modeling and Assimilation Office (GMAO) NASA/Goddard Space Flight Center. IGST Meeting June 2-4, 2008. GMAO Ocean Data Assimilation Systems. ODAS-1
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The GMAO’s Ocean Data Assimilation & SI Forecasts Michele Rienecker, Christian Keppenne, Robin Kovach Jossy Jacob, Jelena Marshak Global Modeling and Assimilation Office (GMAO) NASA/Goddard Space Flight Center IGST Meeting June 2-4, 2008
GMAO Ocean Data Assimilation Systems • ODAS-1 • Algorithms: • Univariate optimal interpolation (UOI) - contributed to USGODAE LAS products • Multivariate EnKF - temperature assimilation also corrects salinity and currents • Model: • Poseidon v4 OGCM (Schopf and Loughe, 1995) : • Quasi-isopycnal vertical coordinate • Prognostic variables are H, T, S, u and v • Sea surface height (SSH) is diagnostic • 1/3° x 5/8° x L27 • Observations: • T(z) from XBTs/Moorings + synthetic S(z) from T-S climatology • T(z), S(z) from Argo drifters • SSH from Topex/Poseidon and Jason-1 (only for EnKF) • Forcing: • SSM/I and QuikSCAT surface wind stress products (Atlas & Ardizzone) • NCEP reanalysis surface heat fluxes • GPCP monthly precipitation • Reynolds & Smith SST relaxation • Levitus SSS relaxation • Next system: ODAS-2 • Implemented with ESMF under GEOS-5 modeling system • MOM4 (collaboration with NCEP and GFDL) • GMAO’s Atmospheric analyses for forcing
GMAO Ocean Data Assimilation Experiments • ODAS-1 • Experiments: 1993-present • Argo impacts (2003 ) • Application: Seasonal Forecasts with GMAO CGCMv1 • Conducted “operationally” every month • Contributed to US consensus forecast
Salinity Variability along the Equatorial Pacific (2ºS-2ºN) 24.5kg/m3 Density Surface
EnKF Exp1 - All observations EnKF Exp3 - No Argo OI - No SSH Observations - Argo Salinity Variations along the Equatorial Pacific 140ºW 165ºE 95ºW
EnKF - All observations EnKF - No Argo OI - No SSH Control - No Assimilation Salinity analyses validated against CTD data TAO servicing cruises (8ºS-12ºN) 2005 Niño-3 (150ºW-110ºW) Niño-4 (160ºE-150ºW)
GMAO CGCMv1 (Tier1) Forecast Ensembles AGCM(AMIP forced with Reynolds SST; NCEP Analyses) 12 month Coupled Integrations: 6-30 ensemble members Atmospheric state perturbations: ’s randomly from previous integrations Ocean state estimate perturbations: ’s randomly from snapshots Ocean DAS(Surface wind analysis, GPCP precipitation; Reynolds SST, Temperature profiles; synthetic salinity profiles; Argo; altimetry) 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; Ensemble Kalman Filter “LDAS”: Offline forced land states (recalibrated)
OI EnKF with SSH EnKF w/o SSH 1-month forecast 3-month forecast 6-month forecast
OI EnKF with SSH EnKF w/o SSH 1-month forecast 3-month forecast 6-month forecast
OI EnKF with SSH EnKF w/o SSH 1-month forecast 3-month forecast 6-month forecast
Impact of Argo on Seasonal Forecasts March Starts Each forecast is verified against its own analysis Forecast Anomaly Correlations - Global Heat Content (25ºS-25ºN) EnKF - All Observations EnKF - No Argo EnKF - No SSH Forecast lead (month)
Impact of Argo on Seasonal Forecasts March Starts Each forecast is verified against its own analysis Forecast Anomaly Correlations - Global Salt Content (25ºS-25ºN) EnKF - All Observations EnKF - No Argo EnKF - No SSH Forecast lead (month)
Summary • ODAS-1 Multivariate EnKF generally outperforms the OI implementation • - both analysis and forecasts • Argo - an invaluable data set to correct salinity • Argo and Altimetry seem to work in tandem to improve upper ocean forecasts, but occasionally also work against each other in the GMAO system. • For GODAE: (1) GMAO ODAS-1 analyses through LAS • (2) State of the Ocean Climate • Next steps: • Use MERRA atmospheric state replay in GEOS-5 coupled model with ODAS-2 • - generate better balanced IC for seasonal forecasts