IGST MeetingJune 2-4, 2008

The GMAO’s Ocean Data Assimilation & SI Forecasts

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

ODAS-1Algorithms:- 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 Systems

ODAS-1Experiments: 1993-present- Argo impacts (2003 )

- Application: Seasonal Forecasts with GMAO CGCMv1

Conducted “operationally” every month

Contributed to US consensus forecast

GMAO Ocean Data Assimilation Experiments

Salinity Variability along the Equatorial Pacific (2ºS-2ºN)24.5kg/m3 Density Surface

165ºE 140ºW

EnKF Exp1 - All observations

EnKF Exp3 - No ArgoOI - No SSH

Observations - Argo

Salinity Variations along the Equatorial Pacific

95ºW

Salinity analyses validated against CTD dataTAO servicing cruises (8ºS-12ºN)

2005

Niño-4 (160ºE-150ºW) Niño-3 (150ºW-110ºW)

EnKF - All observations

EnKF - No ArgoOI - No SSH

Control - No Assimilation

GMAO CGCMv1 (Tier1) Forecast Ensembles GMAO CGCMv1 (Tier1) Forecast Ensembles

12 month Coupled Integrations: 6-30 ensemble members

AGCM (AMIP forced with Reynolds SST; NCEP Analyses)

Ocean DAS (Surface wind analysis, GPCP precipitation; Reynolds SST, Temperature profiles; synthetic salinity profiles; Argo; altimetry)

Ocean state estimate perturbations:’s randomly from snapshots

Atmospheric state perturbations: ’s randomly from previous integrations

AGCM: NSIPP1 AGCM, 2 x 2.5 x L34LSM: Mosaic (SVAT)OGCM: Poseidon v4, 1/3 x 5/8 x L27, with embedded mixed layer physicsCGCM: Full coupling, once per day

ODAS: Optimal Interpolation; Ensemble Kalman Filter“LDAS”: Offline forced land states (recalibrated)

1-monthforecast

3-monthforecast

6-monthforecast

EnKF with SSH EnKF w/o SSH OI

1-monthforecast

3-monthforecast

6-monthforecast

EnKF with SSH EnKF w/o SSH OI

1-monthforecast

3-monthforecast

6-monthforecast

EnKF with SSH EnKF w/o SSH OI

March Starts

Impact of Argo on Seasonal Forecasts

Each forecast is verified against its own analysis

Forecast Anomaly Correlations - Global Heat Content (25ºS-25ºN)

Forecast lead (month)

EnKF - No SSH

EnKF - All Observations EnKF - No Argo

March Starts

Impact of Argo on Seasonal Forecasts

Each forecast is verified against its own analysis

Forecast Anomaly Correlations - Global Salt Content (25ºS-25ºN)

Forecast lead (month)

EnKF - No SSH

EnKF - All Observations EnKF - No Argo

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

Thank You!