1. 1 Review of Ocean Data Assimilation and Forecasting at NCEP/EMC S. Lord, D. Behringer, H-L Pan, H. Tolman

2. 2 Overview GODAS and operational CFS CFS Reanalysis (and Reforecast) project Ocean observations for climate and real-time applications

3. 3 Seasonal to Interannual Prediction at NCEP Operational System since August 2004 Climate Forecast System (CFS) Ocean Model MOMv3 quasi-global 1 o x1 o (1/3 o in tropics) 40 levels Atmospheric Model GFS (2003) T62 64 levels GODAS (2003) 3DVAR XBT TAO Triton Pirata Argo Salinity (syn.) TOPEX/Jason-1 Reanalysis-2 3DVAR T62L28 OIv2 SST Levitas SSS clim. 1. Ocean reanalysis (1980-present) provides initial conditions for retrospective CFS forecasts used for calibration and research 2. Stand-alone version with a 14-day lag updated routinely

4. 4 Number of Temperature Observations per Month as a Function of Depth

5. 5 http://www.cpc.ncep.noaa.gov/products/GODAS/ GODAS access – CPC site Pentad and Monthly data products 1979-present Access to current and archived Monthly Ocean Briefings

6. 6 http://cfs.ncep.noaa.gov/ncep_data/ GODAS access - NOMADS Pentad and Monthly data Interactive plotting ftp, http – full data file download ftp2u – partial data download DODS

7. 7 Suru Saha and Hua-Lu Pan, EMC/NCEP With Input from Stephen Lord, Mark Iredell, Shrinivas Moorthi, David Behringer, Ken Mitchell, Bob Kistler, Jack Woollen, Huug van den Dool, Catherine Thiaw and others NCEP CFSRR Climate Forecast System Global Reanalysis and Seasonal Reforecast Project (1979-2009)

8. 8 CFSRR Purpose Provide the best, consistent historical analysis for –CFS reforecasts –Upgraded CFS to be implemented in NCEP operations (2010) Provide state-of-the-science Reanalysis for the Satellite Era (1979-present) Address calibration and statistical applications for daily and monthly forecasts Provide basis for a future coupled atmosphere-ocean- seaice-land forecast system running operationally at NCEP (1 day to 1 year)

9. 9 CFSRR Components Reanalysis –31-year period (1979-2009 and continued in NCEP ops) –Atmosphere –Ocean –Land –Seaice –Coupled system (A-O-L-S) provides background for analysis –Produces consistent initial conditions for climate and weather forecasts Reforecast –28-year period (1982-2009 and continued in NCEP ops ) –Provides stable calibration and skill estimates for new operational seasonal system Includes upgrades for A-O-L-S developed since CFS originally implemented in 2004 –Upgrades developed and tested for both climate and weather prediction –“Unified weather-climate” strategy (1 day to 1 year)

10. 10 Component Upgrades ComponentOps CFS2010 CFS Atmosphere 1995 (R2) model 200 km/28 sigma levels 2008 model (upgrades to all physics) 38 km/64 sigma-pressure levels Enthalpy-based thermodynamics R2 analysis Satellite retrievals GSI with simplified 4d-var (FOTO) Radiances with bias-corrected spinup Ocean MOM-3 60N – 65 S 1/3 x 1 deg. MOM-4 Global domain ¼ x ½ deg. Coupled sea ice forecast model Ocean data assim. 750 m depth2000 m Land No separate land property analysis Global Land Data Assim. Sys (GLDAS) driven by observed precipitation 1995 land model (2 levels)2008 Noah model Sea ice Daily analysisDaily hires analysis Coupling NoneFully coupled background forecast (same as free forecast)

11. 11 CFSRR Production Configuration Covers 31 years (1979-2009) + 25 overlap months 6 Simultaneous Streams Jan 1979 – Dec 19857 years Nov 1985 – Feb 19893 years Jan 1989 – Feb 19945 years Jan 1994 – Dec 19985 years Apr 1998 – Dec 2004 6 years Apr 2004 – Dec 20095 years Overlap months are for ocean and land spin ups Satellite bias correction spinup for each instrument (3 months)

12. 12 CFSRR at NCEP GODAS 3DVAR Ocean Model MOMv4 fully global 1/2 o x1/2 o (1/4 o in tropics) 40 levels Atmospheric Model GFS (2007) T382 64 levels Land ModelIce Mdl SIS LDAS GDAS GSI 6hr 24h r 6hr Ice Ext 6hr Climate Forecast System

13. 13 12Z GSI18Z GSI0Z GSI 9-hr coupled T382L64 forecast guess (GFS + MOM4 + Noah) 12Z GODAS 0Z GLDAS 6Z GSI ONE DAY OF REANALYSIS 18Z GODAS0Z GODAS6Z GODAS

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16. 16 Assimilating Argo Salinity ADCP GODAS GODAS-A/S Comparison with independent ADCP currents. In the east, assimilating Argo salinity reduces the bias at the surface and sharpens the profile below the thermocline at 110 o W. In the west, assimilating Argo salinity corrects the bias at the surface and the depth of the undercurrent core and captures the complex structure at 165 o E.

17. 17 2009+ GODAS Activities Complete CFSRR –Evaluate ODA results Add ARGO salinity Improve climatological T-S relationships and synthetic salinity formulation ENVISAT data? Improve use of surface observations –Vertical correlations (mixed layer) Situation-dependent error covariances (recursive filter formulation) Investigate advanced ODA techniques –Experimental Ensemble Data Assimilation system (with GFDL) –Reduced Kalman filtering (with JPL) –Improved observation representativeness errors (with OSU-JCSDA)

18. 18 Satellite (AVHRR, JASON, QuikSCAT) In situ (ARGO, Buoys, Ships) OCEAN DATA ASSIMILATION RTOFS-GODAS CFS-GODAS OPNL OCEAN FORECASTS Climate Forecast SystemReal-Time Ocean Forecast System Data Cutoff CFS: 2 week data cutoff RTOFS: 24 hour data cutoff MOM-3  MOM-4 HYCOM NASA-NOAA-DOD JCSDA AMSR, GOES JASON, WindSat, QuikSCAT, MODIS Advanced ODA Techniques Observations CLIMATE FORECAST OCEAN FORECAST http://cfs.ncep.noaa.gov/http://polar.ncep.noaa.gov/ofs/ Shared history, coding, and data processing

19. 19 Real Time Ocean Forecast System (RTOFS): A high resolution operational ocean forecast system for the Atlantic

20. 20 Data assimilation: Algorithms Overall employ 3DVar = 2D (along model layers) x 1D (vertical). 2D assumes Gaussian isotropic, inhomogeneous covariance matrix, recursive filtering method (Jim Purser). 1D vertical covariance matrix: Constructed from coarser resolution simulations SST extended to model defined mixed layer. SSH lifting/lowering main pycnocline. T&S profile lifting/lowering below the last observed layer.

21. 21 Data assimilation: Observations –SST: remotely sensed [AVHRR, GOES] (in situ for evaluation) Data collection window: 48 hours –SSH: remotely sensed [JASON, GFO, ENVISAT] Data collection window: 10 days –T&S profiles: ARGO, CTD, XCTD, moorings. Data collection window: 48 hours

22. 22 RTOFS(Atlantic) Daily Products Once daily (issued at 04Z) –Nowcast 1day –Forecast 5 days Grib files for nowcast and forecast –Hourly surface T,S,U,V, SSH, barotropic velocity, mixed layer depth –Hourly interpolated fields on a regular lat-lon grid. –Daily T,S,U,V,W, SSH for 40 depths and for 26 layers Product distribution –NCO servers (ftpprd) –NOMADS [sub-setting] (full data server functions) –MMAB Web server (ftp, graphics) –NODC deep archives

23. 23 Long Term Strategy Implement coupled CFS system for daily global weather prediction –Diurnal SST prediction –Coupled “weather resolution” forecasts to 35 days Expand RTOFS to global domain –Navy collaboration Merge GODAS and RTOFS ODA capabilities (separate models) Merge CFS/GFS ocean and RTOFS ocean capabilities (multi-model ensemble based system) Gradually add ecosystem forecast capability

24. 24 Thanks Questions?

25. 25 Dynamical Model: HYCOM Primitive equation with free surface. State variables: Temperature, Salinity, Velocity, Sea surface elevation. Vertical mixing and vertical viscosity: GISS

26. 26 Dynamical Model: configuration Horizontal grid: orthogonal telescopic, dx/dy~1 Bathymetry: ETOPO2 (NGDC) Coastal boundary: blend of bathymetry and coastline datasets (NGDC) Surface forcing: GDAS/GFS (NCEP) River outflow/runoff: blend of observations (US rivers USGS) and climatology (RIVDIS) Initialization: T,S from blended regional coastal climatologies (Gulf of Maine, Mid and South Atlantic Bights, Gulf of Mexico) and HYDROBASE Boundary data: sea surface elevations and barotropic velocities from climatology (for low frequency) and tidal model (TPX06) (for high frequency) Body Tides: eight tidal constituents