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Review of Ocean Data Assimilation and Forecasting at NCEP/EMC

S. Lord, D. Behringer,

H-L Pan, H. Tolman

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Overview

• GODAS and operational CFS

• CFS Reanalysis (and Reforecast) project

• Ocean observations for climate and real-time applications

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Seasonal to Interannual Prediction at NCEPOperational System since August 2004

ClimateForecastSystem(CFS)

Ocean ModelMOMv3

quasi-global1ox1o (1/3o in tropics)

40 levels

Atmospheric ModelGFS (2003)

T6264 levels

GODAS (2003)3DVAR

XBTTAOTritonPirataArgo

Salinity (syn.)TOPEX/Jason-1

Reanalysis-23DVART62L28

OIv2 SSTLevitas SSS clim.

1. Ocean reanalysis (1980-present) provides initial conditions for retrospective

CFS forecasts used for calibration and research2. Stand-alone version with a 14-day lagupdated routinely

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Number of Temperature Observations per Month as a Function of Depth

5http://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

6http://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

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Suru Saha and Hua-Lu Pan, EMC/NCEP

With Input fromStephen 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)

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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)

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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)

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Component UpgradesComponent Ops CFS 2010 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 depth 2000 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 analysis Daily hires analysis

Coupling None Fully coupled background forecast (same as free forecast)

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CFSRR Production ConfigurationCovers 31 years (1979-2009) + 25 overlap months

6 Simultaneous Streams• Jan 1979 – Dec 1985 7 years• Nov 1985 – Feb 1989 3 years• Jan 1989 – Feb 1994 5 years• Jan 1994 – Dec 1998 5 years• Apr 1998 – Dec 2004 6 years• Apr 2004 – Dec 2009 5 years

• Overlap months are for ocean and land spin ups• Satellite bias correction spinup for each instrument (3

months)

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CFSRR at NCEP

GODAS3DVAR

Ocean ModelMOMv4

fully global1/2ox1/2o (1/4o in tropics)

40 levels

Atmospheric ModelGFS (2007)

T382 64 levels

Land Model Ice Mdl SISLDAS

GDASGSI

6hr

24hr

6hr

Ice Ext6hr

Climate Forecast System

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12Z GSI 18Z GSI 0Z GSI

9-hr coupled T382L64 forecast guess (GFS + MOM4 + Noah)

12Z GODAS

0Z GLDAS

6Z GSI

ONE DAY OF REANALYSIS

18Z GODAS 0Z GODAS 6Z GODAS

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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 110oW.

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 165oE.

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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)

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Satellite(AVHRR, JASON, QuikSCAT)

In situ(ARGO, Buoys, Ships)

OCEAN DATA ASSIMILATION

RTOFS-GODASCFS-GODAS

OPNL OCEAN FORECASTS

Climate Forecast System Real-Time Ocean Forecast System

Data Cutoff

CFS: 2 week data cutoff RTOFS: 24 hour data cutoff

MOM-3 MOM-4 HYCOM

NASA-NOAA-DODJCSDA

AMSR, GOESJASON, WindSat,

QuikSCAT, MODISAdvanced

ODA Techniques

Observations

CLIMATE FORECAST OCEAN FORECAST

http://cfs.ncep.noaa.gov/ http://polar.ncep.noaa.gov/ofs/

Shared history, coding, and data

processing

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Real Time Ocean Forecast System (RTOFS): A high resolution operational ocean

forecast system for the Atlantic

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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.

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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

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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

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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

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ThanksQuestions?

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Dynamical Model: HYCOM

• Primitive equation with free surface.

• State variables: Temperature, Salinity, Velocity, Sea surface elevation.

• Vertical mixing and vertical viscosity: GISS

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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