TOPAZ evaluation by 1MzR2shh

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									TOPAZ evaluation


 L. Bertino, F. Counillon, P. Sakov
  Mohn-Sverdrup Center/NERSC


   GODAE workshop, Toulouse, June 2009
TOPAZ System overview
     System description
     Validation of TOPAZ
      Data Assimilation
       Satellite Data
                                           Atmospheric
       SLA, SST, Ice,
                                              Data
        In Situ Data


                                     Sea-Ice
                                     model       Atlantic and Arctic
            EnKF                                 model
      Data assimilation
           system                                    Gulf of Mexico
                                     Eco-            model
                                     system model



Uncertainty          Ocean            Hindcast        User-targeted
 estimates      Primary production     studies        ocean forecasting



   Analyze the ocean circulation, sea-ice and biogeochemistry.
Provide real-time forecasts to the general public and industrial users
        The TOPAZ model system
 TOPAZ3: Atlantic and Arctic
     HYCOM + EVP sea-ice model
     11- 16 km horizontal resolution
     22 hybrid layers
 EnKF
     100 members
 Observations
       Sea Level Anomalies (CLS)
       Sea Surface Temperatures (NOAA)
       Sea Ice Concentr. (AMSR, NSIDC)
       Sea ice drift (CERSAT)
       Argo T/S profiles (Coriolis)
 Runs weekly, 10 days forecasts
     ECMWF forcing
     http://topaz.nersc.no/thredds
     http://thredds.met.no (MERSEA…)
   EnKF Correlations




3rd Jan 2006   8th Nov 2006
              The HYCOM model
 3D numerical ocean model
    Hybrid Coordinate Ocean model, HYCOM (U. Miami)
    US Navy global forecasts
 Hybrid coordinate
    Isopycnal in the interior
    Z-coordinate at the surface
    Terrain following (sigma)
 Nesting capability
 Coupled
    Sea-ice model
    Ecosystem models
 Large community (http://www.hycom.org)
                                  Nesting
 Bring dynamically consistent
  information from large-scale
  circulation to coastal seas
     One-way nesting
 “Flather” condition for barotropic
  mode
     Avoids reflection of waves at the
      boundary
 Simple relaxation for the baroclinic
  mode
     And for the tracers
 Arbitrary resolution and orientation
  of the nested grids
   Effect of the
     upgrade
Weekly SSS in Dec. 1999,
        free run

                           MICOM
                           BCM




       TOPAZ3                      TOPAZ4
TOPAZ System overview
      System description
          Validation
       Data Assimilation
      3 Validation criteria
     cf weather forecasting (Murphy, 93)

 Consistency
   Are the operational forecasts in agreement with
    known processes of the ocean circulation?
 Accuracy
   How close to reality are the results?
 Performance (value)
   Advantage over any trivial forecast?
      climatology, persistence
           Validation Metrics
 Problems:
    Validating and comparing GODAE systems consistently
         Different model horizontal grids / Vertical coordinates
    Large amounts of 4D data
         Large data transfers
 Solutions adopted (during Mersea Strand 1, 2003-2004)
      4 Classes of output products (3D, 2D, time series, residuals)
      Common output grids (1/8th deg, projection...)
      Self-documented file format (NetCDF)
      Inter-operable file access (OPeNDAP/THREDDS)
Arctic Metrics
   Validation against hydrographic data




June07




Sept07

     Topaz2      Topaz3          IMR
Online comparison to Argo profiles
          Sparse profiles under ice
                 NPEO deployment 2006




                                        --- TOPAZ
                                        — NPEO




*: North Pole Environment Observatory
Water fluxes
    Sea-ice edge
    Visual comparison
   Ice concentration from model in color,
    SSMI 15% ice contour in black. Ice drift
    is overlaid.
   Good overall correspondence between
    model and data
   Visual comparison allows identification
    of problematic regions
      West of Novaya Zemlya - a tendency
       for the ice edge to drift too little to the
       north during a forecast cycle
      South of Svalbard (Bear Island) model
       ice edge too far to the north
   Issues related to model physics
      Ice-ocean momentum exchange
      Ice models neglect physics which may
       be important on small scales
      Fast ice
      MIZ
    Forecast skills by region
            Barents Sea




Alaska                    Bering Strait




Central
Arctic
           Greenland
           Sea            Kara Sea
SLA assimilation residuals
        Azores box
MERSEA sections updated

 Blue: MERSEA
  Class2 sections
 Red: Sections from
  IMR
TOPAZ System overview
      System description
          Validation
       Data Assimilation
              Assimilation of Ocean Color in
                  HYCOM-NORWECOM

Data:
    Satellite Ocean Color (SeaWIFS)
Coupled Model:
    HYCOM-NORWECOM
          (7 compartments)
Problems:
    • Coupled 3-dimensional
    physical-biological model.
    • High-dimension.
    • Non-Gaussian variables.
Perspectives:
    • Environment monitoring.
    • Fisheries.
    • Methodological developments
    for future coastal HR systems.
   Gaussian anamorphosis with the EnKF
Anamorphosis: prior transformation of the variables in a Gaussian space
(Bertino et al. 2003)
Twin experiments (surface chlorophyll-a synthetic observations)
                           Surface CHLa RMS error




        EnKF                                           Gaussian Anamorphosis
Cut-off of neg. values                                         EnKF


                         Simon & Bertino (OSD, 2009)

								
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