Salinity from the ECMWF ocean analysis

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Salinity from the ECMWF ocean analysis
Magdalena A. Balmaseda
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Salinity in the ECMWF ocean analysis
Outline
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(No Transcript)
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Operational Ocean Analysis Schedule
D1

• BRT ( Behind real time ocean analysis) 12 days
  delay
• For seasonal Forecasts.
• Continuation of the historical ocean
  reanalysis
• NRT (Near real time ocean analysis) No delay
• For Monthly forecasts

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System-3

• INITIALIZATION
• ERA-40 data to initialize ocean and atmosphere
• Bias correction in ocean assimilation.
• Assimilation of salinity data.
• Assimilation of altimeter-derived sea level
  anomalies and global trend.
• Retrospective Ocean Reanalysis back to 1959
• 3D OI, ENACT/ENSEMBLES ocean data,

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OBSERVATION COVERAGE in a 10-day window
?Moorings SubsurfaceTemperature ? ARGO floats
Subsurface Temperature and Salinity XBT
Subsurface Temperature
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OSES Effect of Salinity Observations on Surface
Salinity2001-2006
Salinity observations (mainly for Argo data) has
a large impact on the mean state
Balmaseda et al 2007, GRL
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Results from Data Retention ExperimentsFit to
Salinity observations (rms error)
Tropical Indian
Equatorial Atlantic
ALL NO_ALTI NO_ARGO NO_AA
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RESULTS FROM GSOP OCEAN REANALYSIS
INTERCOMPARSION

• 12 different ocean reanalysis were compared
• Ensemble meansignal
• Ensemble spreadnoise

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Salinity Variability

• Salinity variability dominated by spin-up effects
  in several cases.
• There is no consistency among reanalyes

EQPAC EQATL EQINDTRPAC TRATL NPAC NATL GLOBAL
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BENEFITS OF SURFACE SALINITY OBSERVATIONS

• Current uncertainty in surface salinity analysis
  is large.
• Large uncertainties in precipitation, river
  outflow, melting ice
• Uncertainties have large spatial scale. SMOS
  could be of help
• Potential benefits
• Better Initialization of mixed layer
• Better representation of the Atlantic Ocean
• Inverse problem estimation of P-E?
• It is possible to combine with Altimeter data
  (global trends)