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NCAR JOINT IMAGE/MMM SEMINAR

National Center for Atmospheric Research

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Data Assimilation into a Coupled Ocean-ice model

Alain Caya

Environment Canada

A variational data assimilation system is developed for sea ice analysis and forecast. A multicategory sea ice model coupled to the Princeton ocean model, which is driven by atmospheric forcing, is used to model the ice cover in the Labrador Sea. The forecast-error statistics required for the assimilation are obtained from an ensemble approach to data assimilation. Results from assimilation of ice concentrations retrieved from SSM/I data with the enhanced NASA team algorithm are shown. The use of the estimated forecast-error statistics to correct near-surface ocean temperature and salinity is beneficial during the 24-hour forecast. Significant improvement is expected from the assimilation of ice drift data and ocean-related observations and further development of the assimila-

tion system including the time dimension.

Thursday, 3 August 2006, 3:30 PM

Refreshments 3:15 PM

NCAR-Foothills Laboratory

3450 Mitchell Lane

Bldg 2 Auditorium (Rm.1022)