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Data Assimilation of Ocean and Sea-ice Data for Forecast and Reanalysis with the TOPAZ System

Data Assimilation of Ocean and Sea-ice Data for Forecast and Reanalysis with the TOPAZ System
Type: 
Parallel
Time: 
16 March 2010 - 3:30pm
Laurent P. Bertino1, François Counillon2, Pavel Sakov3, Intissar Keghouche4
1Mohn-Sverdrup Center, Nansen Environmental and Remote Sensing Center, Thormøhlensgt. 47, Bergen, 5006, Norway, Phone +47 55 20 58 61, Fax +47 55 20 58 01
2Mohn-Sverdrup Center, Nansen Environmental and Remote Sensing Center, Thormøhlensgt. 47, Bergen, 5006, USA, francois [dot] counillon [at] nersc [dot] no
3Mohn-Sverdrup Center, Nansen Environmental and Remote Sensing Center, Thormøhlensgt. 47, Bergen, 5006, USA, pavel [dot] sakov [at] nersc [dot] no
4Nansen Environmental and Remote Sensing Center (NERSC), Thormøhlensgate 47, Bergen, Norway, Phone +47-55-20-58-57

In the frame of the European MyOcean project (www.myocean.eu.org), a newer version of the TOPAZ North Atlantic and Arctic forecasting system is being integrated in reanalysis mode over the last 20 years. TOPAZ is a data assimilative system using the Ensemble Kalman Filter (EnKF). The model has been upgraded to the newest version of the HYbrid Coordinate Ocean Model (HYCOM) with a resolution of 11-16 km, with additional features in the snow module of the sea-ice model, and river run-off based on a hydrological model. The EnKF is assimilating satellite altimeter track, sea ice concentration and drift velocity, satellite SST, and T-S profiles from Argo buoys and gliders. Finally, ongoing efforts are directed towards the assimilation of ocean color data in the coupled HYCOM-NORWECOM model. The forecasts and reanalysis data services are following a free and open data policy. The data are used by the environment agencies, weather services, the oil and gas industry, and not the least for planning research cruises.

The presentation will show the impact of the different data sources in the assimilation system and address the issues of physical consistency and accuracy of the data assimilation method.

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National Science Foundation | Division of Arctic Sciences
National Science Foundation
National Oceanic and Atmospheric Administration
National Oceanic and Atmospheric Administration
International Arctic Systems for Observing the Atmosphere
International Arctic Systems for Observing the Atmosphere
Study of Environmental Arctic Change
Study of Environmental Arctic Change
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Arctic Ocean Sciences Board
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Alaska Ocean Observing System
Department of Energy
Department of Energy
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National Aeronautics and Space Administration
World Wildlife Fund
WWF
Association of Polar Early Career Scientists
Association of Polar Early Career Scientists
Bureau of Land Management
Bureau of Land Management
International Study of Arctic Change
International Study of Arctic Change
ArcticNet
ArcticNet
DAMOCLES
Developing Arctic Modeling and Observing Capabilities for Long-term Environmental Studies

This work is supported by the National Science Foundation (NSF) under the ARCUS Cooperative Agreement ARC-0618885. Any opinions, findings, and conclusions or recommendations expressed do not necessarily reflect the views of the NSF.