Assimilating Copernicus SST data into a pan-Arctic ice-ocean coupled model with a local SEIK filter

Assimilating Copernicus SST data into a pan-Arctic ice-ocean coupled model with a local SEIK filter AbstractSea surface temperature (SST) data from the Copernicus Marine Service are assimilated into a pan-Arctic ice-ocean coupled model using the ensemble-based Local Singular Evolutive Interpolated Kalman (LSEIK) filter. It is found that the SST deviation between model hindcasts and independent SST observations is reduced by the assimilation. Compared with model results without data assimilation, the deviation between the model hindcasts and independent SST observations has decreased by up to 0.2 °C at the end of summer. The strongest SST improvements are located in the Greenland Sea, the Beaufort Sea and the Canadian Arctic Archipelago. The SST assimilation also changes the sea ice concentration (SIC). Improvements of the ice concentrations are found in the Canadian Arctic Archipelago, the Beaufort Sea and the central Arctic basin, while negative effects occur in the west area of the Eastern Siberian Sea and the Laptev Sea. Also sea ice thickness (SIT) benefits from ensemble SST assimilation. A comparison with upward-looking sonar observations reveals that hindcasts of SIT are improved in the Beaufort Sea by assimilating reliable SST observations into light ice areas. The study illustrates the advantages of assimilating SST observations into an ice-ocean coupled model system and suggests that SST assimilation can improve SIT hindcasts regionally during the melting season. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Atmospheric and Oceanic Technology American Meteorological Society

Assimilating Copernicus SST data into a pan-Arctic ice-ocean coupled model with a local SEIK filter

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Publisher
American Meteorological Society
Copyright
Copyright © American Meteorological Society
ISSN
1520-0426
D.O.I.
10.1175/JTECH-D-16-0166.1
Publisher site
See Article on Publisher Site

Abstract

AbstractSea surface temperature (SST) data from the Copernicus Marine Service are assimilated into a pan-Arctic ice-ocean coupled model using the ensemble-based Local Singular Evolutive Interpolated Kalman (LSEIK) filter. It is found that the SST deviation between model hindcasts and independent SST observations is reduced by the assimilation. Compared with model results without data assimilation, the deviation between the model hindcasts and independent SST observations has decreased by up to 0.2 °C at the end of summer. The strongest SST improvements are located in the Greenland Sea, the Beaufort Sea and the Canadian Arctic Archipelago. The SST assimilation also changes the sea ice concentration (SIC). Improvements of the ice concentrations are found in the Canadian Arctic Archipelago, the Beaufort Sea and the central Arctic basin, while negative effects occur in the west area of the Eastern Siberian Sea and the Laptev Sea. Also sea ice thickness (SIT) benefits from ensemble SST assimilation. A comparison with upward-looking sonar observations reveals that hindcasts of SIT are improved in the Beaufort Sea by assimilating reliable SST observations into light ice areas. The study illustrates the advantages of assimilating SST observations into an ice-ocean coupled model system and suggests that SST assimilation can improve SIT hindcasts regionally during the melting season.

Journal

Journal of Atmospheric and Oceanic TechnologyAmerican Meteorological Society

Published: Jul 18, 2017

References

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