Assimilation of sea surface temperature into CECOM by flux correction |
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| Authors: | Yongsheng Wu Charles Tang Ewa Dunlap |
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| Institution: | (1) Ocean Sciences Division, Bedford Institute of Oceanography, Fisheries and Oceans Canada, Dartmouth, Nova Scotia, B2Y 4A2, Canada; |
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| Abstract: | Sea surface temperature (SST) from a near real-time data set produced from satellites data has been assimilated into a coupled
ice–ocean forecasting model (Canadian East Coast Ocean Model) using an efficient data assimilation method. The method is based
on an optimal interpolation scheme by which SST is melded into the model through the adjustment of surface heat flux. The
magnitude and space–time variation of the adjustment depend on the depth of heat diffusion into the water column in response
to changes in surface flux, the correlation time scale of the data, and model and data errors. The diffusion depth is scaled
by the eddy diffusivity for temperature. The ratio of the model and data errors is treated as an adjustable parameter. To
evaluate the quality of the assimilation, the results from the model with and without assimilation are compared to independent
ship data from the Atlantic Zone Monitoring Program and the World Ocean Circulation Experiment. It is shown that the assimilation
has a significant impact on the modeled SST, reducing the root mean square difference (RMSD) between the model SST and the
ship SST by 0.63°C or 37%. The RMSD of the assimilated SST is smaller than that of the satellite SST by 0.23°C. This suggests
that model simulations or predictions with data assimilation can provide the best estimate of the true SST. A sensitivity
study is performed to examine the change of the model RMSD with the adjustable parameter in the assimilation equation. The
results show that there is an optimal value of the parameter and the model SST is not very sensitive to the parameter. |
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