2002 Annual

Thursday, 17 January 2002: 2:30 PM
Optimal Observations for Variational Data Assimilation
Armin G. Koehl, SIO/Univ. of California, La Jolla, CA; and D. Stammer
Estimates of the ocean circulation are being conducted by constraining circulation models by a large number of different data sets. One aspect in data assimilation is the question regarding the importance of specific data and their geographic distribution. A solution of this oceanographic experiment design problem is presented. Optimal observations are specified by the types and locations of data points that have the largest impact on the model solution when respective observations are assimilated by a variational assimilation method. In the framework of a North Atlantic model optimal locations for hydrographic observations are calculated for a number of quantities of interest as heat transport and overturning. The performance of the optimal data distribution is tested against canonical section data in data assimilation experiments.

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