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On assimilating sea surface temperature data into an ocean general circulation model Weaver, Anthony T.

Abstract

The feasibility of sea surface temperature (SST) data improving the performance of an ocean general circulation model (OGCM) is investigated through a series of idealized numerical experiments. The GFDL Bryan-Cox-Semtner primitive equation model is set-up as an eddy resolving, unforced, flat bottomed channel of uniform depth. 'Observed' SST data taken from a reference ocean established in a control run are continuously assimilated into an 'imperfect' model using a simple 'nudging' scheme based on a surface relaxation condition of the form Q = C(SST — T₁) where Q is the heat flux and T₁ is the temperature at the top level of the model. The rate of assimilation is controlled by adjusting the constant inverse relaxation time parameter C. Numerical experiments indicate that the greatest improvement in the model fields is achieved in the extreme case of infinite assimilation (i.e., C = ᅇ) in which the 'observed' SST is directly inserted into the model. This improvement is quantified by monitoring the reduction in the root mean square (RMS) errors relative to the simulated reference ocean. Assimilation with longer relaxation time-scales (i.e., smaller C's) proves quite ineffective in reducing the RMS errors. The improvement in the direct insertion numerical experiment stems from the model's ability to transfer assimilated SST into subsurface information through strong advective processes. The assimilation of cool surface data induces convective overturning which transfers the 'cool' information downward rapidly but adversely affects the vertical thermal structure by an unrealistic deepening of the mixed layer. By contrast, warm surface data do not penetrate downward readily. Thus, the systematically biased downward flux of coolness gradually produces unrealistically cool subsurface waters.

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