Time Interpolation of Forcing Fields in Ocean Models

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Abstract
It is shown that the usual practice of forcing ocean models by linear interpolations of monthly mean data values does not produce a forcing whose mean over a month is the data value required. For wind stress data this can yield monthly mean errors, coherent over a basin, of as much as 0.4 × 10−1 N m−2, with 30%–40% of values being in error by more than 10%. A simple method is given to avoid the difficulty, which involves no change to model computer code and no increase in the amount of data stored internally. Abstract It is shown that the usual practice of forcing ocean models by linear interpolations of monthly mean data values does not produce a forcing whose mean over a month is the data value required. For wind stress data this can yield monthly mean errors, coherent over a basin, of as much as 0.4 × 10−1 N m−2, with 30%–40% of values being in error by more than 10%. A simple method is given to avoid the difficulty, which involves no change to model computer code and no increase in the amount of data stored internally.

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