Bias correction of an ocean-atmosphere coupled model


A serious problem in the initialization of a climate forecast model is the model-data incompatibility caused by systematic model biases. Here we use the Lamont model to demonstrate that these biases can be effectively reduced with a simple statistical correction, and the bias-corrected model can have a more realistic internal variability as well as an improved forecast perfomance. The results reported here should be of practical use to other ocean-atmosphere coupled models for climate prediction.

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