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 t he Lament model to demonstrate that these biases can be effectively reduced with a simple statistical correction, and the bias-corrected model can hav e a more realistic internal variability as well as an improved forecast per formance. The results reported here should be of practical use to other oce an-atmosphere coupled models for climate prediction.