Bias correction of an ocean-atmosphere coupled model
Abstract
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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