Improving Uncertain Climate Forecasts Using a New Minimum Mean Square Error Estimator for the Mean of the Normal Distribution

Abstract

When climate forecasts are highly uncertain, the optimal mean squared error strategy is to ignore them. When climate forecasts are highly certain, the optimal mean squared error strategy is to use them as is. In between these two extremes there are climate forecasts with an intermediate level of uncertainty for which the optimal mean squared error strategy is to make a compromise forecast. We present two new methods for making such compromise forecasts, and show, using simulations, that they improve on previously published methods.