Estimating monthly and seasonal distributions of temperature and precipitation using the new CPC long-range forecasts

Abstract

A method for transforming underlying climatological distributions for monthly and seasonal mean temperature and monthly and seasonal total precipitation, in a manner consistent with long-range forecasts by the U.S. Climate Prediction Center, is developed. These transformations are summarized as simple equations into which a user may substitute a forecast probability value and calculate the parameters of a conditional probability distribution. These distributions can then be used to evaluate probabilities associated with user-defined temperature and precipitation outcomes. Examples are given to show the ease of use and interpretability.