Extension of the Climate Prediction Center Long-Lead Temperature and Precipitation Outlooks to General Weather Statistics

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  • 1 Department of Soil, Crop and Atmospheric Sciences, Cornell University, Ithaca, New York
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Abstract

The long-lead monthly and seasonal forecasts issued by the Climate Prediction Center literally pertain only to average temperature and total precipitation outcomes, but implicitly contain information regarding other quantities that are correlated with these two variables. This paper presents a method for estimating the conditional probability distribution for any such quantity that is a computable statistic of available daily climatological data, through weighted bootstrap resampling conditional on particular joint (temperature and precipitation) forecast probabilities. Examples illustrating implementation and particular results are provided.

Abstract

The long-lead monthly and seasonal forecasts issued by the Climate Prediction Center literally pertain only to average temperature and total precipitation outcomes, but implicitly contain information regarding other quantities that are correlated with these two variables. This paper presents a method for estimating the conditional probability distribution for any such quantity that is a computable statistic of available daily climatological data, through weighted bootstrap resampling conditional on particular joint (temperature and precipitation) forecast probabilities. Examples illustrating implementation and particular results are provided.

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