Representing serial correlation of meteorological events and forecasts in dynamic decision-analytic models

Abstract

A recursive solution for optimal sequences of decisions given uncertainty in future weather events, and forecasts of these events, is presented. The formulation incorporates a representation of the autocorrelation that is typically exhibited. The general finite-horizon dynamic decision-analytic framework is employed, with the weather forecast for the previous decision period included as a state variable. Serial correlation is represented through conditional probability distributions of the forecast for the current decision period, given the forecast for the previous period. -from Author