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This paper proposes an information theory approach to estimate the number ofchangepoints and their locations in a climatic time series. A model isintroduced that has an unknown number of changepoints and allows for seriesautocorrelations, periodic dynamics, and a mean shift at each changepoint time.An objective function gauging the number of changepoints and their locations,based on a minimum description length (MDL) information criterion, is derived.A genetic algorithm is then developed to optimize the objective function. Themethods are applied in the analysis of a century of monthly temperatures fromTuscaloosa, Alabama.

An MDL approach to the climate segmentation problem