Interpretation of North Pacific Variability as a Short- and Long-Memory Process*

A major difficulty in investigating the nature of interdecadal variability of climatic time series is their shortness. An approach to this problem is through comparison of models. In this paper a first-order autoregressive [AR(1)] model is contrasted with a fractionally differenced (FD) model as applied to the winter-averaged sea level pressure time series for the Aleutian low [the North Pacific (NP) index] and the Sitka winter air temperature record. Both models fit the same number of parameters. The AR(1) model is a ''short-memory'' model in that it has a rapidly decaying autocovariance sequence, whereas an FD model exhibits ''long memory'' because its autocovariance sequence decays more slowly.