Nonlinear and Nonstationary Signal Processing
Carl Isaac Wunsch · Eos · 2002
Stationary linear systems driven by Gaussian processes are the basic representations of time series used in the Earth sciences. A large body of literature has developed around these misleadingly simple models, which straddle statistics, optimization, control, probability theory, and related fields. That fundamental errors of inference are still made in the refereed literature is perhaps a testimony to the subtleties and confusion that arise when statistics meets the real geophysical world. A major journal devoted to modern climate studies recently felt compelled to publish a tutorial explaining the importance of avoiding aliasing errors when sampling meteorological variables; this subject was clearly understood 100 years ago.