INTERPOLATING A PALEOCLIMATIC TIME-SERIES - NONLINEARITY, PERSISTENCEAND TRENDING IN THE CENOZOIC

Some climatic time series are available only at irregular frequencies, or may show discontinuities. This paper investigates the issues invol ved in interpolating the CENBEN (Cenozoic-Benthic) series, covering 68 m.y., to a regular frequency. Since no single physical model explains this data, interpolation requires fitting a statistical model on the time series itself. The properties of the synthetic series depend crit ically on the model used. Several methods are tried, Gaussian filters, frequency and time domain models, and a Kalman filter. The frequency domain model mainly picks up the long-term properties of the data; how ever, when the window is widened to accommodate movements at shorter h orizons, the result is often to generate spurious cycles. This model a lso tends to mask out nonlinearity, while inducing greater persistence than is justified by the underlying dataset. The Gaussian filter can be set to capture either long or intermediate-term movements, but typi cally does not pick up high frequency variation. Time domain methods s uch as ARIMA models capture more of the high-frequency variations. The best result is obtained using a Kalman filter, which preserves eviden ce of nonlinear oscillations.