TEMPORARY DIMENSIONS OF MULTIVARIATE DATA FROM PALEOCLIMATE RECORDS — A NOVEL MEASURE FOR DYNAMIC CHARACTERIZATION OF LONG-TERM CLIMATE CHANGE

Abstract

Standard techniques of nonlinear data analysis are difficult to apply to short or insufficiently resolved multivariate time series. We demonstrate that dimension estimation based on the decay of eigenvalues of the covariance matrix yields qualitatively robust characteristics even in the case of very short measurement series. The uncertainty of these characteristics is discussed for both: synthetic data sets and measurement data. We apply this approach to measurements of trace element abundances in a marine sediment core obtained at the East Antarctic coast and discuss the results from a paleoclimate point of view.