Characterisation of long-term climate change by dimension estimates of multivariate palaeoclimatic proxy data

Abstract

The problem of extracting climatically relevant information from multivariate geological records is tackled by characterising the eigenvalues of the temporarily varying correlation matrix. From these eigenvalues, a quantitative measure, the linear variance decay (LVD) dimension density, is derived. The LVD dimension density is shown to serve as a suitable estimate of the fractal dimension density. Its performance is evaluated by testing it for (i) systems with independent components and for (ii) subsystems of spatially extended linearly correlated systems. The LVD dimension density is applied to characterise two geological records which contain information about climate variability during the Oligocene and Miocene. These records consist of (a) abundances of different chemical trace elements and (b) grain-size distributions obtained from sediment cores offshore the East Antarctic coast. The presented analysis provides evidence that the major climate change associated with the Oligocene-Miocene transition is reflected in significant changes of the LVD dimension density. This is interpreted as a change of the interrelationships between different trace elements in the sediment and to a change of the provenance area of the deposited sediment.