The prediction of Australian land surface temperatures using near global sea surface temperatures

Abstract

It is widely accepted that large-scale variations of the atmosphere on monthly and longer time scales are commonly related to similar time scale variations in the atmosphere boundary conditions. Evidence for such forced variations is widespread in the literature, and includes the variability of Australasian rainfall associated with Pacific sea surface temperature (SSTs), linked to the El Nino-Southern Oscillation (ENSO). In this study a combined eigenvector analysis has been used to investigate the variability and predictability of Australian seasonal temperatures and their relationship to anomalies in near global SSTs. The findings of this study indicate that the variability of Australian seasonal temperatures is dominated by the large scale with some 80 per cent of the field variance being contained in the first five principal components.