A Multivariate Analysis of Arctic Climate in GCMs

Abstract

A multivariate analysis of Arctic climate is performed comparing the observed climate with that simulated by four different global climate models (GCMs). The focus is on the patterns of temporal and spatial variability in several climate parameters (sea level pressure, temperature, specific humidity, and precipitation). There are broad similarities between the observed data and all the CYCM climates. There are, however, severe major differences. The observed data show the Arctic climate to be dominated by the summertime pattern of temperature and humidity, which is decoupled from the atmospheric circulation. The winter patterns explains less of the observed variance but show a much closer association between temperature and the large-scale circulation. The GCMS, in contrast, overemphasize the winter season and show more of a large-scale advective control on summertime temperature patterns. Possible reasons for these differences are suggested, and their implications for GCM climate studies are discussed. The shortcomings in the GCMs point to the need for improvements in boundary layer rendition, in the treatment of Arctic stratus, and in sea ice simulations through coupled ocean models and the inclusion of ice dynamics.