Improved statistical downscaling models based on canonical correlation analysis, for generating temperature scenarios over Greece

Abstract

This study attempts to improve upon statistical downscaling (Sd) models based on the classical approach which uses canonical correlation analysis, in order to generate temperature scenarios over Greece. Considering the long-term trends of the predictor variables (1,000–500 hPa thickness field geopotential heights—using NCEP data) and the predictand variables (observed mean maximum summer temperatures over Greece), a new Sd model is constructed. Regression models using generalized least square estimators are developed in order to eliminate the trends within the time series. The advantages of the suggested method compared to the classical method are quantified in terms of a number of distinct performance criteria, e.g., Mean squared error which is the basic criterion of the estimated downscaled values relative to the observed. Finally, the suggested Sd models are used to evaluate the effects of a future climate scenario (IPCC-SRES: A2) on mean maximum summer temperatures over Greece. The results from the climate projection indicate a temperature increase for the period 2070–2100 which is smaller than the corresponding increase from the classical approach.