ABSTRACT: A 2-step downscaling method for general circulation model (GCM) outputs is presented. The investigation is based on daily upper air geopotential and humidity fields (Atlantic-European sector) and surface observations (52 German climate stations) from 1966 to 1993. In the first step, significant circulation patterns are identified using cluster analysis which takes advantage of information exclusively from upper air fields. This leads to composite charts which can be readily interpreted synoptically, but which only explain a portion of the variance of the local weather elements. In the second step, a conditional (weather pattern-dependent) stepwise screening regression analysis is performed for each weather element and 6 German climate regions. A principal finding is that the modelled (downscaled) local climate is in good agreement with observations, particularly for the temperature regime, due to the fact that a major part of the variance is explained after the 2 steps. Including 700 hPa humidity slightly improves the explained variance. An application to a GCM control run is added. It shows that the method is capable of reconstructing interannual variability of local weather elements.

KEY WORDS: Climate modelling · Statistical downscaling · Cluster analysis · Regression analysis · General circulation models

Published in CR Vol. 8, No. 3 (1997) on October 9
ISSN: 0936-577X. Copyright © Inter-Research, Oldendorf/Luhe, 1997