Downscaling from GCMs to Local Climate through Stochastic Linkages

摘要

A methodology for estimating local climate variables such as regional precipitation and temperature using atmospheric circulation patterns is developed. A sequence of observed daily air pressure distributions is used to define circulation patterns. The classification of the circulation patterns is constructed using a fuzzy rule based approach. A multivariate stochastic model describes the link between circulation patterns and daily precipitation and daily mean temperatures at a number of selected locations. Model parameters are estimated using observed data. To assess precipitation under changed climate circulation, patterns derived from GCM output pressure values are used to condition the stochastic precipitation model. A link between the occurrence of circulation patterns and extreme precipitation and floods is also discussed. The methodology is demonstrated by the results obtained for selected European and North American locations.