A statistical modeling approach for the simulation of local paleoclimatic proxy records using general circulation model output

A statistical modeling approach is proposed for the simulation of local pal eoclimatic proxy records using general circulation model (GCM) output, A me thod for model-consistent statistical downscaling to local weather conditio ns is developed which can be used as input for process-based proxy models i n order to investigate to what extent climate variability obtained from pro xy data can be represented by a GCM, and whether, for example, the response of glaciers to climatic change can be reproduced. Downscaling is based on a multiple linear forward regression model using daily sets of operational weather station data and large-scale predictors at various pressure levels obtained from reanalyses of the European Centre for Medium-Range Weather Fo recasts, Composition and relative impact of predictors vary significantly f or individual. stations within the area of investigation. Owing to a strong dependence on individual synoptic-scale patterns, daily data give the high est performance which can be further increased by developing seasonal-speci fic relationships. The model is applied to a long integration of a GCM coup led to a mixed layer ocean (ECHAM4/MLO) simulating present-day and preindus trial climate variability. Patterns of variability are realistically simula ted compared to observed station data within an area of Norway for the peri od 1868-1993.