Using forest growth data from the Austrian Central Alps to validate a climate interpolation model. Sub project: Meteorology

One difficulty for the evaluation of climate change impact studies arises from the use of spatially interpolated climate data as ecosystem model input. Climate interpolation models are usually validated by cross validation, using weather stations that have not been included in the data set used for interpolation. Here, error statistics cannot be given for places where there are no weather stations. This applies especially to alpine regions, where the effect of topography on climate is highly relevant. The objective of this project is to use forest growth data (increment cores and dendrometer measurements) sampled along altitudinal gradients with different aspect as proxy data to validate a climate interpolation model in terms of its predictions of temperature, precipitation and solar radiation. The project focuses on Norway spruce and Swiss stone pine at 4 high altitude regions near alpine barrier lakes in Tyrol, Austria.