Forest climatology: reconstruction of mean climatological data for Bavaria, Germany

Abstract

A method is presented that allows the reconstruction of forest climatological data using data available from routine weather stations. Data from 32 routine weather stations were used to estimate the monthly mean values of daily mean air temperature, daily maximum temperature, daily minimum temperature, water vapour pressure, wind speed and precipitation at eight forest climate stations in Bavaria. The data obtained at these stations were used to establish empirical transfer functions to transform data interpolated from the weather stations to values that are valid for the different meteorological conditions in the forests. These empirical transfer functions between observed and interpolated climatological data are derived using a universal regression technique. The results show that using empirical transfer functions reduced the mean absolute errors between observed and estimated monthly mean climatological data significantly as compared to simple interpolation. A 31 year (1965–1995) monthly mean forest climatological data set in Bavaria, reconstructed using Barnes interpolation and the empirical transfer functions, was used to compare the forest microclimate with the surrounding mesoclimate. In addition, the climates of three typical forest regions were compared.