Homogenization of German daily and monthly mean temperature time series

Abstract

Long time series can be potentially influenced by breakpoints. This study presents an automatic procedure to detect and homogenize breakpoints in German daily and monthly mean temperature time series. To verify breakpoints metadata information is used. The homogenization tool is evaluated with a synthetic data set with the result of smaller mean bias and RMSE than the unhomogenized data. For homogenized German temperature data in most cases, smaller and less breakpoints are detected compared to the raw data. The mean differences of trends before and after homogenization is small (0.05 K/length of each time series). The result of the homogenization is presented in three case studies. After homogenization, the trend in these cases is closer to the calculated trend for Germany calculated using a gridded data set.