Downscaling climate change scenarios for apple pest and disease modeling in Switzerland.

The article presents a study which focuses on the exemplification of closing the gap between climate change scenarios and impact modeling of pests and diseases on an hourly time scale in Switzerland. The study uses the Bayesian multi-model combination algorithm to obtain the seasonal probabilistic climate change signals of changes in temperature and precipitation. Results show that a shift in the occurrence and duration of life phases relevant for pest control is indicated in codling moth.