Increasing greenhouse gas concentrations are expected to enhance the interannual variability of summer climate in Europe and other mid-latitude regions, potentially causing more frequent heatwaves. Climate models consistently predict an increase in the variability of summer temperatures in these areas, but the underlying mechanisms responsible for this increase remain uncertain. Here we explore these mechanisms using regional simulations of recent and future climatic conditions with and without land-atmosphere interactions. Our results indicate that the increase in summer temperature variability predicted in central and eastern Europe is mainly due to feedbacks between the land surface and the atmosphere. Furthermore, they suggest that land-atmosphere interactions increase climate variability in this region because climatic regimes in Europe shift northwards in response to increasing greenhouse gas concentrations, creating a new transitional climate zone with strong land-atmosphere coupling in central and eastern Europe. These findings emphasize the importance of soil-moisture-temperature feedbacks (in addition to soil-moisture-precipitation feedbacks) in influencing summer climate variability and the potential migration of climate zones with strong land-atmosphere coupling as a consequence of global warming. This highlights the crucial role of land-atmosphere interactions in future climate change.

Rain gauges and weather radars both constitute important devices for operational precipitation monitoring. Gauges provide accurate yet spotty precipitation estimates, while radars offer high temporal and spatial resolution yet at a limited absolute accuracy. We propose a simple methodology to combine radar and daily rain-gauge data to build up a precipitation dataset with hourly resolution covering a climatological time period. The methodology starts from a daily precipitation analysis, derived from a dense rain-gauge network. A sequence of hourly radar analyses is then used to disaggregate the daily analyses. The disaggregation is applied such as to retain the daily precipitation totals of the raingauge analysis, in order to reduce the impact of quantitative radar biases. Hence, only the radar's advantage in terms of temporal resolution is exploited. In this article the disaggregation method is applied to derive a 15-year gridded precipitation dataset at hourly resolution for Switzerland at a spatial resolution of 2 km. Validation of this dataset indicates that errors in hourly intensity and frequency are lower than 25% on average over the Swiss Plateau. In Alpine valleys, however, errors are typically larger due to shielding effects of the radar and the corresponding underestimation of precipitation periods by the disaggregation. For the flatland areas of the Swiss Plateau, the new dataset offers an interesting quantitative description of high-frequency precipitation variations suitable for climatological analyses of heavy events, the evaluation of numerical weather forecasting models and the calibration/operation of hydrological runoff models.