Ongoing climate change is leading to considerable alterations of the mean climate, the day-to-day weather and their variability. This poses substantial challenges for stakeholders and increases the urgency to develop adequate adaptation and mitigation strategies. In order to represent the local changes in climate across different regions as accurately as possible, and provide useful and usable information for stakeholders, we use an ensemble of convection-permitting climate simulations to quantify the projected changes for user-relevant climate indices for Southern and Central Germany. A wide range of temperature, precipitation, and user-oriented climate indices relevant to various stakeholder applications to address their information requirements are considered. After bias adjustment, the indices are in very good agreement with results using the HYRAS dataset, though small shortcomings remain. Regarding the climate change signal, several different patterns can be identified. For high temperature indices, a significant increase is observed, particularly for very hot days and tropical nights. On the other hand, the number of frost and ice days significantly decreases with global warming. Other indices like hiking days and summer dry days show comparatively small changes. While relative changes are largest for high altitude areas for high temperature indices, their absolute changes are largest for low areas like the Rhine Valley. For high temperature indices, an increase both in mean values and variability is found with global warming. The opposite is true for snow days, ice days and winter service days. We conclude that convection-permitting simulations can be key to provide usable user-relevant climate indices for recent climate conditions and projections for future decades, both considering high spatial resolution and uncertainty estimations. Such a database can thus be extremely useful for the development and implementation of informed adaptation measures to climate change, as discussed in detail for specific examples in Germany.
Pinto et al. (Thu,) studied this question.