In recent years, several decadal prediction systems have been developed to provide multi-year predictions of the climate for the next 5-10 years. On the global scale, high decadal predictability has been identified for the North Atlantic sector, often extending over Europe. The first full regional hindcast ensemble, derived from dynamical downscaling, was produced within the German MiKlip project ('decadal predictions'). The ensemble features annual starting dates from 1960 to 2017, with 10 decadal hindcasts per starting year. The global component of the prediction system uses the MPI-ESM-LR and the downscaling is performed with the regional climate model COSMO-CLM (CCLM). The present study focusses on a range of aspects dealing with the skill and added value of regional decadal temperature predictions over Europe. The results substantiate the added value of the regional hindcasts compared to the forcing global model as well as to uninitialized simulations. The results show that the hindcasts are skilful both for annual and seasonal means, and that the scores are comparable for different observational reference data sets. The predictive skill increases from earlier to more recent start-years. A recalibration of the simulation data generally improves the skill further, which can also be transferred to more user-relevant variables and extreme values like daily maximum temperatures and heating degree-days. These results provide evidence of the potential for the regional climate predictions to provide valuable climate information on the decadal timescale to users.

Abstract. The current state of development and the prospects of the regional MiKlip decadal prediction system for Europe are analysed. The MiKlip regional system consists of two 10-member hindcast ensembles computed with the global coupled model MPI-ESM-LR downscaled for the European region with COSMO-CLM to a horizontal resolution of 0.22∘ (∼25 km). Prediction skills are computed for temperature, precipitation, and wind speed using E-OBS and an ERA-Interim-driven COSMO-CLM simulation as verification datasets. Focus is given to the eight European PRUDENCE regions and to lead years 1–5 after initialization. Evidence of the general potential for regional decadal predictability for all three variables is provided. For example, the initialized hindcasts outperform the uninitialized historical runs for some key regions in Europe, particularly in southern Europe. However, forecast skill is not detected in all cases, but it depends on the variable, the region, and the hindcast generation. A comparison of the downscaled hindcasts with the global MPI-ESM-LR runs reveals that the MiKlip prediction system may distinctly benefit from regionalization, in particular for parts of southern Europe and for Scandinavia. The forecast accuracy of the MiKlip ensemble is systematically enhanced when the ensemble size is increased stepwise, and 10 members is found to be suitable for decadal predictions. This result is valid for all variables and European regions in both the global and regional MiKlip ensemble. The present results are encouraging for the development of a regional decadal prediction system.

Regional climate predictions for the next decade are gaining importance, as this period falls within the planning horizon of politics, economy, and society. The potential predictability of climate indices or extremes at the regional scale is of particular interest. The German MiKlip project ("mid-term climate forecast") developed the first regional decadal prediction system for Europe at 0.44 resolution, based on the regional model COSMO-CLM using global MPI-ESM simulations as boundary conditions. We analyse the skill of this regional system focussing on extremes and user-oriented variables. The considered quantities are related to temperature extremes, heavy precipitation, wind impacts, and the agronomy sector. Variables related to temperature (e.g., frost days, heat wave days) show high predictive skill (anomaly correlation up to 0.9) with very little dependence on lead-time, and the skill patterns are spatially robust. The skill patterns for precipitation-related variables (e.g., heavy precipitation days) and windbased indices (like storm days) are less skilful and more heterogeneous, particularly for the latter. Quantities related to the agronomy sector (e.g., growing degree days) show high predictive skill, comparable to temperature. Overall, we provide evidence that decadal predictive skill can be generally found at the regional scale also for extremes and user-oriented variables, demonstrating how the utility of decadal predictions can be substantially enhanced. This is a very promising first step towards impact-related modelling at the regional scale and the development of individual useroriented products for stakeholders.

Abstract. Heat extremes and associated impacts are considered the most pressing issue for German regional governments with respect to climate adaptation. We explore the potential of an unique high-resolution convection permitting (2.8 km), multi-GCM ensemble with COSMO-CLM regional simulations (1971–2100) over Germany regarding heat extremes and related impacts. We find an improved mean temperature beyond the effect of a better representation of orography on the convection permitting scale, with reduced bias particularly during summer. The projected increase in temperature and its variance favors the development of longer and hotter heat waves, especially in late summer and early autumn. In a 2° (3°) warmer world, a 26 % (100 %) increase in the Heat Wave Magnitude Index is anticipated. Human heat stress (UTCI > 32°C) and local-specific parameters tailored to climate adaptation, revealed a dependency on the major landscapes, resulting in significant higher heat exposure in flat regions as the Rhine Valley, accompanied by the strongest absolute increase. A non-linear, exponential increase is anticipated for parameters characterizing strong heat stress (UTCI > 32°C, tropical nights, very hot days). Providing local-specific and tailored climate information, we demonstrate the potential of convection permitting simulations to facilitate improved impact studies and narrow the gap between climate modelling and stakeholder requirements for climate adaptation.

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