Bringing high-resolution climate data into action: Experiences from the transdisciplinary funding measure RegIKlim

In the RegIKlim funding measure (Regional Information for Action on Climate Change, https://www.fona.de/en/measures/funding-measures/regional-information-for-action-on-climate-change.php), the cross-sectional project NUKLEUS (Actionable Local Climate Information for Germany) is concerned with the provision of useful, actionable, and high-resolution climate information for Germany and the improvement of the interface between climate data and subsequent use, e.g. in impact models for adaptation to climate change, in six pilot regions distributed across Germany.    Climate simulations on the convection-permitting scale were hardly available at the beginning of the project and their simulation areas generally did not cover all model regions or longer time periods. Based on the requirements of the users from the model regions, the prototype of an ensemble with simulations of three regional climate models was generated and thus the first multi-decadal multi-climate model ensemble on a convection-permitting scale (approx. 3 km horizontal resolution) for Germany. It can be shown that the model results are within the expected deviations compared to measured values and that the high-resolution data of the 3 km simulations on short time and spatial scales offer added value compared to the EURO-CORDEX simulations.  In order to improve the interface between climate data and impact models for application, a data and analysis portal (Freva) was set up in NUKLEUS, which facilitates users from the model regions to find suitable data and generate customized data sets using small programs (plugins). The first user-driven plugins have been developed and their application will be presented.   The improvement of the interface also includes information on the uncertainties of certain influencing variables in the impact modeling and the reduction of systematic deviations of the simulations from the observed climate by e.g. bias correction methods. An important result of the uncertainty analysis of the model chain is that the range of climate information is not always the most important variable. Insufficient or outdated land use information can also have a decisive influence on the climate signal. The testing of different bias correction methods shows that the bias correction in principle leads to a reduction in systematic errors, but that the availability of high-resolution observational data for the correction is a major challenge in s. With the statistical refinement approach, good results were achieved for precipitation at a very high resolution of 300-500 m, especially in geographically highly structured regions.  To ensure the translation of the modeling-based information into practical application, the cross-sectional project WIRKsam (Scientific Coordination for the Development of a Regional Climate Register) has developed a set of best practices based on transdisciplinary working group discussions.  To specifically address public spatial planning, it is important to exemplify the utilization potential of the data in pilot application (e.g. development plans) and develop user-oriented capacity-building modules and interpretations guidelines. Through surveys and workshops, transdisciplinary research projects can identify crucial municipal administrative processes, develop information tools for decision support and learn how they could benefit from the new data. This might involve facilitating a cross-departmental understanding of roles and responsibilities.