Climate impact assessments are essential for the development of appropriate response strategies, be it in a climate prediction or a climate change context. In this respect, the linking of climate model simulations to impact models requires the definition of a framework that bridges several inherent information gaps between both model types. In its widest sense, the linking between climate and impact models ranges from the simple application of climate indicators, to more sophisticated top-down approaches (e.g. statistical downscaling techniques), to bottom-up techniques like response surfaces, and - ultimately - to an explicit online coupling of both model types. Despite this variety of methods and applications, providers and users frequently face a number of common methodological challenges and contextual demands this session is dedicated to. This year’s special focus of the session is set on:
• Uncertainty quantification, attribution, and representation by different modelling approaches (e.g. top-down vs. bottom-up) and their relation to contextual demands.
Recurrent challenges in the linkage between impact and climate models such as
• the selection of a suitable methodological framework and its inherent assumptions to be taken,
• the influence of the framework on the simulation result,
• approaches to preserve extremes and physical consistency, or
• approaches to deal with probabilistic projections.
The suggested session invites all contributions that address one or more of the raised challenges. We especially welcome contributions from different impact disciplines (e.g. hydrology, agriculture, and cryosphere among others), climate model data providers, climate service centres, and international projects working on the interface between climate and impact models (e.g. COST-VALUE).

The overall aim of the session is to enforce the scientific exchange between the different communities and to promote a joint effort to improve impact assessment techniques. Therefore, we would like to encourage in particular contributions that present their chosen methodological approaches to address the multi-faceted challenges when linking an impact model to a climate model.