Robust, reliable and user-targeted climate model data are essential to drive impact models in order to assess future climate change impacts. The interface between climate and impact models is a critical location in the model chain, and its design deserves particular attention. In practice, it is constrained by the availability of climate model data, the impacts to be addressed, the type of impact model and the target audience. Those constrains mean that there is no single best design, but instead, the way climate and impact models are linked has to be tailored for each impact assessment. Understanding the effects of the interface design on the estimated impacts is essential in order to reveal and reduce uncertainties, and to guide future assessments. In particular, the choice of the downscaling and bias adjustment method is important, as it can represent a significant source of uncertainty in the projections.

The session is dedicated to the interface between climate and impact models. We will explore and compare different approaches to link climate and impact models, discuss long-standing challenges and ways to overcome them. We especially welcome contributions on - but not limited to:

• the pre-selection and pre-processing of climate model data sets,
• the comparison and selection of suitable downscaling and bias adjustment techniques,
• the uncertainties related to the climate and impact model linking step,
• methods to include probabilistic climate change information in impact assessments,
• the challenge of information distillation to provide climate services.

We encourage researchers and end-users from different sectors and regions to contribute to this session to foster cross-sectorial discussions.