Analysis and management of unexpected and cumulative climate risks in Switzerland

The study on ‘climate-related risks and opportunities’ of the Swiss Federal Office for the Environment (FOEN) provides a comprehensive analysis of climate-related risks and opportunities for Switzerland until 2060. The synthesis of the study results has been the basis for the development of adaptation strategies and measures in Switzerland. The study also identifies knowledge gaps and related missing planning tools for risks, which are difficult to assess as they typically have a low probability of occurrence but have potentially very high impacts for society and/or the environment. Such risks refer in particular to risks, which cumulate through process cascades or are triggered by meteorological/climatic extremes events, which return within shorter time intervals than expected.

To respond to these gaps, a collaborative effort including academic and government institutions at different administrative levels is undertaken in order to explore and analyse the potential of such cumulative risks and actions needed to manage them in Switzerland. The project focuses on two case studies, which are developed in consultation with stakeholders from science, policy and practice at the national and sub-national level.

The case studies analyse risks triggered by meteorological events based on projected and recently published Swiss Climate Scenarios CH2018, considering rare but plausible scenarios where such triggering events cumulate and/or occur in combinations.

We discuss international terminologies and experience with unexpected and cumulative extreme events and put them in relation to the Swiss context. Specifically, we present the cascading processes of the first case study, which focuses on the protective forests in the eastern Swiss Alps. Potential reduction of the protective capacity caused by extreme drought and heat and subsequent increase of risks caused by multiple natural hazards, such as fires and mass movements (snow avalanche, landslide), are assessed in this case study using semi-quantitative methods of risk analysis.