The Risk4Insurance-CC project aims to co-develop, test, and validate operational tools for assessing risks relevant to the insurance sector in the context of climate change.

To achieve this goal, it is necessary that risk models—of varying complexity and aimed at estimating the occurrence and/or magnitude of phenomena—be driven by atmospheric variables produced as outputs from climate projections. This process is complex for several reasons:

• The spatial and/or temporal resolution of the modeling chains is often inadequate for estimating phenomena at the local scale.
• Climate simulations are affected by systematic errors that limit their direct use, making data post-processing necessary before they can be employed as input for impact models.
• Multiple sources of uncertainty exist—for example, related to the evolution of greenhouse gas concentrations or the inter-model variability of climate ensembles—which often represent ensembles of opportunity and therefore do not systematically map the full range of uncertainties associated with the representation of phenomena.

In light of these challenges, Risk4Insurance-CC will develop and test innovative modeling approaches designed to manage and mitigate the three issues described above, in line with the most recent and established scientific literature. Another challenge of the project concerns its global scope and the need to deliver not only output data but also operational procedures for the assessment and management of climate risks that the insurance company can use independently. The activities carried out will also help identify and structure the main scientific questions on which collaboration between the partners can be consolidated—for example, the possibility of moving from simple hazard estimation to full risk assessment, the development of multi-risk approaches capable of representing compound, cascading, or hydrological see-saw dynamics, and the evaluation of territorial resilience to such events.

CMCC role
CMCC is the only organisation implementing this contract.

Activities
Task 1 Mapping of output variables from GCM models
Task 2 Selection of GCMs
Task 3 Post-processing of climate simulations
Task 4 Evaluation of ensemble results

Expected results

• Deliverable 1: Summary table on the mapping of output variables from GCM models (Task 1)
• Deliverable 2: Summary table for the selection of GCM models with brief methodological notes (Task 2)
• Deliverable 3: Summary report on the literature-based approach selected for geostatistical interpolation and statistical bias correction of data (Task 3)
• Deliverable 4: Concise review document of the results obtained from applying the procedure to selected hazard use cases (Task 3)
• Deliverable 5: Probabilistic assessment of ensemble results, including a collection of references from scientific literature (Task 4)