Strong thunderstorms have been studied mainly over flat terrain in the past. However, they are particularly frequent near European mountain ranges, so observations of such storms are needed. This article gives an overview of our existing knowledge on this topic and presents plans for a large European field campaign with the goals to fill the knowledge gaps, validate tools for thunderstorm warnings, and improve numerical weather prediction near mountains.

Despite transdisciplinary approaches being increasingly explored to study droughts and their impacts, their depth and breadth are yet to be fully exploited. By integrating insights from different research fields, we present five key dimensions to deepen and broaden the knowledge co-creation process for drought impact studies. Emphasizing social dynamics and power imbalances, we support hydrologists in developing more integrated, power-sensitive, inclusive, situated, and reflexive studies.

Early warning of increased landslide potential provides situational awareness to reduce landslide-related losses from major storm events. For decades, landslide forecasts relied on rainfall data alone, but recent research points to the value of hydrologic information for improving predictions. In this paper, we provide our perspectives on the value and limitations of integrating subsurface hillslope hydrologic monitoring data and mathematical modeling for more accurate landslide forecasts.

Flood risk assessments help us decide how to reduce the risk of flooding. Since these assessments are based on probabilities, it is hard to check their accuracy by comparing them to past data. We suggest a new way to validate these assessments, making sure they are practical for real-life decisions. This approach looks at both the technical details and the real-world situations where decisions are made. We demonstrate its practicality by applying it to flood emergency planning.

This paper proves the need to conduct an in-depth review of the existing loss modelling framework and makes it clear that only a transdisciplinary effort will be up to the challenge of building global loss models. These two factors are essential to capture the interactions and increasing complexity of the three risk drivers (exposure, hazard, and vulnerability), thus enabling insurers to anticipate and be equipped to face the far-ranging impacts of climate change and other natural events.