Towards operational impact forecasting of building damage from winter windstorms in Switzerland

Abstract

National meteorological and hydrological services issue warnings for severe weather events, typically based on stakeholder‐agreed fixed thresholds of meteorological parameters such as wind speeds or precipitation amounts. Yet societal decisions on preventive actions depend on the expected impacts of the weather event. In order to better inform such preventive actions, meteorological services are currently working towards including expected impacts into their warnings. We develop an open‐source impact forecasting system for building damage due to winter windstorms in Switzerland. It combines a numerical ensemble weather prediction model with exposure and vulnerability data. This system forecasts expected building damage in Swiss Francs with a 2‐day lead time on a 500‐m grid or aggregated to administrative regions. We compare the forecasted building damage with insurance claims in the canton of Zurich. The uncertainty of the impact forecasts is large. For the majority of days with severe winter windstorm damage, the mean forecasted damage was in the right order of magnitude, with one missed event and one false alarm. For thunderstorms and foehn storms, the rate of missed events and false alarms is much higher, most likely related to the limited meteorological forecast skill. Such impact forecasts can inform decision makers on preventive actions, such as allocating emergency response and other assets. Additionally, impact forecasts could also help communicating the severity of the upcoming event to the general public as well as indirectly help meteorological forecasters with taking warning decisions.

How to provide actionable information on weather and climate impacts?–A summary of strategic, methodological, and technical perspectives

“…climate forecast scale (Röösli et al, 2021). Therefore, impactrelated services are in line with other key strategic developments (probabilistic and seamless forecasts) and, if produced by an integrated HEV-model (Figure 1), can help to unite existing NMHS products within a single framework.…”

“…Implementing impact-related services at a NMHS for the first time usually requires introducing new concepts, methods and data sources into the operational setting (Röösli et al, 2021). Using a common approach like a HEV-model does not avoid this effort, it only provides a reusable framework for new concepts and its elements, especially if provided open-source and free to use.…”

“…In comparison to traditional representations of risk modeling where hazard, exposure and vulnerability are discrete building blocks, e.g., using the famous IPCC risk propeller (O'Neill et al, 2022), we here propose a continuous representation of risk modeling in a smooth risk plane (Figure 1). The mechanics of this modeling approach allows for a gradual increasing interaction of these three building blocks, starting with hazard only information up to a full risk assessment (Röösli et al, 2021). We therefore refer to the full risk triangle as shown in Figure 1 as the "larger picture" into which the traditional hazard modeling activity of a NMHS is naturally embedded.…”

Consequence forecasting: A rational framework for predicting the consequences of approaching storms

“…These hazard intensities are then fed into vulnerability models (also known as fragility curves) to produce estimates of damage, and subsequently into an economic loss model to produce economic impacts for each storm. Integrating storm losses for all storms in the hazard model produces the total potential losses over the lifetime of the assets and this can be used to set insurance premiums and reinsurance thresholds, or alternatively the impacts of individual event can be considered (Röösli et al, 2021;Welker et al, 2021). For further details of Catastrophe Risk Modelling, the reader is directed to Grossi and Kunreuther, 2005;Clark, 2002;Golnaraghi, et al, 2018, and the open source Catastrophe models OASIS or CLIMADA (Aznar-Siguan and Bresch, 2019).…”

Climate change impacts on snow avalanche risk in alpine regions

“…For all the model outputs, CLIMADA provides a module to perform uncertainty and sensitivity analyses (Kropf et al, 2022) using global (quasi-)Monte Carlo sampling. CLIMADA is currently used in various contexts such as: Tropical cyclones (Eberenz et al, 2021;Meiler et al, 2022), flood (Sauer et al, 2021), European winter storms (Röösli et al, 2021), heat (Stalhandske et al, 2022), and wildfires globally (Lüthi et al, 2021). In this work, it is applied to avalanche hazard in the context of climate change.…”