From Atmospheric Dynamics to Insurance Losses: An Interdisciplinary Workshop on European Storms

Pinto, Joaquim G.; Pantillon, Florian; Ludwig, Patrick; Déroche, Madeleine-Sophie; Leoncini, Giovanni; Raible, Christoph C.; Shaffrey, Len; Stephenson, David B.

doi:10.1175/bams-d-19-0026.1

Cited by 10 publications

(8 citation statements)

References 13 publications

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“…This was achieved by using a loss model that required training with records of local insurance data. Beyond these published studies, several companies in the insurance sector (e.g., Willis Towers Watson, Aon, Guy Carpenter, AIR, RMS) provide loss estimates of impending or current windstorm events as a service for their clients (see Pinto et al, 2019, for an overview). These models link freely available forecasts from the weather services to in-house company loss models.…”

Section: Extratropical Windstormsmentioning

confidence: 99%

“…These impact estimates and their uncertainty provide a clear added value to the clients, as they enable them to take measures to minimize potential impacts of an impending storm, for example, to assign staff or to buy short‐term additional windstorm damage coverage (Welker et al, 2020). Unfortunately, such information is not widely accessible, which calls for enhanced communication between public and private research (Pinto et al, 2019). To the authors' knowledge, there is no published study on the quantitative benefits of windstorm impact forecasts yet.…”

Section: State Of the Art Of Impact Forecastingmentioning

confidence: 99%

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Impact Forecasting to Support Emergency Management of Natural Hazards

Merz

Kuhlicke

Kunz

et al. 2020

Reviews of Geophysics

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161

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Forecasting and early warning systems are important investments to protect lives, properties, and livelihood. While early warning systems are frequently used to predict the magnitude, location, and timing of potentially damaging events, these systems rarely provide impact estimates, such as the expected amount and distribution of physical damage, human consequences, disruption of services, or financial loss. Complementing early warning systems with impact forecasts has a twofold advantage: It would provide decision makers with richer information to take informed decisions about emergency measures and focus the attention of different disciplines on a common target. This would allow capitalizing on synergies between different disciplines and boosting the development of multihazard early warning systems. This review discusses the state of the art in impact forecasting for a wide range of natural hazards. We outline the added value of impact-based warnings compared to hazard forecasting for the emergency phase, indicate challenges and pitfalls, and synthesize the review results across hazard types most relevant for Europe. Plain Language Summary Forecasting and early warning systems are important investments to protect lives, properties and livelihood. While such systems are frequently used to predict the magnitude, location, and timing of potentially damaging events, they rarely provide impact estimates, such as the expected physical damage, human consequences, disruption of services, or financial loss. Extending hazard forecast systems to include impact estimates promises many benefits for the emergency phase, for instance, for organizing evacuations. We review and compare the state of the art of impact forecasting across a wide range of natural hazards and outline opportunities and key challenges for research and development of impact forecasting.

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Section: Extratropical Windstormsmentioning

confidence: 99%

Section: State Of the Art Of Impact Forecastingmentioning

confidence: 99%

Impact Forecasting to Support Emergency Management of Natural Hazards

Merz

Kuhlicke

Kunz

et al. 2020

Reviews of Geophysics

Self Cite

161

View full text Add to dashboard Cite

show abstract

“…For example, the dense observing network of weather stations across Europe, combined with powerful forecasting capabilities of National Meteorological Services and an insurance market motivated by substantial exposure (PERILS, 2019), provides the research incentive to develop a good understanding of the hazards posed by extratropical wind storms (e.g., Dawkins et al, 2016; Pinto et al, 2019; Sainsbury et al, 2020; Welker et al, 2021). There are high‐quality centennial records of extreme wind speeds at many locations across Europe (Feser et al, 2015; Hawkins et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Advances in numerical weather prediction, data science, and open‐source software herald a paradigm shift in catastrophe risk modeling and insurance underwriting

Steptoe

Souch

Slingo

2022

Risk Manage Insurance Review

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Recent advances in numerical weather prediction, combined with the new generation, high‐resolution climate simulations, and open‐source loss modeling frameworks, herald a move beyond the limited statistical representation of catastrophe risk based on past observations. In this new forward‐looking view of risk, an appreciation that our observed record of past natural catastrophes represents a limited sample of possible events, and that the statistics of weather and climate are changing as the planet warms, highlights a key limitation in traditional catastrophe modeling approaches that are built on defining statistical relationships using the observed record. Instead, ensembles of new spatially and dynamically consistent simulations of weather and climate provide physically plausible, but as‐yet‐unseen events at scales appropriate for making effective risk management and risk transfer decisions. This approach is especially useful in locations around the world where observational records are unobtainable or of short historical duration, such as in low‐income countries. We take a forward‐looking approach at the way that future catastrophe modeling and insurance underwriting could occur in response to these technological and scientific advances, using open‐source loss model frameworks.

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“…In the following, we will summarize the efforts for forecasting the impacts of storm events. According to Merz et al (2020), there are storm impact forecasting systems for insurance losses in the private domain, for example, proprietary models run by insurance companies (Pinto et al, 2019). In the public domain, there have been studies that show the skill of impact forecasting for storm impacts on a theoretical level (Pantillon et al, 2017; Pardowitz et al, 2016), but they do not focus on the communication of these forecasted impacts as warnings to specific users or the general public.…”

Section: Introductionmentioning

confidence: 99%

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

Röösli

Appenzeller

Bresch

2021

Meteorological Applications

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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.

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From Atmospheric Dynamics to Insurance Losses: An Interdisciplinary Workshop on European Storms

Cited by 10 publications

References 13 publications

Impact Forecasting to Support Emergency Management of Natural Hazards

Impact Forecasting to Support Emergency Management of Natural Hazards

Advances in numerical weather prediction, data science, and open‐source software herald a paradigm shift in catastrophe risk modeling and insurance underwriting

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

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