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Tornado & Hail

Tornado and hail risk, collectively referred to as severe convective storms, is a growing concern to insurers and public authorities. Recent tornado-related losses across North America have augmented concerns of tornado-hail risk for agricultural, motor and property exposures across the world and highlighted the need for better understanding of tornado-hail risk and its seasonal triggers.

The destructiveness of tornado-hail events despite its localised nature present particular challenges in risk assessment and for that reason is a relatively underdeveloped area of catastrophe risk modelling. WRN research focuses on key areas of tornado-hail risk to improve understanding of climatic effects, physical understanding, and insurance-related impacts.

Regional Hail Risk Models.

The traditional scale of flood risk modelling for insurance companies has been at national and regional scales, corresponding with national insurance markets, data availability and existing platform capabilities. The WRN has developed a range of hail risk models to assess risk for exposed regions in Europe, South Africa and Australia. The WRN has an extensive tornado-hail  programme to meet current industry requirements, confronting new challenges such as climate impacts on frequency and severity the WRN's global hail modelling programme.

Event Response.

The WRN has pioneered the use of radar and satellite imagery and other remote sensing techniques to help communities and insurers prepare for and manage the consequences of tornado-hail events. A significant priority for the WRN is the fusing of highest-detail tornado-hail event radar imagery with portfolios via advanced mapping technologies to provide insurers with situational awareness to manage claims and evaluate damage and losses to portfolios with increased speed and confidence.

Latest on Tornado & Hail

  • A new physically based stochastic event catalog for hail in Europe

    Date: May 20, 2014 | Type: Paper | Attachment: Download File ›
    Journal: Natural Hazards. | Ext. Link: Click Here ›

    Pillar: Natural Hazard & Risk
    Hub: Tornado & Hail

    Authors: H. J. Punge • K. M. Bedka • M. Kunz • A. Werner
    Fields: Hail ! Climatology ! Overshooting top ! Europe

    Summary: Hailstorms represent one of the major sources of damage and insurance loss to residential, commercial, and agricultural assets in several parts of Central Europe. However, there is little knowledge of hail risk across Europe beyond local historical damage reports due to the relative rarity of severe hail events and the lack of uniform detection methods. Here we present a new stochastic catalog of hailstorms for Europe.

    Read More about this publication ›

    The poleward migration of the location of tropical cyclone maximum intensity

    Date: May 15, 2014 | Type: Paper | Journal: Nature | Ext. Link: Click Here ›

    Pillar: Natural Hazard & Risk
    Hub: Tornado & Hail

    Authors: James P. Kossin, Kerry A. Emanuel, & Gabriel A. Vecchi
    Fields: Climate Change, Atmospheric science

    Summary: Attempts to monitor changes in tropical cyclone activity have been hampered by inconsistencies in global data sets, such as measures of frequency, storm duration and intensity. Jim Kossin and colleagues by-pass this long-standing problem by instead focusing on the latitude at which tropical cyclones reached their lifetime maximum intensity, a far more robust measurement. They find that during the past 30 years the position of peak intensity has migrated steadily poleward, at a rate of about 60 km per decade. This shift appears to be associated with changes in vertical wind shear and potential intensity, which the authors suggest may be associated with recent increases in the width of the tropical belt associated with global warming.

    Read More about this publication ›

    Statistical–Dynamical Predictions of Seasonal North Atlantic Hurricane Activity

    Date: Sep 29, 2010 | Type: Article | Attachment: Download File ›
    Journal: Monthly Weather Review |

    Pillar: Natural Hazard & Risk
    Hub: Tornado & Hail

    Authors: GABRIEL A. VECCHI, MING ZHAO, HUI WANG,GABRIELE VILLARINI, ANTHONY ROSATI
    Fields:

    Summary: Skillfully predicting North Atlantic hurricane activity months in advance is of potential societal significance and a useful test of our understanding of the factors controlling hurricane activity. In this paper, a statistical–dynamical hurricane forecasting system, based on a statistical hurricane model, with explicit uncertainty estimates, and built from a suite of high-resolution global atmospheric dynamical model integrations spanning a broad range of climate states is described.

    Read More about this publication ›

About WRN

As economic, social and environmental uncertainties increase, institutions and populations seek greater resilience to support sustainable growth. Science and insurance lay at the heart of understanding, managing and sharing these risks, building more secure futures at local and global scales.

The Willis Research Network (WRN) operates across the full spectrum of risk from natural catastrophe, to legal liability, financial and security issues linked across driving themes: Resilience, Security & Sustainable Growth; Managing Extremes; Insurance & Risk Management and Mastering the Modelled World.

All Members and activities are united by a common aim: improving resilience by integrating first class science into operational and financial decision-making across public and private institutions.

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Fast Facts

  • The WRN was formed in September 2006 to support leading academic research into extreme events, with a specific focus on responding to the challenges faced by businesses, insurers and governments
  • The WRN's membership spans the globe, counting more than 50 world-class universities, scientific research organisations and public policy institutions
  • Collectively, our members have published more than 100 papers in leading scientific journals
  • Nearly all of the WRN's research is freely available to the public and can be downloaded on our website

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