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Summer has just started, but weather has already been warm over Europe. Many countries have experienced very high temperatures over the first weeks of June, and there is a chance the 2014 summer will be warmer than normal. A warm atmosphere can bring very high convection potential and potentially lead to a busy severe convective storm season. While seasonal forecasts are uncertain, severe hail events already experienced in June already point to a potential increase in hail risk this year.

The first noticeable hailstorm of the season hit Germany, France, and Belgium between June 7 and 9. Over that period, southern air masses were very warm and clashed with much cooler air from the north. This frontal system brought heavy local wind, rain, and hail, especially over the north of France, Belgium, and northwest region Germany, where large cities like Essen, Düsseldorf, or Köln experienced property damages and six casualties.

RMS scientists Dr. Navin Peiris and Panagiotis Rentzos led a reconnaissance survey in the region a few days after the event and noted that even if there was some evidence of direct hail damage to roofing, most of the substantial damages and transport disruption around Düsseldorf came from tree falls due to very strong wind gusts.

July 12, 2014 will be the 30th anniversary of the most expensive hailstorm in the history of Germany, which generated losses around US$2 billion 1984—half of which was insured. The hailstorm developed amid a streak of late afternoon thunderstorms after a day of intense solar heating. A mass of moist sea air flowed into southern Germany overnight and the combination of moisture and rising air triggered a rapidly intensifying thunderstorm system over the Swiss Mittelland that propagated eastward. Hail fell within a 250-kilometer (150-mile) long and 5–15 kilometer (3–9 mile) wide swath from Lake Constance to eastern Bavaria near the Austrian border. At around 8 p.m. local time, the hailstorm passed over Munich, damaging approximately 70,000 houses, 200,000 cars, 150 aircraft, and most agricultural crops within the storm’s path. More than 400 people were injured. Over half of the insured losses were attributed to damaged cars.

July also marks the first anniversary of the 2013 German hailstorm, which caused insured losses of US$3.4 billion, the second highest from a single natural catastrophe in 2013. Like the June 2014 events, the storm hit after a prolonged period of above-average temperatures in central Europe. The first hail event hit northern Germany on July 27, and the second dropped hailstones with a diameter of up to 8 cm (3.1 in) over south Germany the next day.

Interestingly, all these major events occurred in regions with very high potential of hail damage, which can be described in catastrophe models such as the RMS HailCalc model in terms of kinetic energy to help better manage hail risk. In June, RMS presented the first results of a reconstruction of this hailstorm on at the 1st European Hail Workshop. The paper illustrates how a fast estimation of insured hail losses could be obtained following an event in the future. Developing methods of estimating insured loss totals and return periods immediately after an event are an ongoing area of research in the insurance industry, as illustrated in the RMS paper and others at the workshop.

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Are (Re)insurers Really Able To Plan For That Rainy Day?

Many (re)insurers may be taken aback by the level of claims arising from floods in the French Riviera on October 3, 2015. The reason? A large proportion of the affected homes and businesses they insure in the area are nowhere near a river or floodplain, so many models failed to identify the possibility of their inundation by rainfall and flash floods. Effective flood modeling must begin with precipitation (rain/snowfall), since river-gauge-based modeling of inland flood risk lacks the ability to cope with extreme peaks of precipitation intensity. Further, a credible flood model must incorporate risk factors as well as the hazard: the nature of the ground, such as its saturation level due to antecedent conditions, and the extent of flood defenses. Failing to provide such critical factor can cause risk to be dramatically miscalculated. A not so sunny Côte d’Azur This was clearly apparent to the RMS event reconnaissance team who visited the affected areas of southern France immediately after the floods. “High-water marks for fluvial flooding from the rivers Brague and Riou de l’Argentiere were at levels over two meters, but flash floodwaters reached heights in excess of one meter in areas well away from the rivers and their floodplains,” reported the team. This caused significant damage to many more ground-floor properties than would have been expected, including structural damage to foundations and scouring caused by fast-floating debris. Damage to vehicles parked in underground carparks was extensive, as many filled with rainwater. Vehicles struck by more than 0.5 meters of water were written off, all as a result of an event that was not modeled by many insurers. The Nice floods show clearly how European flood modeling must be taken to a new level. It is essential that modelers capture the entire temporal precipitation process that leads to floods. Antecedent conditions—primarily the capacity of the soil to absorb water must be considered, since a little additional rainfall may trigger saturation, causing “saturation excess overland flow” (or runoff). This in turn can lead to losses such as those assessed by our event reconnaissance team in Nice. Our modeling team believes that to achieve this new level of understanding, models must be based on continuous hydrological simulations, with a fine time-step discretization; the models must simulate the intensity of rainfall over time and place, at a high level of granularity. We’ve been able to see that models that are not based on continuous precipitation modeling could miss up to 50% of losses that would occur off flood plains, leading to serious underestimation of technical pricing for primary and reinsurance contracts. What’s in a model? When building a flood model, starting from precipitation is fundamental to the reproduction, and therefore the modeling, of realistic spatial correlation patterns between river basins, cities, and other areas of concentrated risks, which are driven by positive relationships between precipitation fields. Such modeling of rainfall may also identify the potential for damage from fluvial events. But credible defenses must also be included in the model. The small, poorly defended river Brague burst its banks due to rainfall, demolishing small structures in the town of Biot. Only a rainfall-based model that considers established defenses can capture this type of damage. Simulated precipitation forms the foundation of RMS inland flood models, which enables representation of both fluvial and pluvial flood risk. Since flood losses are often driven by events outside major river flood plains, such an approach, coupled with an advanced defense model, is the only way to garner a satisfactory view of risk. Visits by our event reconnaissance teams further allow RMS to integrate the latest flood data into models, for example as point validation for hazard and vulnerability. Sluggish growth in European insurance markets presents a challenge for many (re)insurers. Broad underwriting of flood risk presents an opportunity, but demands appropriate modeling solutions. RMS flood products provide just that, by ensuring that the potential for significant loss is well understood, and managed appropriately.…

Laurent Marescot
Laurent Marescot
Senior Director, Model Product Strategy, RMS

Based in Zurich, Laurent initially joined RMS in 2008 as part of the Zurich account management team, servicing the European (re)insurance and ILS market. He then moved to the model product management group, leading the technical product management team for European climatic perils, such as windstorm, severe convective storm and flood. Since 2014, he has joined the model product strategy group for Europe model product line.

Prior to RMS, Laurent worked 3 years at the Swiss Federal Institute of Technology Zurich (ETHZ) as a Research Associate and Lecturer, managing multidisciplinary natural hazard research projects. Laurent still lectures regularly on geophysics and catastrophe modeling at universities, and gives seminars and invited talks in international meetings. He is a Lecturer and Scientific Collaborator at the University of Fribourg (Switzerland). Laurent co-authored numerous industry publications, reviewed scientific articles and proceeding papers. He holds an MSc in Geology from the University of Lausanne and a PhD in Geophysics from the University of Lausanne and the University of Nantes.

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