Loss potential from severe thunderstorms in Europe is increasing – New method for analysing loss data highlights the benefits of prevention
The loss potential of severe thunderstorms is increasing in many parts of Europe. This is mainly due to the growing intensity of thunderstorms and the increasing vulnerability of expensive building façades to hail damage. Munich Re analyses this subject in the 2016 issue of its publication Topics Geo, which takes a detailed look at the previous year’s natural catastrophes.
Over the last few years, severe thunderstorms in Europe have caused a number of losses of more than a billion euros, mainly as a result of hail, strong gusts and flash floods. The costliest thunderstorm event since 1980 occurred in Germany in July 2013, when powerful hailstorms in particular caused overall losses of US$ 5bn (€4.6bn) in today’s values. About US$ 3.8bn (€3.5bn) of this was insured.
“Expensive construction materials and complex building façades are a major contributing factor to the increasing loss potential of hailstorms. Recent studies have also shown that the intensity of thunderstorms and hailstorms has increased in many regions”, explains Peter Höppe, Head of Munich Re’s Geo Risks Research department. “Rising moisture content in the lower atmosphere is a key driver of stronger thunderstorms – a physical consequence of the long-term warming of the world’s oceans. With values also continuing to rise, prevention is becoming even more important to keep loss levels low.”
The insurance industry fully supports efforts to improve the strength and resilience of buildings. For example, the Swiss Cantonal Fire Insurance Association runs the “Elementary Safety Register Hailstorm”, which establishes the hail resistance of various materials used in the exteriors and roofs of buildings.
In 2015, natural catastrophe losses again remained below the long-term average. Overall losses totalled US$ 100bn, compared with an average of US$ 180bn for the ten previous years. Insured losses amounted to US$ 30bn (ten-year average US$ 56bn). The year’s most devastating natural catastrophe was the Nepal earthquake in April, which claimed the lives of some 9,000 people. The overall losses from the quake were US$ 4.8bn.
New method for analysing historical loss data presented
Besides looking at longer-term trends and analysing the year’s natural catastrophes, the latest issue of Topics Geo also presents a new method for more detailed evaluation of historical loss data. Munich Re developed the method to take into consideration the economic development of a region affected by a loss event in the period since the natural catastrophe occurred. In the case of regional analyses, this enables us to be more precise about the loss-mitigating effect of prevention measures and about changes on the hazard side such as natural climate cycles or climate change.
Unlike techniques based solely on inflation-adjusted figures, this new method does not reveal a rising trend in overall global losses since 1980. It must be noted that the data extrapolated to today’s values are distorted by the economic development of China in recent decades. For example, flood losses in China from the 1990s would now have to be multiplied by a factor of 20 in some cases to arrive at today’s values. At the same time, prevention measures are not included in this calculation. Recent weather events in China have produced reduced losses thanks to flood-control measures taken there. These two effects tend to cancel each other out statistically.
If one examines the loss statistics of individual regions or hazard types using the new method, the following statements can be made. For example: There has been a clear upward trend in losses adjusted to today’s values from severe thunderstorms in the USA since 1980, which tallies with meteorological observations. By contrast, there has been no upward development for flood losses in Europe following major events in the recent past thanks to flood-protection measures implemented there (in Germany above all since 2002).
Munich Re will include figures based on the new method in its natural catastrophe statistics in future.
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