Rising Losses From Severe Convection Storms Mostly Explained by Exposure Growth

Rising Losses From Severe Convection Storms Mostly Explained by Exposure Growth
Property Risk Management

06 of 07

This insight is part 06 of 07 in this Collection.

September 11, 2023 5 mins

Rising Losses From Severe Convection Storms Mostly Explained by Exposure Growth

Rising Losses From Severe Convection Storms Mostly Explained by Exposure Growth Hero Banner

Climate change or exposure growth? By understanding the drivers of increased severe convective storm loss volatility, reinsurers can better prepare for January 1 renewals.

Key Takeaways
  1. From 1990 to 2022, severe convective storm losses increased at an annual rate of 8.9 percent.
  2. Over 80 percent of the loss trend can be explained by exposure growth.
  3. There is little evidence that climate change is impacting key atmospheric ingredients that influence SCS.

Seventy percent of global insured losses were driven by severe convective storms (SCS) in recent years. In the U.S., SCS caused $38 billion of insured loss in the first half of 2023, breaking the record of $33 billion set in the first half of 2011. From 1990 to 2022, SCS insured losses increased at an annual rate of 8.9 percent. As we enter January 1 (re)insurance renewals, it’s pertinent to understand what is driving this trend of SCS loss volatility. Is it climate change, where a warming planet contributes to a shift in weather patterns, resulting in a new normal of elevated storm activity? Or can the increased loss trend be explained by underlying exposure growth and population distribution changes? 

We answer this question by first looking at the weather “ingredients” that are most favorable for severe thunderstorm development. The first is Convective Available Potential Energy, or CAPE, which is a measure of atmospheric instability and considered as a proxy for fuel available to a developing thunderstorm. The second variable is wind shear, a measure of wind speed and directional differences with height above the Earth’s surface. The product of these two measures is known as the Severe Index (SEV) and is commonly used to diagnose severe weather potential.

Severe weather ingredients from 1990-2019

Severe weather ingredients from 1990-2019

The chart above shows annual averages for key SCS ingredients from 1990-2019. National Oceanic and Atmospheric Administration’s ERA5 reanalysis data, which is reported every six hours, was averaged through each year to determine the annual number. Other than some long term, decadal variation in CAPE observations in the Central U.S., there are no discernible trends in atmospheric ingredients that are most suitable for severe weather formation. 

With the absence of physical drivers increasing severe convective storms, we can then assume that much of the SCS loss trend is due to underlying exposure changes. To prove this, we identified four main drivers of exposure change and quantified how much of the overall SCS loss trend they explained. 

  1. Real gross domestic product (GDP) accounts for how much “stuff” there is in the economy and grew at an annual rate of 2.3 percent. 
  2. Fixed reproducible tangible wealth (FRTW) accounts for how much goods and services are worth and grew at an annual rate of 2.1 percent. 
  3. Property cost inflation, measured by the producer price index for all construction, provides a good estimate of how construction costs change over time. This grew the fastest at a 2.8 percent rate. 
  4. Population distribution, measured by the housing distribution index, is based on changes over time in housing units in high hazard states like Texas and other Sun Belt states. It grew t a rate of 1.1 percent.
Trends 1990 to 2022

Nominal annual SCS losses and loss and exposure trends from 1990 to 2022

Source: Aon Analytics

Note: Nominal losses were subject to a $100 million (in 2006 dollars) threshold before being aggregated by year.

Overall, exposures have grown at a combined rate of 8.6 percent per year. Compared to the loss trend of 8.9 percent, and allowing for analysis uncertainty, this means that over 80 percent of SCS loss growth can be explained by exposure changes. The remaining 20 percent is unexplained by these metrics but could be due to small climate changes that are not discernible in the Severe Index, other exposure factors, or random chance. 

While climate change has been shown to be a driving force behind evolving trends for other perils such as hurricane and heatwave, there is little evidence that climate change is impacting key variables that influence SCS. (Re)insurers instead must deal with growing exposures in high hazard areas, which can be managed through traditional risk management techniques, such as accumulation management, effective claims handling and appropriate deductible, limit and premium levels. Going forward, the industry’s emphasis for the SCS peril should be less on a changing climate and more on traditional risk management.

 

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