On the “long tail” of flood disaster losses in California

By Kathleen Schaefer and Deirdre Des Jardins

Hurricane Ian has shown the vulnerability of the rapidly growing cities in the Southeast to storm-driven flooding. As reported in the New York Times, in the counties whose residents were told to evacuate, just 18.5 percent of homes have insurance through the National Flood Insurance Program (NFIP) (Flavelle 2022). Outside of those counties, it’s even worse. E&E News reported that inland Orange County, with 1.5 million residents, has fewer than 12,000 households with federal flood insurance (Frank and Cusik 2022).

As hurricane losses along the Gulf and Atlantic coasts increase, should California explore alternatives to the National Flood Insurance Program? California has had fewer NFIP claims than most states over the past 20-30 years. This suggests that California has managed flood risk and floodplain development better than other states (Miller and Pinter 2022). But in thinking about disasters, disaster payments, and insurance, it is essential to consider the probability distribution of extreme weather events and disaster losses due to these events.

What often gets lost in discussions is that losses are not normally distributed. The probability distributions tend to have a long tail and thus are generally best described by Weibull or negative binomial probability distributions.

Graph of Weibull Distribution
Weibull Distribution                  Wikipedia

In California, our most significant precipitation comes in the form of atmospheric rivers (AR). AR precipitation intensities and totals from AR storms depend on the amount of water transported by the storm. This is quantified as Integrated Vapor Transport (IVT), defined as the amount of water transported across a line perpendicular to the atmospheric river flow. The maximum precipitation rate of the storm will depend on the maximum transport of water by the storm, as measured by IVT. Dettinger et al. (2018) thus suggested that the return periods of maximum IVT rates offer a valuable means for characterizing AR storms and their risks. The chart below (from Dettinger et al., 2018) shows how the historical return periods for IVT rates vary along the west coast. The highest intensity storms have return periods of 5-25 years or more.

Ralph et al. (2019) proposed five categories for Atmospheric Rivers, ranging from Cat 1 (weak) to Cat 5 (exceptional). The scale is based on maximum IVT and storm duration (See below, from USGS).

Chart showing atmospheric river rating scale

Corringham et al. (2019) found that flood losses in the Pacific Northwest and California are almost entirely due to atmospheric rivers and that losses increase exponentially with atmospheric river (AR) intensity. (See chart below.)

Combining the work of Dettinger et al. (2018) with the analysis from Corringham et al. (2019), we can start to assign a probability to the AR flood losses. One would expect Category 5 ARs in California every 5-25 years, with a 25%-75% range of flood losses of $24 million to $1.1 billion. In recent history, the maximum flood loss for an AR was $3.7 billion in 1995. (Corringham et al., 2019).

The long tails of flood disaster losses are expected to increase with climate change. Swain et al. (2018) found “large, statistically robust increases in the simulated frequency of extremely heavy precipitation events on multiple timescales” with climate change. Brunner et al. (2021) also found a “precipitation extremeness threshold.” Above this threshold, flood magnitudes with climate change are expected to increase, but below it, flood magnitude is modulated by land surface processes. These processes include drying of soil due to increased temperatures. The authors found that patterns of less extreme floods are likely not to be representative of increases in higher-magnitude events.

In conclusion, while California’s flood management has successfully reduced flood losses in recent decades, it is essential to consider the “long tail” of disaster events and disaster losses. Extremely heavy precipitation events are also expected to increase in frequency with climate change.

Kathleen Shaefer a nationally recognized expert in flood risk management, and is affiliated with the Center for Catastrophic Risk Management and the UC Davis Watershed Science Center. Her research looks at innovative ways to address flood risk and flood insurance needs.

Further Reading

Brunner, M.I., Swain, D.L., Wood, R.R. Willkofer, F., Done, J., Gilleland, E., Ludwig, R. 2021. An extremeness threshold determines the regional response of floods to changes in rainfall extremes. Commun Earth Environ 2, 173.

Corringham, T. W., Ralph, F. M., Gershunov, A., Cayan, D. R., and Talbot, C. A. 2019. Atmospheric rivers drive flood damages in the western United States. Science Advances, 5(12):eaax4631.

Dettinger, M. D., Ralph, F. M., and Rutz, J. J. 2018. Empirical return periods of the most intense vapor transports during historical atmospheric river landfalls on the US West Coast. Journal of Hydrometeorology, 19(8):1363–1377

Flavelle, C. 2022. Hurricane Ian’s Toll Is Severe. Lack of Insurance Will Make It Worse. New York Times. September 29, 2022.

Frank, T., Cusik, D. 2022. Ian ravaged one of the fastest-growing areas in the U.S. E&E News, September 29, 2022.

Henson, B. 2019. Cat 1 to Cat 5: A Scale for Atmospheric Rivers, Weather Underground, February 4, 2019.

Miller, R., Pinter, N. 2022. Federal Disaster Assistance to California. California WaterBlog. September 25, 2022.

Ralph, F.M., Rutz, J., Cordeira, J. Dettinger, M., Anderson, M. Reynolds, M., Schick, L., Smallcomb, C. 2019. A Scale to Characterize the Strength and Impacts of Atmospheric Rivers. Bulletin of the American Meteorological Society. 100.10.1175/BAMS-D-18-0023.1.

Swain, D. L., Langenbrunner, B., Neelin, J. D., and Hall, A. (2018). Increasing precipitation volatility in twenty-first-century. California Nature Climate Change, 8(5):427.

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