 County Wildfire Risk Ratings in Northern California: FAIR Plan Insurance Policies and Simulation Models vs. Red Flag Warnings and Diablo WindsJames Schmidt MPRA Paper from University Library of Munich, Germany Abstract: Because of increasing wildfire risk and associated losses, fire insurance has become more difficult to obtain in Northern California. The only insurance alternative for homeowners who are unable to find conventional home insurance is limited and costly coverage available through the California FAIR Plan. Counties located in the Central Sierras have been particularly hard hit with insurance cancellations. FAIR Plan policies in several of those counties exceeded 20% of all policies in 2021. Results from three recent assessments, based on wildfire simulation models, agree that counties in the Central Sierras are among the most at-risk for wildfire-caused structure loss. Most housing losses in the 2013-2022 decade, however, were the result of wind-driven fires in the Northern Sierras and in the Northern San Francisco Bay Area. 85% of all losses occurred in fires where a Red Flag Warning (RFW) for high winds had been issued by the National Weather Service. The Northern Sierras and the North Bay Area averaged 60% more RFW days during the fall fire season compared to the Central Sierras. Strong downslope “Diablo” winds from the Great Basin deserts were involved in seven of the most destructive fires, accounting for 65% of the total housing losses. Based on records from 109 weather stations throughout the Sierras and the Bay Area, these wind events occur primarily in the Northern Sierras and the Bay Area. Climate models have predicted that Diablo-type winds should decrease as the interior deserts warm, but weather stations in both the Bay Area and the Sierras recorded a large increase in the number of strong DiabIo wind days in the 2017 through 2021 years. All seven of the Diablo wind fires occurred during that time span. Fires driven by strong Diablo winds fit into a category of disasters referred to as “black swan” events – rare occurrences that have very large effects. Because these fires occur so infrequently, they have minimal effect on risk estimates produced by averaging together the outcomes of thousands of simulations. Exceedance probability analysis (Ager et al., 2021) can help to identify the communities most at risk from such high-loss, low-probability events. Combining exceedance probability analysis with simulation models that capture the frequency and location of extreme wind events should cause county risk rankings to more closely match actual losses. As a result, the relative risk ratings (and FAIR Plan policies) assigned to the Central Sierras should be reduced. Keywords: Wildfire; Fire Insurance; FAIR Plan; Diablo Wind; Red Flag Warnings; Exceedance Probability; Black Swan; Simulation; FSIM; ELMFIRE; Exposure; Ignition Density; Risk; California; Downslope Winds; Climate models; RAWS; weather stations; Wildland Urban Interface; WUI; Camp Fire; Tubbs Fire; Central Sierras; San Francisco Bay Area; Northern Sierras (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:120195 Access Statistics for this paper More papers in MPRA Paper from University Library of Munich, Germany Ludwigstraße 33, D-80539 Munich, Germany. Contact information at EDIRC. |
Is your work missing from RePEc? Here is how to contribute.
Questions or problems? Check the EconPapers FAQ or send mail to .
EconPapers is hosted by the
School of Business at Örebro University.