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Larger, Hotter, Faster: The Problem with Wildfire Analytics, and How To Solve It


How risk managers, brokers, and insurers can leverage statistically validated, scientifically informed, and high-resolution wildfire analytics to confidently assess wildfire risk exposure.


insurance copywriter claire vorster

The Yarnell Hill fire in Arizona is famous for all the wrong reasons. The blaze was ignited by lightning amid a drought and extreme summer temperatures. The fire turned rapidly and overran a team of 19 firefighters as they were trying to make their way to safety. In its wake, it also burned 8,400 acres and destroyed many properties. Analysis of historical meteorological data shows that wind on the north side of the fire, at the Emergency Operations Center, was moving from the north-northeast at 13 miles per hour (mph), whereas in Stanton, southeast of the fire, the wind was gusting to 47 mph.


“It was a very different situation on the south side versus the north side of the fire. Fine-scale convective storm cells can create that type of variability in the wind. That’s something the firefighters weren’t anticipating.” —Curtis N. James, Embry-Riddle meteorologist

The Problem with Wildfire Analytics - The Enigmatic Peril The Yarnell Fire tragedy demonstrates why wildfires are an enigmatic peril. Wildfires are difficult to predict and control, and they are getting worse for a number of reasons:

- Rising temperatures and changing precipitation patterns are leading to drier and warmer conditions in many regions. Droughts, heatwaves, and high winds can also make it easier for fires to start and spread.


- Another factor is land use change. Human activities such as logging, urban development, and agriculture can change the composition and density of vegetation, creating conditions that are more conducive to wildfires. Additionally, many forests are overgrown and in need of thinning, but budget and management issues make it difficult for forest managers to reduce the fuel load. - Finally, human-caused wildfires, such as those caused by campfires, cigarettes, fireworks, and arson also play a significant role in the increase of wildfires.

When you combine factors such as lightning strikes, human activity, and weather conditions, wildfires can spread quickly and unpredictably. Additionally, the damage caused by wildfires can be extensive, including loss of property, injury, and loss of life.


The Rising Cost of Wildfires


Americans are "flocking to fire." This is the conclusion of a study in the journal Frontiers in Human Dynamics, published in December 2022. Using census data, the researchers discovered that individuals are rapidly relocating to regions that are more vulnerable to devastating wildfires or extreme heat. Although some wealthy Americans are drawn to the beauty of forested places, others are also being compelled by economic pressures. Due to skyrocketing housing costs and the cost of living, people are being pushed toward more rural areas where properties are less expensive.


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Illustration- Clark ET AL, Frontiers in Human Dynamics

The cost of more people residing in wildfire-prone areas is enormous; the 2018 Camp Fire, which burned Paradise, California, is estimated to have cost $16.5 billion in damage. Here are examples, from Wildfire Today, of recent wildfires that have caused widespread evacuations, fatalities, and the destruction of buildings:


2016; 88,000 people evacuated from Fort McMurray, Canada; 2 fatalities; 3,600 structures impacted.

2017: 90,000 people were evacuated from North Bay, California; 44 people died; 8,900 structures impacted.

2018: 27,000+ evacuated from Paradise, California; 85 fatalities; 19,000 structures impacted. 2021: The Marshal Fire destroyed 1,056 structures; the most destructive fire in Colorado history in terms of buildings destroyed.

“As temperatures increase — as things get drier and hotter and prices for housing get more unaffordable — it’s definitely going to push people into these rural areas,” says Kaitlyn Trudeau, a data analyst at the nonprofit Climate Central. “Some people don’t have a choice.”

Pricing the Risk


Deepak Badoni, founded EigenRisk® in 2014 so that those responsible for making risk management decisions could get real actionable wildfire analytics in a timely and efficient manner. When it comes to wildfires, he explains what is at stake:


“In the aftermath of another record-breaking year for U.S. wildfire events and damage, there’s a tremendous need for precise information on wildfire risk within well-defined geographic areas. Historically, the industry has struggled to accurately assess risk in wildfire-prone areas due to a lack of credible models backed by the latest science, and at sufficient resolution.”

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Risk professionals need to be able to accurately assess wildfire hazard potential - using a wildfire hazard model to make confident decisions. This is why EigenRisk® entered into a strategic partnership with Teren, Inc.TM, a leading climate resilience data and analytics company. Teren's cutting-edge U.S. wildfire potential model will be available through the EigenPrism®, catastrophe risk management platform. This collaboration will enhance the platform's capabilities and provide valuable insights to clients on wildfire risk. The partnership will continue to evolve, providing ongoing benefits to clients.


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Teren delivers climate resilience data to help organizations build and operate resilient businesses and sustainable communities. By harnessing remotely sensed data, powerful processing, and modern data science, Teren delivers hyper-localized, actionable insights to manage climate risk and build resilience over time. Its wildfire potential model explains 83 percent of variability in historical wildfire events occurring between 2000 and 2021.

“Fear of climate change threatens the viability of the insurance business in an increasing number of markets,” said Katherine Kraft, Director of Product at Teren. “We’ve heard from insurers that the Teren wildfire potential model enables them to make safer, more confident bets on insuring the most resilient properties within wildfire-exposed regions, rather than exiting those regions entirely and leaving profits on the table.”

The Solution for New Extremes Data does not lie, and as the frequency and severity of wildfires increases, insurers have suffered significant losses, leading to a reduction in the availability of coverage and an increase in premiums.


The good news comes from Derek Thrumble of Alesco, who says the company has: “Implemented the Teren wildfire hazard intensity data set as part of its suite of hazard models within the EigenPrism software platform.”

Derek agrees that the market for risks that are potentially exposed to wildfire continues to be challenging, however he explains the advantage that better data provides:

“We have applied this data across a number of client asset schedules already this year covering cargo (stock); financial institutions (mortgage loans) and real estate business. The risk rankings and risk mapping generated has enabled us to provide underwriters with a much more detailed assessment of the level at wildfire risk at all the key locations. This insight has allowed us to secure valuable additional capacity and improve the renewal terms in terms of deductible levels and premium rating.”


Accurate Wildfire Hazard Modeling Starts Now Teren utilizes LiDAR technology and modern data science techniques to accurately assess ground-level fuels and mitigate wildfire risk. With decades of reclamation experience, they can also evaluate post-burn conditions to assess damage and prevent further loss.

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By combining the power of ecosystem data science and high-performance geospatial computing, this wildfire hazard model can more accurately predict where and when fires are likely to occur, and how they might spread, providing valuable insights for fire management, and reducing risk exposure for communities and natural resources.


Ecosystem data science can be used to analyze the relationships between different types of vegetation, topography, and weather conditions, and how they contribute to wildfire risk. This can include data on vegetation density, canopy cover, fuel loads, and species composition. By understanding how different ecosystems are affected by wildfires, the model can make more accurate predictions about where and when fires are likely to occur.


High-performance geospatial computing can be used to process and analyze large amounts of data on a regional or even global scale. This allows the model to take into account factors such as land use, population density, and infrastructure, and how they contribute to wildfire risk. Additionally, it can be used to analyze satellite data and remotely sensed imagery, which can provide information on vegetation cover, land surface temperature, and other factors that can influence wildfire behavior.


The Power of Historical Data to Predict Future Trends


By incorporating data on current and forecasted weather conditions, as well as information on land use and vegetation, the Teren model can generate predictions about where and when wildfires are likely to occur in the future. The last word goes to Spanish-American philosopher, George Santayana who warned that those who cannot remember the past are condemned to repeat it. There is no doubt that accurate wildfire modeling will improve our ability to make better decisions about risk and pricing, and help protect against property damage, injury, and loss of life.


EigenRisk, Inc., an independent insurance technology firm, helps (re)insurers, brokers and risk managers across the globe manage catastrophe risk, and drive higher growth, customer engagement and operational efficiency. The firm’s cloud-based platform provides one-stop access to powerful data management, geo-visualization, analytics, reporting, modeling, alerts and APIs. These capabilities are integrated with hazard data, event projections and simulations curated from more than 20 leading public and private sources to provide a more dynamic and complete perspective of risk.


Denver-based Teren is a leading climate resilience data and analytics company. By harnessing the plethora of remotely sensed data from orbit and airborne platforms, Teren delivers hyper-localized, asset-level insights for managing climate risk and building resilience over time. Teren uniquely solves complex problems by applying modern data science techniques, geo-intelligence, and high-performance computing to deliver timely, actionable results. Teren works with asset owners, developers, engineering firms, and insurers to pinpoint risk, reduce exposure and improve climate resilience.

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