The Data Behind Fire Factor®

Fire Factor uses the First Street Wildfire Model to identify wildfire risks across the United States.

Providing first-of-its-kind wildfire analysis

The First Street National Wildfire Model is a nationwide, fire-behavior-based wildfire model that shows a specific location’s probabilistic risk of wildfire based on vegetation, topography, and likely weather. Built with First Street’s fire science partners the Pyregence Consortium, it leverages decades of peer-reviewed research and forecasts how wildfire risks will change over time due to changes in the environment.

Calculating and mapping wildfire probabilities

The First Street Wildfire Model is a wildfire model based on the physical processes which drive fire behavior across the landscape, which means it considers the real-world conditions that create wildfires and then estimates the likelihood and severity of wildfire at any given location in the contiguous US based on hundreds of millions of simulated possible wildfire events.

    Fuel layers
    Weather conditions
    Historic observations

The process starts by asking: “What would burn if a wildfire were to occur?” The model uses data from the United States Forest Service and the Department of the Interior to identify the type, quantity, age, and condition of the vegetation across the contiguous US that would provide fuel for a potential wildfire. It also includes any measures taken to modify those fuels to reduce risk,  such as prescribed burns, thinning of vegetation, cutting of fire breaks, and other forest management practices – as well as the location and severity of previous wildfires that have changed the fuels present and thus impacted the probability of future fires. What sets the First Street Foundation Wildfire Model apart are both its property-specific resolution and its incorporation of new fuel estimates within the Wildland Urban Interface (WUI),  based on patterns observed in over 500 historic WUI wildfires, enabling estimates of wildfire risk for individual homes in those areas. The model then considers a wide range of possible weather patterns that impact fuels by making them hotter and drier, as well as wind and weather conditions that may help fires grow and spread. The data used to simulate these conditions are from 10 years of National Oceanic and Atmospheric Administration’s (NOAA’s) hourly resolution surface weather observations that include wind, air temperature, relative humidity, and precipitation for the contiguous US, providing a realistic representation of the range of surface weather conditions that drive wildfire behavior. The model simulates the possible ignition locations of wildfires based on historic fire locations and a random element to simulate possible lightning strikes. The fire behavior model predicts how wildfires may (or may not) spread given the fuel and fire weather conditions, and tracks simulated fires that grow to a sufficient size, noting the location, intensity, and duration of these fires.

Determining future wildfire risks

As with any First Street Foundation risk model, incorporating environmental changes that impact future wildfire risk, such as anticipated temperatures and precipitation patterns, is an essential trademark of the First Street Foundation Wildfire Model. The model utilizes 10 years of  NOAA weather observations from  2011-2021 to establish baseline conditions and analyzes multiple environmental possibilities under the WCRP’s CMIP6 climate model ensemble’s SSP245 scenario to forecast temperature and precipitation conditions 30 years into the future that would impact fuel conditions and thus future wildfire risk. This allows the First Street Foundation Wildfire Model to project wildfire risk 30 years into the future by focusing on climate change’s impacts on the state of the fuels that support wildfire growth while holding vegetation and winds static to simplify the projection. This work has been published in articles that have met the rigorous standard of scientific peer review.

Simplifying wildfire risks

The First Street Foundation Wildfire Model has run over 150 million wildfire simulations for the present year and 30 years into the future, creating a view of essentially all possible wildfires that could occur,  resulting in over 50 million significant simulated wildfires for current and future conditions. The end result is a statistically well-characterized dataset of probabilistic wildfire likelihood across the contiguous US, expressed as the burn probability, the anticipated mean and maximum intensity (expressed as flame length), and the likely presence of embers.

However, as with any persistent probabilistic risk, this risk carries over year after year and accumulates over time. To express this, the First Street Foundation Wildfire Model calculates a cumulative wildfire likelihood, which shows the likelihood of wildfire at a given location at least once over 30 years. For example, if a home has a 0.5% chance of wildfire annually, through the accumulation of that risk, that home has a 14% chance of wildfire over 30 years.

0.5%
Annual chance of being in a wildfire
Fire Factor Map LAyer
0
<0.1%
0.5%
1%
2%
5%+
% likelihood of being in wildfire

Scoring system for properties

To simplify the communication of the level of wildfire risk, the First Street Foundation Wildfire Model also calculates a property’s Fire Factor. Simply put, a property’s Fire Factor increases as the 30-year cumulative wildfire likelihood increases. A property with a higher Fire Factor has a higher likelihood of being in a wildfire.

A home’s Fire Factor also takes into account exposure to embers that may be cast from nearby fires, the flames of which are not likely to reach the property itself. While these homes have a very minor probability of being in a wildfire (less than 0.02%), the presence of burning debris from any nearby fires still presents a risk for the homeowner, and is therefore accounted for in the property’s Fire Factor.

Calculating home vulnerability

Unlike flooding, which can cause severe damage without necessarily destroying property, wildfires are uniquely devastating and destructive natural disasters for homeowners. While the financial impact of floods depends on the depth of flooding and the construction of a home, allowing for loss estimates to be predicted for various depths, the financial loss estimate from a wildfire is much simpler to calculate – a home that ignites will, in the large majority of cases, be destroyed.

Given the gravity of this situation for homeowners with wildfire risk, First Street Foundation partnered with the Arup Corporation to analyze data from public real estate and tax assessor records, the USGS, and the USDA, to create a unique, property-specific measurement for home vulnerability. This vulnerability assessment includes First Street’s use of aerial or satellite imagery to calculate the “defensible space” for each building, the surrounding area that is ideally free of any trees and shrubs that can promote the ability of flames to reach the structure. First Street Foundation’s home vulnerability estimate provides homeowners with the probability that their home will ignite if wildfire reaches the property, as well as what building characteristics contribute to that risk.

By comparing these building attributes to historical burn data and building material properties analyzed by the Arup Corporation, First Street Foundation is then able to deduce the damage from wildfire exposure at different flame lengths and ember exposure, giving homeowners an in-depth understanding of wildfire risk for their property.

Ensuring scientific accuracy

The creation of the First Street Foundation Wildfire Model with the Pyregence Consortium and the Arup Corporation required an unprecedented partnership of top climate scientists, modelers, technologists, and analysts. The data the model produces undergoes multiple reviews and must pass comprehensive “checkpoints” before being made publicly available.

  • Model results have been validated against historic wildfire records (number of fires, fire severity, area burned, number of structures lost), independent government estimates of risk such as the community-resolution Wildfire Risk to Communities products,  and government loss and disaster claims.
  • The methodologies used by the First Street Foundation Wildfire Model have been published in scientific peer-reviewed journals and presented at international scientific meetings.

Continuously improving over time

First Street Foundation has made its wildfire model’s full technical methodology available to the public because it supports Open Science, which includes scientific collaboration, open data inputs, and methodological transparency. The First Street Foundation Wildfire Model will continue incorporating feedback from the scientific community and expanding its model over time, including an annual data update to account for any fuel disturbances following each season’s wildfire activity.

Why are wildfire risks increasing?

The largest factor impacting wildfire risk in a  changing environment is higher air temperatures, which dry out fuels more quickly and create conditions that are conducive for wildfires to ignite and spread.

What can be done to stop wildfires?

Although wildfire risk can never be completely eliminated, there are a number of steps homeowners and communities can take to reduce risk.

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