Terrafuse AI, a climate and weather risk forecasting tool developer, launched Wildfire AI today. Wildfire AI is the first to leverage daily climate intelligence and predictive modeling for the public, delivering greater accuracy to assess and mitigate the rising property risk from wildfires in California.
Nearly 4.5 million U.S. homes were identified at high or extreme risk of wildfire, with more than 2 million in California alone. Chaucer, a speciality (re) insurance group recently released data showing the average number of major U.S. wildfires (over 40,000 acres) per year has risen 30% over the last 15 years, contributing to wildfire-associated costs growing from $1 billion per year in the 1990s, to $17.1 billion in 2020.
“I experienced firsthand the devastating impacts of wildfires when, a few years ago, my entire neighborhood in California was evacuated and much of it burned down,” said Hunter Connell, co-founder and CEO of Terrafuse AI. “We also know that without more accurate insights about property risk, homeowners, businesses, and governments are facing impossible odds to plan for, mitigate, and escape these catastrophes in time.”
Terrafuse AI taps into the vast wealth of earth observation data to produce climate risk models that are 1,000 times faster than traditional climate models, by deploying machine learning on Microsoft Azure.
“Innovation in climate risk assessment is needed now more than ever to keep up with the volatile nature of climate change,” said Bonnie Lei, Head of Global Strategic Partnerships for Microsoft AI for Earth. “Terrafuse AI is able to bring incredible speed and accuracy to climate risk analytics and chose to use Azure to accelerate the scaling of their solution.”
Terrafuse AI’s approach leverages machine learning models trained by more than 50 environmental conditions, including hyperlocal wind speed, vegetation characteristics, humidity and observed wildfire events. These complex models produce an accurate measure, expressed as a risk score or annual exceedance probability, that quantifies the likelihood of a catastrophic wildfire event happening down to a hyperlocal scale of 100 feet. Terrafuse AI’s models have been validated against $1 billion of proprietary insurance claims data. In addition to venture backing, Terrafuse AI partners include the U.S. Air Force, Microsoft AI for Earth, National Science Foundation, and Lawrence Berkeley National Laboratory.
“Unfortunately, 2021 has brought us yet another devastating fire season in California with elevated fire risk that results in fires exploding at numerous locations across the state at nearly the same time,” said Dr. Daniel Feldman, Atmospheric Scientist and Advisor to Terrafuse AI. “Fire risk extends far beyond the areas burned and is highly-localized and ever changing.”
“In the Caldor Fire, the Wildfire AI model’s prediction rapidly changed from low to a very high risk score in the span of just a few days during the rapid growth of that fire,” continued Feldman. “The spatial patterns of the risk score reflected the spatial patterns of the increased likelihood of fire due to the surface winds, fuels, and humidity conditions.”
The estimated value of the global climate analytics market is $40 billion. Wildfire AI is free to the public to facilitate greater access to scientific machine learning that accurately predicts hyperlocal wildfire risk daily. Enterprise solutions, including a year-ahead climate risk forecast, are also available.
Terrafuse AI develops climate and weather risk forecasting products powered by climate science and machine learning. The company’s tools provide hyperlocal climate risk intelligence to empower better decision-making and climate risk mitigation for individuals and companies.
SOURCE Terrafuse AI