After Hunter Connell's California hometown of Santa Rosa was partially incinerated in a 2017 wildfire, she vowed to find a way to predict – and ideally prevent – similar climate change-linked disasters.
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"We needed a way to account for the complexity and interdependence of the environment and climate conditions that lead up to an event like this" said Connell, an environmental engineer turned venture capitalist.
"A human brain alone cannot understand all these forces," she said.
Connell is now the CEO of Terrafuse AI, one of a constellation of climate analytics start-ups that aim to predict how climate change will impact certain industries, communities, zip codes and even individual properties.
The firms are building complex models to look at flooding, wind, wildfire, and other climate-related threats, fusing known climate science with mounds of additional data, from satellite imagery to existing migration patterns and city street drainage.
That can generate risk scores, allowing investors to play out how different climate scenarios will hit their assets – with some firms even recommending new parcels of land to purchase.
The rise of these analytics tools could alert policy makers and asset holders to the risks posed by climate change – and even help direct resiliency efforts.
But they also raise a host of concerns, climate equity experts said.
"What happens in a world where only people who have a lot of money are getting access to these predictions – and the rest of us aren't?" asked Miyuki Hino, a University of North Carolina environmental planning professor.
"More data doesn't necessarily lead to benefits for everyone," she said.
Rich Sorkin, the CEO of Jupiter, one of the most established players in the industry, said he also saw the risks.
"In the wrong hands, this can be like dynamite," he told the Thomson Reuters Foundation, noting it could "start a panic."
But the information also could achieve the opposite effect – reducing risks as users better grasp climate threats, helping drive the behavior change necessary to cut emissions and prepare for climate shifts, he said.
For everyone from home buyers to utility companies to massive real estate holders, accurate predictions about climate risk are increasingly a financial necessity.
In 2020, for example, wildfires burned through more than $13 billion in insured properties in California. Connell, of Terrafuse, said that money could have been saved with more accurate predictions of wildfire behavior.
By using historical data, the firm is training its AI model to make increasingly precise predictions of wildfire losses each year, she said, which can help insurance companies decide where to underwrite properties.
"Climate intelligence is a superpower," said Iggy Bassi, the CEO and founder of Cervest. "You are going to need it whether you are a policy maker, insurance broker, real estate builder, speculator or if you're a slum dweller."
Cervest has spent two years developing its own model that allows users to see the climate risk for individual plots of land or larger portfolios, breaking down threats from heat, wind and other factors.
Tech venture capital firm Draper Esprit, an investor in Cervest, estimates the value of the global climate analytics market at $40 billion
While some aspects of Cervest's platform will be offered free to users, holders of larger portfolios will be charged for more tailored predictions. The firm says more than 30 major companies are already users.
"These kinds of analytics are going to rule every transaction," he predicted, with mortgage brokers, for instance, using the tool to look up risks on a particular property before offering a loan.
"If it looks like it's a pretty safe house from a climate risk perspective they can offer the buyer a green mortgage" at a lower rate, he explained.
Such analytics tools are now taking hold across sectors including financial services, city agencies, insurance companies and utility firms.
Since 2019, Moody's – one of the three major credit agencies tasked with assessing the risk of bonds and other securities – has acquired two climate analytics companies.
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Last year, Broward County in Florida worked with Sorkin's firm Jupiter to develop its 100-year municipal flood projections.
And last summer California insurance regulators approved the use of Zesty.AI, another wildfire prediction platform, to inform insurance rates in the state.
For those interested in investing in climate resilience, such analytics could help decide the most efficient place to channel limited funds, Bassi said.
The analytics can also be put to use for private gain.
"There are nimble billionaires who are saying, 'I am dumping land (because of climate risk), tell me where to buy,'" said Parag Khanna, the CEO of ClimateAlpha.
The firm calls itself the Palantir of property, after the famous data analytics software firm founded by Peter Thiel.
ClimateAlpha, Khanna said, has engineered a "data lake" that integrates 50 environmental, demographic, fiscal, energy, and other variables for a given property.
It runs the data through its proprietary algorithm and provides customers with value predictions based on various climate scenarios.
Chris Marlin, the former president of Lennar International, one of the largest home builders in the United States, recently joined ClimateAlpha's board.
Everyone from home buyers to banks to real estate owners will eventually need access to climate-risk data, he said.
"The whole value chain of real estate is going to wake up to climate impacts," he said. "The questions are: when, and who is going to be best prepared?"
Jesse Keenan, a professor at Tulane University who has studied the industry and serves on the advisory board for Jupiter, noted that "of course people are going to make money on climate change."
He has described the race to develop the best algorithms to predict climate impacts as a "climate intelligence arms race" – but says there's a reluctance to reckon with the implications of that trend.
In 2018, a California university changed the title of a talk Keenan was slated to give – "How to Make Money from Climate Change in Real Estate" – because they were offended by the concept, he said.
But "this is happening," he said. "We have to understand how this works so we can figure out the right regulatory environment."
Regulators, for instance, could step in and use climate analytics tools to predict how the assets of financial institutions will fare under different climate scenarios, to better protect investors and the economy, Keenan said.
Before the end of 2021, the US Securities and Exchange Commission is expected to roll out new rules requiring publicly traded companies to disclose the risks climate change poses to their assets.
Some new climate analytics firms see helping make those predictions as a possible revenue stream.
But pricing risk and making accurate predictions is not the same as fighting climate change or responding to it fairly, said A.R. Siders, a professor at the University of Delaware's disaster research center.
"Pricing in the risk appropriately makes sense" – but doesn't necessarily lead to better public policy, she said.
"If what a town needs is a better planner this doesn't really help," she said.
Better predictions – without policies to protect the most vulnerable – also could simply supercharge climate inequities, she added.
"Let's say you use these tools to get a better sense of the risk of flooding," she said. As a result, "you make flood insurance more expensive and then all the low-income residents have to leave."
Hino worries that the insights derived from the tech might be deployed to benefit only a narrow set of interests.
"They may very well be used to argue for investments to protect the assets of those who need it least," she said.
