EarthRisk Figures Odds in Long-Range Forecasts of “Extreme Weather”

1/25/12Follow @bvbigelow

If you were in the business of supplying heating oil in the Northeast, do you think it would be useful to know if a big winter snowstorm is likely to arrive with sub-zero temperatures in Massachusetts next month? How would fire chiefs in the brushy backcountry of Southern California react if they knew the odds of intense Santa Ana winds would increase dramatically in four weeks?

For all of meteorology’s satellite imaging and computer modeling, John “JP” Plavan and Stephen Bennett say it’s just about impossible to use current weather forecasting models to make more than general predictions about the weather more than two weeks in advance. That might be enough time for fuel oil suppliers to get a few extra shipments into local dealers, they say, but it’s not sufficient to make decisions at the highest levels of a big corporation or government agency.

But what if a weather forecasting model could “estimate” the likelihood of extreme weather events 30 or 40 days in advance? Would it be helpful, for example, to know if the odds a major winter storm would hit a particular region had increased from 33 percent to, say, 66 percent?

This, in a nutshell, is the promise of the innovation under construction at EarthRisk Technologies, a San Diego company that Plavan and Bennett founded less than two years ago. “If you’re Home Depot, you certainly want to have snow shovels in stock if you’re anticipating a big snowstorm,” says Bennett, a career meteorologist who helped create the company’s predictive analytics technology with scientists at U.C. San Diego’s Scripps Institution of Oceanography. Likewise, if you’re the Federal Emergency Management Agency, you’d certainly want to get a 30-day advance warning of the next Hurricane Katrina.

“We fancy ourselves as a software company, not as a weather company,” says Plavan, an investor serving as the company’s founding chairman and CEO. “We provide information that helps our clients make decisions of value.”

Bennett, who is EarthRisk’s chief science and products officer, says the highest value for the company and its customers lies in determining the likelihood of extreme weather—heat waves, cold snaps, and the kinds of storms that trigger destructive events like tornadoes, hurricanes, and flooding. “Extreme events are the ones that have the highest impact,” Bennett says. “The places where the opportunities are to be seized, and the risks managed, are at the extremes.”

JP Plavan

Plavan compares the startup’s predictive analytics to counting cards in Blackjack, a technique used by some gamblers to optimize their bets and to guide how they play each hand. “The odds change, depending on the cards already played,” Plavan says. Instead of six decks of cards in the dealer’s shoe, however, EarthRisk calculates the odds for extreme weather events based on correlations between existing weather patterns and historical patterns in a database that encompasses more than 60 years of detailed global weather data.

“The research question that Scripps Oceanography helped us answer is whether there are certain things that the atmosphere does that loads the dice, so to speak, in the way things play out,” Bennett says. “The data patterns have become so complex that it’s too much for a meteorologist—for one brain—to digest.”

Their focus on the statistical risks of extreme weather events also represents a fundamentally different approach from the long-range forecasts now issued by the U.S. Climate Prediction Center, which relies on a different type of computer model.

Bennett began his career as a meteorologist, working as a forecaster at The Weather Channel, WeatherData, and other media outlets. He later obtained a law degree, and eventually landed at Enron, where he helped develop extended forecasts used by the energy giant in natural gas commodities trading.

After Enron imploded in scandal, Bennett says their seven-person team joined the Chicago-based Citadel Investment Group, which expanded their group to 150 people in a global energy trading business focused on oil and natural gas. “The gist of the job was to use weather forecasts and related data to support our commodities pricing forecasts in futures markets,” he says, explaining that trading in a variety of commodities futures can be highly influenced by extreme weather events that affect supply and demand. During his last two years at Citadel, Bennett said he focused on insurance and reinsurance investment strategies for large swaths of U.S. coastal areas that are subjected to hurricanes.

Because extreme weather can disrupt commodities markets, Bennett says he became increasingly interested in the possibility of using predictive analytics to extend the window of conventional weather forecasts beyond 10 to 14 days. Developing such capabilities, however, required the kind of expertise that usually resides in research universities.

Bennett says that Tony Haymet, director of Scripps Institution of Oceanography, viewed the research as a valid scientific issue for the school, which has gained recognition for its research into global climate change. With guidance from Bennett, who joined Scripps on a part-time basis, climate scientist Alexander Gershunov and postdoctoral researcher Kristen Guirguis developed a proprietary methodology to validate whether certain weather patterns were statistically consistent. For example, when a certain jet stream pattern forms over Alaska, the odds that severe cold will descend on the Midwest increase significantly.

The research succeeded in identifying a variety of patterns that could be correlated to current weather conditions, but it was impractical for commercial use, Plavan says. So Bennett and Plavan worked with UC San Diego’s Technology Transfer Office to license the technology and enlisted Digital Telepathy, a San Diego software engineering firm, to create a graphical user interface. “We knew going into this that turning this data into usable information was the job of the private sector,” Bennett says.

Digital Telepathy became an investor in EarthRisk Technologies, along with Sear Technologies, a San Diego investment firm that Plavan and two partners founded in 2008. “We didn’t need to get a big equity investor to fund development,” Plavan says.

The company also has generated some revenue by providing its technology to 10 customers on a subscription basis. “We currently can only sell to energy firms large enough to have their own meteorology desks,” Plavan says, explaining that some technical expertise is needed to interpret the data. EarthRisk’s next step is to develop next-generation technology capable of generating probabilistic forecasts. With eight full-time employees and consultants, Plavan and Bennett plan to also expand their forecasting capabilities beyond cold snaps and heat waves (which is the chief value and focus of their energy customers) to hurricanes and other destructive storms.

“We’re already breaking new ground by introducing these new products,” Bennett says. “If we are ultimately successful in pioneering these new weather analytics techniques, they will become widespread. They’ll become the industry standard.”

For EarthRisk Technologies, Plavan says, “Our goal is to generate a large amount of recurring revenue,” based on a software-as-a-service business model. “We think we can sell an awful lot of subscriptions with this.”

Bruce V. Bigelow is the editor of Xconomy San Diego. You can e-mail him at bbigelow@xconomy.com or call (619) 669-8788 Follow @bvbigelow

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