WASHINGTON — Karen St. Germain’s office in Silver Spring, Md., is a weather geek’s dream, with large windows providing expansive views to the west, across the northern suburbs of Washington.
It’s a fitting angle — ideal for watching incoming storms — for someone who occupies one of the top positions in the National Oceanic and Atmospheric Administration at a time when the agency is caught between growing demand for timely and accurate weather information, and competition from a host of new companies threatening to beat government agencies at their own game.
The outcome of that competition could affect the public's access to the best available weather and climate data in the years ahead.
Fueled in part by climate change, extreme weather is an increasing liability to the economy, with 10 weather and climate disasters costing more than $1 billion each so far this year, according to NOAA. During the last two years alone, Western wildfires have cost more than $40 billion. Hurricanes are dumping more rain than they used to, and heat waves are more intense and frequent.
Those rising costs — along with advances in data-gathering and processing, and cheaper access to low Earth orbit — have spurred start-ups and established companies to get into the business of weather forecasting.
Private weather forecasting is a $7 billion industry and growing, according to a 2017 National Weather Service study. It's also increasingly testing the federal government's hold on weather data and warnings.
Those pressures are expected to grow as forecasting moves into environmental prediction, such as anticipating harmful algal blooms and dengue virus outbreaks. The Trump administration has so far shown little inclination to make sure government agencies stay ahead of private competition.
Until recently, AccuWeather, Earth Networks, the Weather Co., and other private weather providers relied on the fire hose of data from NOAA’s National Weather Service and satellite arm, as well as NASA and other agencies. Now companies are producing their own data and using analytics in business-savvy ways, tailoring their forecasts to specific real-world problems.
With the ability to launch satellites and supercomputers and to harvest data from semiautonomous vehicles and wearables, the new arrivals are leapfrogging the information-gathering capabilities of federal agencies.
They are also more nimble in analytics, using machine learning, artificial intelligence, and cloud-based systems to warn a railroad company when to avoid a tornado barreling toward a specific stretch of track, or telling a farmer when to irrigate a particular row of crops. These companies are advising airline ground controllers when they might need to de-ice planes, or reschedule flights to avoid severe thunderstorms.
And they are putting the National Weather Service in an awkward position as it tries to fulfill its mission of protecting lives and property. The agency faces the prospect of having to partner with outside companies to get the best data. Not all of them are willing to share. Some of them harbor ambitions of taking over more of the federal government's functions.
As the director of the Office of Systems Architecture and Advanced Planning at NOAA's Satellite and Information Service, St. Germain, a satellite instrument specialist and graduate of the Naval War College, is charged with navigating through that unfamiliar business environment, and ensuring the country has the data it needs to prepare for the extreme weather and environmental events headed our way.
Among her challenges are the growing tensions between, as she sees it, two ends of the value chain when it comes to weather and climate observations.
"So on one hand we've got the emerging interests that want to make observations and sell them," St. Germain said. "And they want to, of course legitimately, then they want to control the licensing terms and so forth and sell to more than one [customer]. And then on the other end of the value chain, we've got the folks who make their money by building tailored products."
Those companies are used to getting their data free from the government and using it to create their products. "So there's a lot of natural tension there. And I don't know how all of that will play out," she said.
In such a fast-moving business environment, there are clear risks in spending public money on novel technologies.
St. Germain, who is powered by an espresso machine on her desk adorned with Washington Nationals bobbleheads, has to make sure the data are accurate and reliable — and that any company she partners with will remain in business for the long term. She is worried that NOAA would contract with a private firm for data that are crucial for issuing timely severe weather warnings, only to see that company suddenly go out of business.
"We don't have to frame this as an either/or question. We don't have to choose between relying only on commercial data sources or only on traditional 'government' sources," she said. In President Donald Trump's fiscal year 2020 budget request, she said, there is an increase to buy space-based commercial weather data, which would be a first for NOAA.
But the expansion of private weather forecasting means a future in which the federal government may no longer be the primary source of weather information.
Consumers are already getting used to the idea of private sources of information for weather — even if the data originate with the Weather Service. We rely on weather apps to get our daily forecast, be it Weather Underground, the Weather Channel, Dark Sky, or many others.
The past decade has seen a flurry of launches as well as consolidation in the private weather business, with IBM’s $2 billion purchase of the Weather Co. in 2016, which included the popular weather.com website and app but not the cable network attached to that site. Climate Corp., whose computer modeling tools provide farmers with the ability to plan for increasingly common weather whiplash, with the Midwest lurching from drought to flood and back again, was bought by Monsanto in 2013.
In November, IBM rolled out a global weather forecast model developed in partnership with the nonprofit National Center for Atmospheric Research that claims to accurately predict small-scale weather features such as severe thunderstorms. IBM says the service represents an advance for places like Africa and South Asia that may have few weather observation posts and poor infrastructure.
Spire, a start-up, has launched a fleet of dozens of tiny satellites that track ships and aircraft, and gathers atmospheric data to help improve weather predictions. The company is marketing that data, known as radio occultation, to NOAA and international agencies as a way to improve their forecasts or eliminate the need for their own larger, more expensive satellites.
Ursa Space Systems, which uses satellite-based systems to provide images of Earth's surface even when there is cloud cover, is producing products aimed at the insurance industry. Descartes Labs and Planet Labs are using imaging analysis for fire weather prediction. They, along with other satellite imaging firms, are also competing to sell data to financial firms to predict company earnings.
ClimaCell, founded by three Israeli military veterans, uses data harvested from cellphone towers, vehicles and other unconventional sources. JetBlue has invested in the company and uses its tools for forecasting operations at major hubs including Boston and Fort Lauderdale.
These challenges to the primacy of the National Weather Service come when Americans increasingly are focused on the weather because of climate change and the growing impact of extreme weather.
“Weather has moved into this much bigger role in people’s psyche today because of the amount of devastation that it’s bringing,” said Washington Sen. Maria Cantwell, the ranking Democrat on the Senate committee that oversees NOAA and NASA. Cantwell said she wants NOAA to have the technology it needs to better serve the public rather than ceding ground to the private sector.
The Weather Service is already sometimes lagging behind global technological advances, especially in computer model accuracy.
Europe’s main weather forecasting model often beats the Weather Service’s Global Forecast System — most famously when the European model accurately predicted Hurricane Sandy’s unprecedented track a week in advance in 2012.
The National Weather Service, with congressional support, is trying to close the gap, chiefly through a new modeling program called the Earth Prediction Innovation Center, which aims to speed up model development through collaboration with universities, other agencies and the corporate sector.
Andrew Blum, author of the book The Weather Machine, warns that commercial competition for data could put the public at risk if agencies like NOAA allow it to stifle the flow of free data, which is fed into every global computer model.
"None of these models work unless we have the global data," he said. The risk we're running now is that "someone turns off the spigot," possibly motivated by legal agreements stemming from commercial data buys, robbing everyone else of key data.