| Weather is turning into big business. And that could be trouble for the public. Now for your local weather forecast: That’ll be $10, please.
 
 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 past two years alone, Western wildfires have cost more than $40 billion. Hurricanes are dumping more rainfall 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 a farmer when to irrigate a particular row of crops. These companies are telling 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 Deputy Assistant Administrator for Systems at NOAA’s Satellite and Information Service, St. Germain, a satellite instrument specialist and graduate of the National 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. Consumers are already getting used to the idea of private sources of information for weather — even if the data originates 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. It might not be that big of a leap for people to get used to paying for a subscription service to get a basic forecast or even severe weather warnings, much like we pay for our favorite shows on Hulu or Netflix.
 
 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.
 
 On Monday, the Minnesota-based firm DTN announced a merger with Europe’s Meteogroup, creating what they  claim will be the largest private weather company worldwide. 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. For now it’s only a short-term forecasting tool, covering out to 12 hours. But the model could yield huge gains for government warning systems in nations that have struggled to warn their people in time of approaching severe weather, including tropical cyclones.
 
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