Perspective: Weather businessWeather Is Turning into Big Business. And That Could Be Trouble for the Public.

Published 2 December 2019

This may well be the future of weather forecasting: “Now for your local weather forecast: That’ll be $10, please.” Climate change is inflicting an increasingly heavier costs on the U.S. economy, and 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.

Climate change is inflicting an increasingly heavier costs on the U.S. economy. 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. Andrew Freedman writes in Washington Post that during the past two years alone, Western wildfires have cost more than $40 billion. Hurricanes cause much heavier rainfall than they used to, and heat waves are more frequent and more intense.

Freedman writes:

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.

Freedman notes that unlike existing private forecasting companies — AccuWeather, Earth Networks, the Weather Co., and others — the new weather prediction start-ups are gathering and producing their own data, using analytics with an eye to serving business needs, and 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.

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