Weather forecasting has gotten a big boost from machine learning. How that translates into what users see can vary.
The Weather Company, operator of the Weather Channel, today released a revamped version of its Storm Radar app, featuring an AI-powered Weather Assistant that lets users customize how they view forecasts and weather maps, toggling between layers like radar, temperature, and weather conditions like wind and lightning.
It can also sync with other apps, like your calendar, to send text notifications and weather summaries that tie info about the upcoming weather into your daily plans. You can stick a voice on it to talk like an old-timey radio weatherman, if you’re into that. Like most weather apps, it gets the data comes from the National Oceanic and Atmospheric Administration and the National Weather Service . The app costs $4 per month. It is available on iOS only for now, but the company says an Android version is coming eventually. “We wanted to build an experience that would be a weather level-up for anybody, really, from a casual observer to a seasoned storm chaser,” says Joe Koval, a senior meteorologist at the Weather Company. “If you're looking for advice on when the weather will be good to walk your dog tomorrow, you no longer have to look at a bunch of different disparate weather data elements and try to figure out the answer to that question yourself.” You can find the weather on your phone already, of course. Android and iOS devices typically place the weather prominently beside the time. Google and Apple have both fused their weather apps into their smartphones directly. AI features have since been infused, offering insights and summaries about the day to come. But there are third-party weather apps galore, like Storm Radar, Carrot Weather, Rain Viewer, and Acme Weather—an app from the former Dark Sky app creators. New weather apps like Rainbow Weather aim to be AI-first. Weather services are also being integrated directly into AI chatbots, like Accuweather, which recently launched an app directly in OpenAI’s ChatGPT. “Everyone has their idea of what they want in a weather app, what data they're interested in, how they're interested in it being presented,” says Adam Grossman, a founder of the DarkSky app. “How do you build a single weather app that works for everybody?” DarkSky, one of the most popular iOS weather apps, was bought by Apple in 2020 and merged into its Apple Weather service. Grossman eventually left Apple to start Acme Weather, with the goal of making a weather prediction service that better telegraphs the uncertainty of forecasting. “No matter how good your forecast is, you're going to be wrong,” Grossman says. “That’s something that weather apps traditionally haven’t done a great job of doing. Our approach is trying to figure out how to add those pieces of context back in.” Repositories of weather information usually come from government sources, like NOAA or other global weather services that collect data from weather satellites, radar, weather balloons, and on-the-ground instruments. All that data is fed into weather prediction models that simulate the physics of the atmosphere. Those predictions are often generated by resource-intensive supercomputers, but machine learning models have trimmed that processing down, making predictions quicker. Weather apps like Storm Radar and Acme Weather translate that bounty of information by corroborating and compiling the models, then helping to create high-resolution maps and a visual representation of the data, an area where AI can also be particularly useful. “Machine learning is probably the biggest change to weather forecasting in a while,” Grossman says. “And they’re just getting started.” The push of using AI in weather apps comes in the era where the government has dismantled NOAA and other federal efforts to track and measure weather patterns, leaving parts of the job of data collection to private companies. Weather systems also have a harder time predicting extreme weather events and climate disasters, which are growing ever more frequent. Koval says Storm Radar is taking a science-first approach to AI in its app. “If the NWS issues a warning, the AI isn't going to guess the risk,” Koval says. “It's going to cross-reference that official warning with your specific calendar at your location to tell you how it impacts your plan.” Storm Radar is a more maximalist approach, with layered complexity akin to something like Google Maps. For the real weather sickos, widgets can be customized to cover the screen, displaying any and all weather information available. The AI features of the app aim to simplify that overload of data, letting the AI assistant give a summary or short description of the weather to come. That can come in text form, or via several differently accented voices that aim to sound like TV meteorologists. “You can choose a persona ranging from a vintage weather person to a pop culture fan,” Koval says. “Personalization is really a key in this app.” Grossman, who says Acme Weather uses AI on the forecasting side, is skeptical about any service—weather or otherwise—that touts its AI just for the sake of having AI. “It should feel transparent; it shouldn't feel like you're talking to a chatbot,' Grossman says. 'If it's about surfacing the right content, you should open it up, and you should see what you need to see. It shouldn’t feel like AI is doing anything for you.”
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