"Snow and rain can be difficult events to predict because long-range models shift from day to day, and sometimes from hour to hour, with general patterns of pressure, precipitation, air speed, and temperature fluctuating constantly in the run-up to a big storm. This is why professional meteorologists speak in potentialities and probabilities, identifying trends across many different models to determine the likelihood of a given outcome."
"But probabilities are less sexy than proclamations, ambiguities less attractive than assurances-or so the rising number of storm-hyping accounts on social media seem to suggest. "I've looked at EVERY Major Weather Model that exists," the weather influencer Brady Harris wrote on X, on Friday. "I've looked at numbers. I've looked at the trends. They all point to 1 THING." That thing? Snow-and not just any run-of-the-mill snow, but, according to Harris, the "Big Snowstorm we've all been waiting for.""
"Yes, weather influencers exist, and their accounts-along with those of social-media-driven weather brands-have become increasingly popular thanks to their flair for the dramatic. Compared to their credentialled meteorologist counterparts, engagement-driven accounts run by private weather services and amateur storm chasers tend to exaggerate possibilities and foment hype for anticipated weather events, presenting forecasts as facts and predictions as guarantees. Despite using the same models as the professionals—anyone can freely access National Oceanic and Atmospheric Administration data."
Professional meteorologists frame forecasts as probabilities because long-range models change daily and even hourly, with pressure, precipitation, wind, and temperature patterns fluctuating before major storms. Social-media weather influencers and engagement-driven weather brands often present forecasts as certainties, amplifying dramatic outcomes and promoting storm hype. Many influencers and amateur services use the same publicly available NOAA model data as professionals, but prioritize attention and engagement, which encourages exaggeration. This amplification can mislead the public about forecast uncertainty, erode trust in credentialed meteorologists, and create mismatched expectations for weather events. Algorithms and commercial incentives help spread sensationalized forecasts widely.
Read at The New Yorker
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