**
As the United States braces for another hurricane season and faces unprecedented summer heat, there are growing concerns that budget cuts enacted during the Trump administration could jeopardise the reliability of crucial weather forecasts. Experts warn that reductions in climate and weather data collection, alongside a shift towards artificial intelligence for forecasting, may leave the nation ill-prepared for the extreme weather events that are becoming increasingly common.
The Dilemma of Data Scarcity
Last year, the National Oceanic and Atmospheric Administration (NOAA) introduced a suite of AI-enhanced global weather models, claiming these innovations would enhance “speed, efficiency, and accuracy.” However, experts like Monica Medina, former principal deputy undersecretary of commerce for oceans and atmosphere, caution that AI’s effectiveness hinges on the availability of comprehensive historical data. Under the Trump administration, NOAA’s climate and weather data collection efforts have been significantly curtailed, with a proposed budget increase for the National Weather Service overshadowed by a staggering 40% overall cut to NOAA.
Medina emphasises the paradox: “We absolutely need AI to help us process the increasing volume of data,” she said. “But right now, what we’re doing is cutting back the data collection … we’re going in the wrong direction.”
Despite assertions from NOAA that a robust network of weather data continues to operate, including satellites, weather balloons, and land-based sensors, staffing reductions have led to scaled-back operations of essential data collection mechanisms. As a result, the integrity of the country’s forecasting capabilities is under serious threat, with implications that could be disastrous in an era defined by climate volatility.
AI Limitations in Weather Forecasting
For decades, meteorologists relied on traditional physics-based models, using intricate mathematical equations to predict future weather. While the new AI models identify patterns from historical data, experts are quick to point out their shortcomings. According to a recent study published in Science Advances, AI models struggle to predict extreme weather events, often reverting to historical norms rather than accounting for the unprecedented conditions driven by climate change.
Sebastian Engelke, a professor at the University of Geneva, highlighted the crux of the problem: “They don’t really care if there’s a different situation than we’ve seen before, because they can understand based on a rules-based analysis what will happen tomorrow.” The implications of this limitation are becoming increasingly evident, especially as the United States anticipates a “super El Niño,” which could drive record-breaking heat and heightened hurricane activity.
Chris Gloninger, a forensic meteorologist, further illustrated the challenges posed by AI. He noted that the infrastructure in place for weather prediction was built on the assumption of a stable climate. As extremes become more frequent, AI models trained on historical data become less reliable. Gloninger lamented, “The AI weather models were trained on a climate that no longer exists.”
The Future of Weather Forecasting
The reliance on AI models amid budget cuts could create a precarious situation for federal weather forecasts. As Gloninger warned, “You need accurate data for inputs for our forecast models, but we’re running on less data currently with this administration.” NOAA maintains that AI is being integrated into its ensemble models, which combine various forecasting techniques. However, concerns persist that the extent of AI’s application could outpace its readiness, especially with a diminishing data foundation.
Neil Jacobs, the current NOAA administrator, is regarded as a leading expert in modelling. Still, his position as a Trump appointee raises questions about his ability to challenge the administration’s budget priorities without risking his job. While Jacobs has defended the cuts at congressional hearings, critics argue that his commitment to advancing weather forecasting may be compromised by an allegiance to budget constraints that ultimately undermine NOAA’s capabilities.
Why it Matters
Accurate weather forecasts are not merely a convenience; they are essential for public safety, economic stability, and disaster preparedness. As climate change continues to amplify weather extremes, the consequences of unreliable forecasting could be dire. With lives at stake, the intersection of funding cuts and the adoption of unproven AI technology poses a serious risk to the nation’s ability to respond effectively to natural disasters. It is imperative that we prioritise investment in robust data collection and research to protect communities and safeguard the future.
