As the United States braces itself for an intense hurricane season and unprecedented summer heat, fears are mounting that recent budget cuts from the Trump administration could jeopardise the reliability of crucial weather forecasts. Experts warn that diminished funding for climate and weather data collection may leave the federal government ill-equipped to handle the extreme weather events that are increasingly becoming the norm.
The AI Forecasting Dilemma
Last year, the National Oceanic and Atmospheric Administration (NOAA) introduced a new suite of artificial intelligence-driven global weather forecasting models, which officials claimed would enhance the speed, efficiency, and accuracy of weather predictions. However, as Monica Medina, former principal deputy undersecretary of commerce for oceans and atmosphere, points out, the effectiveness of these AI models hinges on the quality and quantity of data they are trained on. “We absolutely need AI to help us crunch the data faster,” Medina stated, but she emphasised that ongoing cuts to data collection efforts are taking the country in the wrong direction.
Despite NOAA’s reassurances that a robust network of data collection persists, including satellites, weather balloons, buoys, and ground sensors, many reports highlight that staffing reductions have resulted in significant limitations to satellite observations and balloon launches. This decline in data collection is particularly troubling as the country prepares for a summer marked by extreme weather conditions, including a looming ‘super El Niño’ that is expected to elevate temperatures and potentially increase hurricane activity.
Traditional Models vs. AI-Based Predictions
For decades, conventional weather forecasting relied on physics-based models that utilised complex mathematical equations to simulate atmospheric dynamics. In contrast, the newer AI models focus on recognizing patterns in historical data to forecast weather outcomes. While they require less computational power and have outperformed traditional models in certain aspects, they are not without their shortcomings.
In an April study published in *Science Advances*, researchers found that AI models tend to struggle with predicting extreme weather events, often failing to account for the unprecedented conditions exacerbated by climate change. “They seem to have trouble simulating the record-breaking weather events that are becoming increasingly common,” noted Sebastian Engelke, a professor at the University of Geneva and co-author of the study. The reliance on historical data limits AI models’ ability to predict what is becoming a drastically altered climate landscape.
Chris Gloninger, a forensic meteorologist who has faced backlash for speaking out on climate issues, highlighted the potential dangers of relying on AI systems trained on outdated climate data. “The AI weather models were trained on a climate that no longer exists,” he warned, stressing that the infrastructure built on historical climate assumptions is now woefully inadequate to cope with the realities of climate change.
The Risk of Underfunding
The implications of reducing funding for NOAA and its data collection efforts are profound. Craig McLean, former acting chief scientist at NOAA, articulated the direct correlation between climate research funding and the accuracy of weather forecasts, stating, “Cutting climate research impacts the skill of our weather forecast.” As the nation faces a future fraught with more frequent and severe weather events, the urgent need for comprehensive and reliable data is clearer than ever.
In April, NOAA is expected to reveal its outlook for the 2026 Atlantic hurricane season, and the stakes could not be higher. As Gloninger cautioned, if the government increases its reliance on AI models while simultaneously curtailing the data that informs them, it could lead to a “snowball effect” of deteriorating forecast accuracy.
The Role of Leadership and Funding
Neil Jacobs, the current NOAA administrator, is acknowledged as a leading expert in modelling science. However, as a Trump appointee, he faces the challenge of balancing scientific integrity with the constraints of a politically motivated budget. While Jacobs has a reputation for advancing weather forecasting, critics argue that his position may limit his ability to advocate for necessary changes, especially in light of the administration’s damaging cuts to NOAA.
Medina encapsulated the crucial role weather forecasts play in everyday life, stating, “Weather forecasts are vital to our economy, to our health, and to public safety.” As the nation grapples with the escalating climate crisis, the stakes couldn’t be higher. The ability to provide accurate forecasts could mean the difference between life and death during extreme weather events.
Why it Matters
The escalating climate crisis demands robust and reliable weather forecasting systems, yet ongoing cuts to data collection threaten to undermine this essential function. A failure to invest in comprehensive climate research and data infrastructure not only jeopardises public safety but also compromises economic stability. As the consequences of climate change become increasingly apparent, the need for accurate predictions to guide disaster preparedness and response has never been more urgent. Without a concerted effort to address these shortcomings, the nation risks being ill-prepared for the extreme weather events that lie ahead.