Mass Layoffs at NOAA: A Costly Mistake for Weather Forecasting
Mar 4, 2025, 5:20 PM | Skymet Weather Team
Image Courtesy: NOAA
Skymet is disheartened by the recent news of NOAA layoffs. According to the BBC, around 880 workers, including weather forecasters, have lost their jobs. This is not only discouraging for established scientists and meteorologists but also for young minds who aspire to follow in their footsteps and pursue a career in forecasting.
Behind every weather forecast is a dedicated meteorologist who has spent years and sometimes decades studying, researching and understanding the weather. Weather and climate sciences are as much done through machines as well as experience and intuition. Weather science isn’t just numbers and models; it’s experience, intuition and a deep connection to the atmosphere. Machines can process data, but they don’t feel the wind shift before a storm or recognize the telltale signs of sudden fog.
A lot of the gap-filling, as well as pattern recognition, is learned by experienced meteorologists over a lifetime. Thunderstorms and fog are among the trickiest weather phenomena to predict. A seasoned meteorologist, observing the skies and analyzing patterns, can often outperform a machine in a local forecast. The atmosphere is vast, and much of it remains unsampled. Without human expertise, refining forecasts will be an uphill battle in keeping people safe.
Recent times, as such, when weather extremities are so common, we must recognize the need of the hour and continue the ongoing legacy of years and years of traditional forecasting along with incorporating the recent advancements. At a time when extreme weather is becoming more common, cutting back on meteorologists is definitely a step in the wrong direction. Forecasting isn’t just about numbers, rather, it’s about lives, livelihoods and trust.
Models may lack analytical skills where field experts excel. Both statistical and dynamic models experience time delays due to data scarcity and real-time limitations, whereas experts can promptly make course corrections when needed. Model outputs are static, while meteorologists have the flexibility and intuition to adapt. Machines can generate forecasts based only on historical data, but every weather event has its own unique signature - this is where meteorologists and weather scientists play an irreplaceable role.
