The world will be forced to weather DOGE’s budget-slashing.
Massive layoffs at the National Oceanic and Atmospheric Administration (NOAA) could spell disaster for U.S. weather forecasting, experts warn. The cuts, part of Elon Musk’s Department of Government Efficiency (DOGE) overhaul, are targeting crucial forecasting offices that provide life-saving data for severe weather events.
Reports indicate that the White House is planning to cancel leases for essential NOAA facilities, including the Center for Weather and Climate Prediction and a radar development lab in Oklahoma—both critical in producing weather models used by the National Weather Service, U.S. military, and the Federal Aviation Administration. The loss of these centers could send the accuracy of U.S. forecasts into a sharp decline.
Meteorologists are sounding the alarm. Dr. Daniel Swain, a UCLA climate scientist, took to social media (in a now-deleted post) to say: “If this actually happens, it would spell the end of U.S. numerical weather prediction.” Veteran weather anchor Jim Cantore called it “horrible news” for the nation’s forecasting capabilities. 4029 News meteorologist Darby Bybee emphasized that the ability to predict severe weather is now “literally in jeopardy.”
The timing of these cuts has only added to the outrage, as they come just as the country grapples with severe storms, wildfires, and the impending hurricane season. Oklahoma Rep. Forrest Bennett couldn’t help but highlight the irony.
In his now-deleted X post, Rep. Forrest Bennett highlighted the stark irony, saying, “Just came here to make sure that the irony of severe weather occurring in OK the night it’s being reported that Trump’s DOGE is canceling the lease for the NOAA center in Norman, after laying off weather experts at NWS, isn’t lost on anyone.”
The impact of these layoffs is already being felt, with over 1,000 NOAA employees fired just last week, sparking protests from both the scientific community and politicians. Many of those let go had specialized expertise crucial for interpreting weather data, monitoring tsunamis, and enhancing forecasting models.
Evan Belkin, a recent hire by the National Weather Service in 2023, told NBC News, “When you don’t have people and bodies to verify how accurate the model depictions are, you’re not going to be successful.” The layoffs have left a serious gap in expertise, threatening the integrity of U.S. weather forecasting at a time when the country faces increasing weather-related challenges.
Kayla Besong, a scientist at the Pacific Tsunami Warning Center, also shared her concerns with NBC, emphasizing that NOAA’s systems are incredibly complex and require specialized expertise to operate. She explained, “I’ve been developing these skills for over 10 years. I’m an excellent programmer. Their systems are very niche, and they require people who know how to program.”
There’s growing speculation that the cuts could be politically motivated, particularly due to NOAA’s pivotal role in climate monitoring. Dr. Stefan Rahmstorf, a renowned climate scientist, suggested that the Trump administration may be targeting NOAA due to its climate research, commenting, “Maybe the word ‘climate’ in NOAA’s Center for Weather and Climate Prediction is the problem?”
Although there’s hope that some of these cuts could be reversed, much like how the National Science Foundation reinstated dozens of employees after public outcry, the damage to U.S. forecasting capabilities may already be irreparable. With hurricane season rapidly approaching, experts warn that the impact of these decisions will soon be felt by millions.
Tom DiLiberto, a climate scientist with NOAA since 2010, spoke to The Independent, offering a sobering perspective: “The government is here to help people. It’s not here to make things worse. But what they’re trying to do is make things worse, across the board.”
As the government struggles to sort itself out, the outlook for both weather predictions and national stability looks increasingly uncertain—cloudy skies ahead, both literally and figuratively.
