Western NC housing nonprofit executive warns ‘lives will be lost’ to DOGE weather service cuts

Why Elon Musk-directed cuts to federal programs will endanger people in North Carolina during the next disaster.

by Brandon Kingdollar, NC Newsline
March 25, 2025

On a panel Monday discussing the Trump administration’s cuts to the National Weather Service [NWS], Todd Carter, an executive with a western North Carolina housing nonprofit, warned “lives will be lost” due to ongoing staff and budgets cuts.

“We make this information available for free. Not everything should be for sale, not everything should be for profit,” said Carter, Hospitality House of Northwest NC’s chief development director. “[Without NWS] we’d have to pay for a report every time something comes out — we don’t have the time to do that, we don’t have the funding to do that, and lives will be lost.”

Carter said his organization, which has worked to house North Carolinians displaced by Helene across seven counties impacted by the hurricane, is able to mobilize ahead of storms early because it receives emergency alerts through the National Oceanic and Atmospheric Administration, an agency targeted for major cuts by Elon Musk’s so-called Department of Government Efficiency.

That’s because agency officials recognize Hospitality House provides “critical” services to the rural counties it helps — Watauga, Wilkes, Ashe, Avery, Alleghany, Mitchell, and Yancey — Carter said.

“One of our clients in an apartment, she was crying for help, she got to the very top of the roof of her apartment building, and she was telling our executive director [Tina Krause], ‘Miss Tina, I can’t swim, I can’t swim,’” Carter said. “She’s 75 years old and was afraid she was going to die.”

Another resident helped by the nonprofit, a 72-year-old man, had to be rescued by boat, according to Carter. “They were bringing people by boat down the road to us and our staff were doing the best they can.”

It was after the region’s devastation by Helene — when rising floodwaters and violent winds knocked out cell service in Boone, where the housing nonprofit is based — that weather officials provided them with NOAA radios and set them up on the early warning system. Now, though, cuts to the service may leave them unprepared for a future disaster.

The Monday afternoon panel — hosted by the Center for American Progress, a left-leaning think tank — comes as NOAA, the agency that oversees the National Weather Service, is poised to lose more than 20% of its workforce. At DOGE’s direction, the agency is slashing more than 2,000 jobs — around 1,300 in February and another 1,000 set for March, according to the Associated Press.

Many of those officials serve as weather forecasters, helping to predict hurricanes, tornadoes, and other potentially deadly storms before they occur. For now, the firings are on hold, after a pair of federal judges ordered the rehiring of laid-off employees. The Trump administration has petitioned the Supreme Court to allow the firings, AP reported.

“NOAA works closely with FEMA and other agencies to make sure that decisionmakers have high-quality data in a timely manner to make the decisions that they have to make,” said panelist Michael Morgan, a former NOAA official who served under the Biden administration. “Loss of that staffing means a reduction in NOAA’s ability to serve the public, and that could lead to, unfortunately, loss of lives.”

David Dickson, a meteorologist with Covering Climate Now, called NWS models the “invisible backbone of all weather forecasts.” Cuts to the agency would make those models less accurate, endangering lives and risking severe impacts to the U.S. economy. (Because of the importance of accurate weather monitoring to U.S. trade, the agency is under the Department of Commerce.)

“The National Weather Service gives in excess of a hundred billion dollars to the U.S. economy. That’s why this is so important,” Dickson said, warning that even canceled weather balloon launches make those forecasts more prone to inaccuracy. “We’re seeing impacts to this data set that are almost like a butterfly effect.”

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