Weather Service Scrambles in Hurricane Season After Trump Purge 61%

By Edith Olmsted82%

7/6/2026, 8:08:28 PM

BS Summary: This article contains 22 faulty reasoning types, including Negativity Bias, Pessimism Bias, and Availability Heuristic, with Post Hoc (False Cause) as the most egregious example at 32.5% saturation with 176 hits. Analysis detected 1,021 faulty-reasoning hits from 541 analyzed words, generating a BS Score of 56.8% and a BS Rank of 61% (8,565 of 21,886 articles). This article is worse (more manipulative) than 60.90% of the article peer group.

Nearly a year after President Donald Trump’s mass government layoffs, the National Weather Service and the National Oceanic and Atmospheric Association are still scrambling to replace scientists and collect missing data. 
The NWS is hiring for hundreds of mostly entry-level positions, after the agency lost about 15 percent of its employees during Trump’s first year back in office, CBS News reported Monday. 
Tom Fahy, legislative director of the National Weather Service Employees Organization, said that the agency had shed roughly 600 workers in 2025. 
Most of those employees were seasoned workers who accepted early retirement packages, while roughly 100 were probationary employees in their first year of work. 
Meanwhile, NOAA employed nearly 300 fewer meteorologists and hydrologists at the end of May than it did in January 2025, according to federal data reviewed by CBS News. 
Former government scientists told CBS News that mass layoffs, which forced out experts, have undermined the research and forecasting conducted by these agencies. 
Alan Gerard, a meteorologist who worked for three decades at the weather service and NOAA before retiring last year, told CBS News that the Trump administration’s sudden reductions to the workforce disrupted the flow of institutional knowledge. 
“Obviously, people retiring and new people coming up is a natural part of any business or agency,” Gerard said. 
“But it’s meant to be done in an organized process, where the new people coming in have the benefit of working for a period with people who are experienced and can help train them and build up their expertise.” 
Rick Thoman, a climate specialist in Alaska who worked for three decades as a weather service meteorologist, told CBS News that the sudden layoffs had been “a really bad thing.” 
“Alaska is not like forecasting for Nebraska, and there are no schools of meteorology in Alaska. 
Everyone has to come here and learn it,” Thoman said. 
“So, even though there’s some effort to increase staffing now, because there are no old-timers left, and folks come in here without any experience in high-latitude weather forecasting, it just makes it that much harder.” 
Already, the cracks have started to show. 
Since Trump returned to office, employees, including Gerard and Thoman, have observed a notable decline of “upper air” data collected by weather balloons as several weather stations have stopped launching probes twice daily. 
“There’s concern about the quality of the models because of the lack of upper air data,” Gerard told CBS News. 
“There’s a lot of expression of just being less confident, and having less confidence in your data tends to undermine a lot of your operational decisions, right?” 
Thoman pointed out that in October, weather models had incorrectly predicted a storm that displaced more than 1,000 people, after more than half of the area’s scheduled balloon launches failed to take flight in the days before the storm hit. 
Thoman said it was “inconceivable” that the lack of data had made no impact on the weather model forecast. 
This shortage of both data and weather experts is especially concerning with the hurricane season about to start. 
Climate change has resulted in longer, more intense storms—and now, it looks like some people won’t be as well equipped to face them. 
Article reasoning-pattern comparisonThis article: 5.7%Edith Olmsted: 4.8%newrepublic.com: 6.1%Confirmation Bias5.7%This article: 0.0%Edith Olmsted: 0.5%newrepublic.com: 0.5%Anchoring Bias0.0%This article: 12.6%Edith Olmsted: 3.2%newrepublic.com: 3.3%Availability Heuristic12.6%This article: 3.0%Edith Olmsted: 0.7%newrepublic.com: 1.0%Representativeness Heuristic3.0%This article: 0.0%Edith Olmsted: 0.8%newrepublic.com: 0.8%Hindsight Bias0.0%This article: 3.5%Edith Olmsted: 2.4%newrepublic.com: 2.0%Overconfidence Bias3.5%This article: 5.9%Edith Olmsted: 11.7%newrepublic.com: 8.0%Framing Effect5.9%This article: 0.0%Edith Olmsted: 0.0%newrepublic.com: 0.4%Loss Aversion0.0%This article: 7.2%Edith Olmsted: 0.3%newrepublic.com: 0.3%Status Quo Bias7.2%This article: 0.0%Edith Olmsted: 0.1%newrepublic.com: 0.1%Sunk Cost Effect0.0%This article: 0.0%Edith Olmsted: 0.0%newrepublic.com: 1.0%Optimism Bias0.0%This article: 15.7%Edith Olmsted: 3.3%newrepublic.com: 2.5%Pessimism Bias15.7%This article: 27.4%Edith Olmsted: 21.0%newrepublic.com: 13.3%Negativity Bias27.4%This article: 0.0%Edith Olmsted: 1.9%newrepublic.com: 0.9%Self-Serving Bias0.0%This article: 0.0%Edith Olmsted: 2.7%newrepublic.com: 2.0%Fundamental Attribution Error0.0%This article: 6.8%Edith Olmsted: 0.7%newrepublic.com: 0.2%Actor-Observer Bias6.8%This article: 0.0%Edith Olmsted: 1.3%newrepublic.com: 1.7%In-Group Bias0.0%This article: 0.0%Edith Olmsted: 1.2%newrepublic.com: 1.0%Out-Group Homogeneity Bias0.0%This article: 0.0%Edith Olmsted: 1.1%newrepublic.com: 1.2%Halo Effect0.0%This article: 0.0%Edith Olmsted: 1.7%newrepublic.com: 0.6%Horn Effect0.0%This article: 0.0%Edith Olmsted: 0.0%newrepublic.com: 0.0%Dunning-Kruger Effect0.0%This article: 9.4%Edith Olmsted: 2.4%newrepublic.com: 1.4%Recency Bias9.4%This article: 0.0%Edith Olmsted: 0.3%newrepublic.com: 0.5%Primacy Effect0.0%This article: 0.0%Edith Olmsted: 0.1%newrepublic.com: 0.1%Blind-Spot Bias0.0%This article: 0.0%Edith Olmsted: 6.0%newrepublic.com: 3.8%Ad Hominem0.0%This article: 0.0%Edith Olmsted: 1.3%newrepublic.com: 1.1%Straw Man0.0%This article: 5.0%Edith Olmsted: 2.3%newrepublic.com: 3.4%Appeal to Authority5.0%This article: 4.3%Edith Olmsted: 1.2%newrepublic.com: 1.9%False Dilemma4.3%This article: 0.0%Edith Olmsted: 1.3%newrepublic.com: 2.0%Slippery Slope0.0%This article: 0.0%Edith Olmsted: 0.2%newrepublic.com: 0.3%Circular Reasoning0.0%This article: 1.8%Edith Olmsted: 9.7%newrepublic.com: 8.0%Hasty Generalization1.8%This article: 0.0%Edith Olmsted: 0.4%newrepublic.com: 0.3%Red Herring0.0%This article: 0.0%Edith Olmsted: 0.8%newrepublic.com: 0.6%Bandwagon0.0%This article: 8.9%Edith Olmsted: 7.6%newrepublic.com: 6.3%Appeal to Emotion8.9%This article: 3.7%Edith Olmsted: 1.8%newrepublic.com: 1.8%Begging the Question3.7%This article: 32.5%Edith Olmsted: 6.2%newrepublic.com: 3.2%Post Hoc (False Cause)32.5%This article: 0.0%Edith Olmsted: 0.1%newrepublic.com: 0.3%Tu Quoque0.0%This article: 0.0%Edith Olmsted: 2.4%newrepublic.com: 0.8%Burden of Proof0.0%This article: 0.0%Edith Olmsted: 0.0%newrepublic.com: 0.1%Appeal to Nature0.0%This article: 6.5%Edith Olmsted: 0.3%newrepublic.com: 0.3%Composition/Division6.5%This article: 7.4%Edith Olmsted: 2.2%newrepublic.com: 2.0%Anecdotal7.4%This article: 0.0%Edith Olmsted: 0.2%newrepublic.com: 0.2%No True Scotsman0.0%This article: 3.5%Edith Olmsted: 2.5%newrepublic.com: 1.8%Ambiguity (Equivocation)3.5%This article: 0.0%Edith Olmsted: 0.0%newrepublic.com: 0.0%Gambler’s Fallacy0.0%This article: 0.0%Edith Olmsted: 0.1%newrepublic.com: 0.1%Middle Ground0.0%This article: 3.5%Edith Olmsted: 0.4%newrepublic.com: 0.3%Personal Incredulity3.5%This article: 0.0%Edith Olmsted: 0.5%newrepublic.com: 0.2%Special Pleading0.0%This article: 0.0%Edith Olmsted: 0.1%newrepublic.com: 0.3%Genetic Fallacy0.0%This article: 10.4%Edith Olmsted: 4.1%newrepublic.com: 2.3%Unattributed Quote10.4%This article: 0.0%Edith Olmsted: 1.5%newrepublic.com: 1.6%Quote-first Misdirection0.0%This article: 4.1%Edith Olmsted: 25.6%newrepublic.com: 15.5%Biased Writer Voice4.1%This article: 0.0%Edith Olmsted: 1.1%newrepublic.com: 2.4%Indoctrination0.0%This article: 0.0%Edith Olmsted: 11.9%newrepublic.com: 7.2%Politically Left Leaning Bias0.0%This article: 0.0%Edith Olmsted: 1.0%newrepublic.com: 0.6%Politically Right Leaning Bias0.0%This article: 0.0%Edith Olmsted: 0.0%newrepublic.com: 0.3%Attempt to Sell a Product or S…0.0%

541 words analyzed.

Speakers

3speakers58%attributed speech227writer words
Voice mapSelect a segment to jump to its words
Writer's voice • 9 words • 0.0% coverageWriter's voice • 31 words • 0.0% coverageWriter's voice • 31 words • 0.0% coverageTom Fahy • 22 words • 100.0% coverageWriter's voice • 24 words • 0.0% coverageWriter's voice • 28 words • 0.0% coverageWriter's voice • 23 words • 100.0% coverageAlan Gerard • 37 words • 0.0% coverageAlan Gerard • 19 words • 0.0% coverageAlan Gerard • 39 words • 0.0% coverageRick Thoman • 30 words • 0.0% coverageRick Thoman • 16 words • 0.0% coverageRick Thoman • 10 words • 0.0% coverageRick Thoman • 35 words • 0.0% coverageWriter's voice • 7 words • 0.0% coverageWriter's voice • 33 words • 100.0% coverageAlan Gerard • 20 words • 0.0% coverageAlan Gerard • 27 words • 0.0% coverageRick Thoman • 40 words • 0.0% coverageRick Thoman • 19 words • 0.0% coverageWriter's voice • 18 words • 0.0% coverageWriter's voice • 23 words • 0.0% coverage
Selected voice

Rick Thoman

100%flagged-word coverage
150 attributed words48% of attributed speech89% writer coverage
0%12.5%25.0%Unattributed Quote-24.7 ptsWriter: 24.7%Rick Thoman: 0.0%0.0%

Attribution is sentence-level. Pattern percentages are calculated only from words assigned to that voice.

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Analysis

Hover over highlighted words in the article to view the associated bias or fallacy analysis.