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Twice a day, all across the country, the National Weather Service launches a fleet of latex balloons into the stratosphere to collect what’s known as “upper-air data”—detailed measurements of temperature, humidity, and pressure. Before they pop, the balloons collect information that guides the world’s forecasters, and helps the rest of us figure out how to prepare for the days ahead. Lately, though, the NWS has reportedly been sending up fewer balloons than it once did, eroding meteorologists’ confidence in their own predictions.
These lapses point to a broader phenomenon. Partly as a result of staffing cuts and funding reductions, government-sourced information has been slowly disappearing. Some organizations have halted surveys and tracking projects; others have deleted archives and databases. Taken together, this new reality risks clouding our understanding of the economy, public health, and the environment—all of which could make it harder to assess the state of the country and the world.
The National Oceanic and Atmospheric Administration (NOAA), which houses the National Weather Service, lost about 15 percent of its staffers last year through layoffs and buyouts. Meteorologists told Politico that those cuts have affected the schedule of NWS weather-balloon launches in the western United States, creating “sizable data holes for crafting severe weather forecasts.” CBS News reported that similar reductions in weather-balloon launches have been happening elsewhere across the country, and that meteorologists now have fewer data to work with.
Accurate forecasts are essential in preparing for large-scale disasters; they can even save lives. Alan Gerard, a weather analyst and former NWS meteorologist, emphasized on his Substack earlier this week that although the precise impact of these launch changes remains unclear, “meteorologists’ confidence in the models and their own ability to analyze some situations has been damaged by the lack of upper air data.” (A NOAA spokesperson told me that “the majority of upper air sites are operating on schedule,” that “any sites conducting fewer launches are due to temporary resource or equipment constraints,” and that “NOAA’s weather model performance shows no evidence of overall degradation on any approved launch schedule.”)
The administration’s cost-cutting has also affected some of the global data collection that the U.S. used to fund. When the Trump administration pulled funding for some foreign-assistance programs last year (this is estimated to have resulted in the deaths of hundreds of thousands of people worldwide), the United Nations’ Food and Agriculture Organization ended up cutting more than 100 of its programs. Some were focused on monitoring outbreaks of disease and infestation among animals—and among the pests its investments helped track was a parasitic fly called the New World screwworm, which has been disrupting cattle farming in Central America and Mexico over the past few years. Last month, it crossed into the United States, endangering the country’s already dwindling supply of beef. Monitoring alone may not have stopped the screwworm’s spread—and there is no evidence to suggest that U.S. funding cuts led to the current outbreak—but cataloging these flies’ movements has long been a crucial part of prevention.
In making certain data private or changing collection methodologies on the orders of the president, this administration is effectively punching holes in the public record. Data.gov removed nearly 3,400 data sets during the first month of Donald Trump’s second term, scrubbing information from the Census Bureau, the Office of Justice Programs, the CDC, and more. The CDC tracks pregnancy risk in the U.S. in an effort to prevent infant mortality; staffing reductions have reportedly made that information inaccessible. Since 1995, the USDA has been tracking the number of American households experiencing food insecurity; the Trump administration discontinued a survey of that data in September, claiming in a press release that this information was “politicized” and “costly” to produce, and did “nothing more than fear monger.”
The government’s data are far from infallible (and, as history has shown, can be manipulated). But the cumulative effect of these recent changes is an erosion of public understanding—and potentially of good policy making. The Federal Reserve, for example, bases its interest-rate decisions around the Bureau of Labor Statistics’ jobs data, among other sources. Last year, when the government shutdown delayed the release of that data, then–Fed Chair Jerome Powell likened the experience to “driving in the fog.” It was the first time in 77 years that the BLS failed to release the U.S. unemployment rate. Relying solely on private data, the Fed was forced to cut rates without a comprehensive read of the American labor force.
Earlier this year, when the Trump administration axed an online archive called the CIA World Factbook, which compiled information about countries around the world, my colleague David A. Graham wrote that its demise was yet another component of the White House’s broader war on information. “Democracy,” he explained, “requires voters having access to accurate and shared information so that they can assess the claims that the government makes.” When missing balloons magnify inaccuracies in weather forecasts, they lend credence to the idea that the government’s information may be getting more unreliable—and that, just maybe, we don’t need to keep funding NOAA after all.
In this way, partial information blackouts can generate more and more distrust in American institutions, creating a vacuum where conspiracy theories can thrive. Transparency may not put a full stop to misinformation, but it can be a powerful remedy.
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Rafaela Jinich contributed to this newsletter.
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