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While they’re confident in the accuracy of this year’s predictions, the future looks a lot murkier.

Buoys have it tough.
Built to endure some of the harshest conditions on the planet, the instruments are thrashed by ocean waves, buffeted by high winds, corroded by sea salt, and scorched by the sun’s ultraviolet rays. Their measurements on everything from solar radiation to seawater salinity, barometric pressure, and the still-alarmingly-warm water temperatures in the Gulf of Mexico (by any other name) provide crucial information for the experts making forecasts for weather patterns like the El Niño and the Southern Oscillation variations, which have impacts felt around the world. The buoys also provide life-or-death data used to make informed forecasts for the 60 million Americans living in the Atlantic and Gulf regions — i.e. those most vulnerable to hurricanes.
The job of maintaining the government’s more than 200 moored buoys across the Pacific and Atlantic basins falls to the National Oceanic and Atmospheric Administration’s National Data Buoy Center, based out of southern Mississippi. Like many teams at NOAA, the NDBC consists of a small group of oceanographers, computer scientists, engineers, and meteorologists that play an outsized role in shaping our understanding of what’s happening in the ocean. Also like many teams at NOAA, it has been hit hard by the Trump administration’s sweeping layoffs and buyouts. Of its 34 full-time employees, the NDBC had already lost three as of March 1, while the fate of another 120 contract employees — who help keep the buoys maintained and operational — is in limbo. “Hopefully it won’t get to the point where [the system] kind of falls apart,” one engineer who retired this year worried to The Columbian.
Against this bleak backdrop, independent forecasters have begun to release their predictions for the 2025 hurricane season. Groups like Colorado State University’s Department of Atmospheric Sciences and the media company AccuWeather, which publish highly regarded outlooks every April, rely almost entirely on data from NOAA’s buoys, satellites, and weather stations.
“NOAA is critical,” Levi Silvers, a research scientist and a co-author of CSU’s 2025 outlook, told me. “If you look back 20 or 30 years ago, we didn’t have nearly as many buoys out there. That meant forecasters “couldn’t really tell how deep the warm or cool layers of the Pacific went,” which led to more unpleasant surprises, he said. “We can see that now because of the buoys from NOAA.”
This year, government-provided data informed CSU’s forecast of 17 named storms in 2025, as well as AccuWeather’s prediction of 13 to 18 named storms. Both groups’ forecasts are slightly lower than their 2024 predictions, although Silvers stressed that the dip shouldn’t be the emphasis. “It’s still above normal,” he said, noting that the average number of named storms between 1991 and 2020 was fewer than 15. “I hope that people don’t get the impression that it’s a below-average season because it’s less than last year.”
Paul Pastelok, AccuWeather’s head of long-range forecasting, likewise told me that while water temperatures aren’t as warm in the Atlantic basin’s main development area as last year, they’re still pretty close. Hurricanes primarily draw their power from heat at the sea’s surface, so early season temperature readings can tip off forecasters to increased storm activity. There is no reason to write off the possibility of another storm as powerful as Hurricane Milton making U.S. landfall this year. (AccuWeather predicts three to five Category 3-strength or higher storms this year, while CSU expects four.) The potential for rapid intensification — where a storm significantly increases in wind speed over a period of 24 hours or less, as we saw with last year’s Hurricane Beryl — also remains.
Pastelok was particularly alarmed by the numbers NOAA has reported in the Gulf, which could mean a lot of “homegrown activity.” “In the past, we’ve seen these long-track systems coming off the African coast that can produce some big storms — Category 4 or 5 — but we have time to react and see where they’re going to go,” Pastelok said. “It’s the ones that develop closer to the county that could catch people off guard.”
Pastelok added that AccuWeather hasn’t had any issues receiving NOAA data, and he isn’t worried yet about continuing to obtain quality data to tweak their predictions, including potentially accounting for a late-season La Niña, a pattern typically conducive to more hurricanes. Silvers sounded less sure: “I don’t think people realize how much work it takes to get information from a satellite or a buoy to make a picture in your computer,” he said. “It has to be collected, and there’s a huge process of quality control, where we have to make sure the data is good.” NOAA has — or at least had — many employees doing the “grueling, tedious, computer-science-type work” to provide good data to hurricane forecasters.
NOAA’s National Hurricane Center also provides its own forecast of named storms, which is usually released just before the June 1 start of the season. In response to my emailed questions about how the administration’s layoffs may affect NHC’s forecasting capabilities, a communications officer reiterated the agency’s policy of not discussing internal personnel matters or engaging in speculative interviews. She added, however, that NOAA “remains dedicated to its mission, providing timely information, research, and resources that serve the American public and ensure our nation’s environmental and economic resilience.”
Other branches of NOAA responsible for observations and communications related to hurricanes also appear to be in trouble. Mission-critical flight directors for the Hurricane Hunters, who measure the intensity of developing storms by flying through the eyewall, have been among those laid off by the agency, reducing NOAA’s aviation capacity by 25%. The National Weather Service has also indefinitely suspended its extreme weather alerts in languages other than English — including Spanish, which is spoken at home by 20% of Floridians and nearly 30% of Texans. And while NOAA noted to me that its Weather Prediction Center, National Water Center, and National Weather Service offices around the country issued a “rare coordinated NOAA news release” ahead of last year’s devastating Hurricane Helene, that kind of inter-department cooperation and messaging gets harder as the contact information of former point-people goes dark and one-time colleagues are no longer around to answer a call.
For now, at least, the 2025 hurricane predictions remain high quality and trustworthy; Pastelok sounded confident of the range AccuWeather had landed on, and Silvers also sounded assured in the numbers CSU put out. But buoys break — the NDBC’s annual “maintenance mission” alone lasts eight months, not to mention its constant backlog of as-needed repairs — and other ocean monitoring programs are also at risk of losing their funding.
At the end of the day, a forecast is only as good as the data fed into it. Hurricanes are highly complicated systems, and every degree of water temperature, shift in wind shear, and variation in tropical waves can change the character of a storm. If NOAA’s data and quality control degrades in the coming months or even years, it’s not an exaggeration to say that the fallout could be catastrophic.
And as hurricane forecasters like to say: All it takes is one storm.
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The data center boom is everywhere you look in U.S. economic and emissions data.
This is an edition of Heatmap Daily, an evening review of the day’s news written by our executive editor. Sign up for it here.
It isn’t exactly a new thought, but I’ve been struck recently by how many trends in America’s economic and environmental data are fundamentally about the data center boom and the return of electricity demand:
First, the Energy Information Administration reported this week that U.S. emissions grew by more than 2% last year, driven by surging electricity demand and an increase in coal-fired generation.What caused that higher power demand? New factories and data centers — as well as record summertime cooling demand.
Second, many of the new factories driving that higher power demand are themselves producing goods that are … let’s say … data center-adjacent. There are the enormous new semiconductor fabs, of course. But Ford and General Motors have also set up new production lines (or repurposed old ones) to manufacture grid-scale batteries to meet power demand.
Third, take a look at the recent U.S. spending on private non-residential construction — in other words, everything American companies are building that is not houses, condos, or apartments.
The construction industry’s spent almost $60 billion on data centers over the past year, which is more than it spent on all other office buildings combined (and more than it spent building warehouses, too). Just a handful of categories — data centers, power plants, electricity infrastructure, and certain kinds of electronics manufacturing — now make up a third of all U.S. private non-residential construction investment. They’ve never made up such a large share of construction spending since data collection began in 2014.
As The New York Times recently noted, the American economy is unusually dependent on the American stock market right now — and the stock market is unusually dependent on artificial intelligence. This week, investors started to balk at the enormous spending hyperscalers are planning to keep building out the AI boom; Alphabet’s shares dropped 8% this week after it boosted its planned 2026 capital expenditure and signaled 2027 will be even bigger. If the data center boom started to slow down in earnest, then more than just that budget will change.
Speaking of which, my colleague Emily Pontecorvo wrote earlier this week about how many businesses are struggling to even estimate their carbon emissions from artificial intelligence. The carbon accounting startup Watershed recently unveiled a new formula to help companies get a sense of their AI-related emissions.
But even that formula is still limited by the amount of data hyperscalers publish — and they don’t publish that much. Google, for instance, is the only AI company that has (laudably) provided estimates of its emissions on a per-prompt basis. Yet no company has published its per-token emissions, or how emissions sync up with particular models or regions.
So Emily asked Google: Why aren’t you — or any other model provider — disclosing this kind of data yet?
The tech company didn’t get back to us until after we’d published Emily’s story. But its response was interesting enough that I wanted to quote some of it here.
The problem is “industry consensus,” Cooper Elsworth, a Google spokesperson, told us. “There is currently very little consensus on how to comprehensively and fairly measure the serving environmental impact of generative AI (such as text generation),” he wrote. “Without standardized, ‘apples-to-apples’ frameworks, it is difficult to compare different providers accurately.”
That’s partly because energy use — and emissions data — can vary from site to site and depend on “custom-built hardware, software compilers, and advanced inference techniques.” And he claimed Google doesn’t always have the measurement hardware in place to provide such specific estimates: “Providing precise, repeatable data requires highly advanced measurement infrastructure,” he said. “For example, software-based energy monitoring tools often suffer from sampling biases. For our study, we had to step away from top-down averages and directly measure actual energy at the physical power supply unit (PSU) level across our deployed fleet. Not all providers have the telemetry or data sets required to benchmark their operations at this level of granularity.”
Read Emily’s story to understand the other reasons why estimating — or even “guesstimating” — AI-related carbon emissions is so challenging.
A conversation with Emma Uridge of the Kansas Health Institute.
This week’s conversation is with Emma Uridge, analyst with the Kansas Health Institute. Uridge spent copious hours analyzing state and local laws on data center development to best understand how policymakers are responding to the potential environmental public health impacts of large AI infrastructure, including power and water. The report, which came out this week, also goes in depth into those health impacts. I reached out to her to discuss what she sees as must-watch territory for our readers on this emerging policy arena.
Our conversation was lightly edited for clarity.
What is actually being done on policy when it comes to data centers — beyond moratoria of course?
So first I’d like to just talk about the point of moratoria. It’s helpful to talk about how these policies emerge in the first place. One area where moratoria are helpful is when a data center is proposed but the county has no approach for how they’d like to potentially regulate them. That’s temporary, most of the time. It lets local governments conduct research on the various impacts and also negotiate community benefits, ones that can mitigate any potential negative impacts — like Lancaster Pennsylvania, which instituted a community benefit agreement that maximized the potential benefits of development while mitigating what large data centers can do. That agreement looked at capping municipal water use at 20,000 gallons per day and requiring 100% clean energy. It had financial penalties for non-compliance. The company also committed $20 million to their local economic development and clean energy fund. There are ways to negotiate with developers.
We also see amendments to existing zoning. Data center proposals are increasingly popping up in rural areas, many of which are unzoned, so there’s no way a county can negotiate unless there’s a moratorium in place.
Other policy solutions include different performance standards or requiring on-site renewable energy, like what Jefferson County, Missouri, looked at. Also setback requirements, mandatory noise buffers, ending by-right zoning.
Where are local governments getting ideas for regulating data centers?
A lot of the technical information comes from developers. That can in cases be seen as a biased source of information. I wouldn’t say there’s a dedicated group providing assistance to local governments when a project is proposed — which is a similar story to wind industry development, where we have only a handful of consultants who provide technical advice. It can be really helpful to get a multi-disciplinary approach to hearing information. It can be helpful to have the utility commission, public health folks, those in academia, as well as the developer.
As of right now, especially in rural areas, local governments have a hard task of balancing pushback while getting the most accurate, evidence-based, neutral information to make decisions. That balance can be contentious.
What is the federal government doing on data center policy? How is the Trump administration approaching it?
A few things there. In the early days, the drive was for AI expansion and to be competitive with foreign adversaries. Now due to the amount of public pushback in red and blue localities and a more cautious approach.
I’m not seeing a lot of actual policy movement at this time.
I know the EPA is looking at the chemicals used in cooling data centers because when that water is cycled through the system, some of it is discharged into the water system, so they’re looking at the Toxic Substances and Control Act for monitoring that.
How much of an impact does this minimal federal role have on industry behavior?
Y’know, this isn’t specific to data centers. This is true for all kinds of large-scale development: there’s a need to require some sort of federal monitoring and regulation.
That’s where I see an emerging role for public health. At the federal level, there could be policy movement towards requiring some sort of environmental monitoring at data centers to make sure they’re operating responsibility. Looking at specific water use relative to water availability and what happens when there’s a time of severe, persistent drought. With air quality too — we’ve seen areas where the grid isn’t as reliable so their diesel generators are kicking on more and affecting air quality for residents.
We’re just not seeing all of that right now. We need corporate disclosure.
What do you see as the most important public health impacts from data center development?
It varies by localities. The most discussed obviously is water usage. One thing I’d note about my conversations with folks enthusiastic around emerging tech is, there are still questions that need to be asked about the capacity of localities to support a data center. Like a small town in Kansas may only be using 40% of their water for their utility needs. If a data center came online, how much of that water goes to the data center?
One area underexplored within the public health discipline is energy poverty and energy security. The ability of a household to meet the needs of everything energy provides in our lives. It’s known we have an aging electric grid but we’re not talking enough about large-scale blackouts when the grid is not sufficient to support some of these new data centers.
Plus more of the week’s big development fights.
1. Laramie County, Wyoming — Meta is fighting the fine it received in the Cheyenne data center water pollution controversy, and the conflict between the tech giant and the city’s small board of public utilities is continuing to spill out into the public.
2. Niagara County, New York — This county just rejected a solar project’s highway work permits in a show of retaliation against the state’s Office of Renewable Energy Siting.
3. Barron County, Wisconsin — The anti-solar protest is the new campaign stop in deep red Wisconsin.
4. Chesapeake, Virginia — A large battery storage project on the Virginia coastline is on the rocks amidst rampant local opposition.
5. Lewis County, West Virginia — West Virginia is now a key battleground in the fight over transmission, as a line spanning all of West Virginia and Maryland — and cutting through Data Center Alley in Virginia — causes compounding consternation.