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Skiers, snowboarders, and cross-country athletes are in mourning for snow.

On January 15, as the first major winter storm of the season screeched across the U.S., Minneapolis’ Theodore Wirth Regional Park remained cold, hard, and — most stubbornly — brown. “We continue to be denied any measurable amount of snow,” read the park’s trail report for the day. “Frozen dandruff-covered dirt is our destiny for the time being.”
In a few weeks, over Presidents Day weekend, the park is scheduled to host the United States’ first cross country skiing World Cup in more than 20 years. For an event like that, “dandruff-covered dirt” simply will not cut it. “We’re really excited to have a great event there with tons of friends and family,” Gus Schumacher, a 2022 Winter Olympian in skiathlon, told me. While he still has hope, the Twin Cities’ snow deficit remains around 18 inches for the season. “We have to cross our fingers for some winter in the next month,” he said.
For the 30 million Americans who enjoy snow sports every year, this sort of finger-crossing has become as much of a pre-season ritual as tightening bindings and waxing skis. While scientists have long taken note of dwindling snowpack — the Fifth National Climate Assessment, released last year, specifically cited winter recreation as a pending cultural and economic victim of climate change — data had only shakily linked snow level to human-driven warming until recently. This month, a study published in Nature confirmed that it’s not all in our heads: Some parts of the U.S. are losing 10% to 20% of their snowpack per decade because of anthropogenic climate change.
Perhaps even more concerning, the study’s authors found that snow loss has a tipping point: Once the average winter temperature in a region warms beyond 17 degrees Fahrenheit (-8 degrees Celsius), snow loss rapidly accelerates, even with small temperature rises.
In spite of headlines about arctic blasts and photos of buried football fields, snow levels in many parts of the country have remained worryingly low at the midpoint of this year’s meteorological winter — and temperatures, on average, remain high. In early January, most ski areas in the U.S. were only operating half of their lifts, “which is unusual for this time of year,” Chance Keso, a senior news producer for On the Snow, which tracks ski conditions, told me. “Typically,” he explained, “we would see most resorts almost all completely open by this time of year.”
The recent storm systems have helped somewhat, Keso said — Alyeska, a ski area in Alaska, “passed the 400 inches mark a few weeks ago.” But even Buffalo, which received record snow in January, is tracking behind average when the whole season is considered. In California, where the ski industry is a $1.6 billion business, snowpack is only 57% of normal.
Likewise, meteorologist Sven Sundgaard wrote for Minneapolis’ Bring Me the News that this winter has been “pretty weak” in Minnesota. It has been cold, no doubt, and yet “nowhere in the state reached 25 [degrees Fahrenheit] below zero, which should EASILY happen in a January cold snap in northern Minnesota, even in our much warmer climate,” he said. (This week, temperatures are expected to be 10 to 15 degrees above normal across the state.) On the Snow reported that, as of Monday, “snowpack levels across Minnesota are currently 73% of normal.”
Counterintuitive as it may be, researchers expect climate change to bring more snow to certain places, as extremely cold parts of the world warm to more snow-friendly temperatures and increased precipitation from a warmer atmosphere results in more flurries. Parts of Siberia and the northern Great Plains appear to be experiencing a deepening snowpack of over 20% per decade, Justin Mankin and Alexander Gottlieb, the co-authors of the Nature paper, found in their research. But just because snow loss hasn’t hit an area yet doesn’t mean it won’t soon; “basins that are hovering right at the edge of that cliff, for whom major snow losses have not yet emerged, are about to see the snow losses emerge,” Mankin said.
Despite the worries about Minnesota’s upcoming World Cup, Susanna Sieff — the sustainability director for the Switzerland-based International Ski and Snowboard Federation (known by its French initials, FIS) — told me that event cancellations for the six Olympic snow sport disciplines this season have so far “been on par with previous seasons.” A spate of foiled World Cups in Zermatt, Italy, Beaver Creek, Colorado, and the French Alps in late 2023, she said, was “due to inclement weather and not lack of snowfall.”
Still, Sieff admitted that “for those that needed a wake-up call, the last few years have certainly provided it.” 2022 was especially bad for competitive ski and snowboarding — the organization canceled seven of its eight early-season World Cups for lack of snow. This month, FIS released an updated sustainability action plan that runs through the 2026 season and includes a particular focus on mitigation, environmental justice, and responsible stewardship. (Protect Our Winters, an environmental advocacy group that put me in touch with Schumacher, the ski athlete who serves as one of their ambassadors, has pressured FIS to be more transparent given the existential crisis facing competitive snow sports. My father is a longtime FIS event volunteer.)
Resort operators are increasingly using machine-made snow as a fall-back plan — as Schumacher told me, in cross-country, “we ski on warm, manmade snow far more than was the case 10 years ago.” It’s also common for XC events to move to alternate venues where snow can be stretched further. For example, Lillehammer, Norway has hosted a World Cup race in nine of the past 10 years. But “since I came on the World Cup in 2020, we haven’t been able to use the marquee trails built for the 1994 Olympics,” Schumacher said.
Even this “fake” snow is imperiled. “Snowmaking is not a climate solution,” the National Ski Areas Association, an industry group, has made clear. “It is an operational tool.”
It’s also expensive. Snowmaking can eat up to 15% of a ski area’s operating budget, draining the pockets of small and independent resorts. The consequence is yet another illustration of how climate change hits “the most vulnerable system and the most vulnerable people in that system,” Mankin said. “The ski industry is a really clear example of where you’re going to see consolidation onto better resourced, higher, more exclusive mountains that have the ability to produce human-made snow — and which are more difficult for the general population to access.”
Since the 1970s, ski areas in the U.S. have dwindled from roughly 1,000 locations to only about 470, according to SnowBrains, a ski and snowboard publication. It’s a trend climate change is helping to accelerate. That, of course, means fewer areas for athletes to compete and practice, as well as fewer local hills and trails for would-be athletes to fall in love with the sport.
For those in the snow sports world, this is nothing short of heartbreaking. The average American already doesn’t watch snow sports and “shouldn’t really care” whether cross-country or downhill skiing competitions survive, Schumacher told me. But the consequences are bigger than just competitive and recreational snow sports having shorter seasons of poorer quality or becoming more exclusive. A lack of snow is also about critical watersheds that are strained when snow doesn’t fall in the mountains, leaving ecosystems damaged and agriculture unirrigated. Heck, it’s about hardy, stoic Minnesotans losing what it means to be hardy, stoic Minnesotans. “What they should care about,” Schumacher said of his fellow Americans, “is the effects of climate change that come after the death of snow sport as we know it.”
Mankin told me something similar. “What happens in winter,” he warned, “doesn’t stay in winter.”
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What 700 math problems say about the AI economy’s biggest open question
This is Heatmap Daily, an evening news digest written by our executive editor. Subscribe here.
Happy Monday and welcome back.
It’s been a big weekend: I’m fairly certain Saturday Night Live mentioned Heatmap’s data center polling in one of its Weekend Update segments over the weekend. Watch here.
There are 22 days to the midterm elections here in the United States. We’ll soon enter that pre-election wormhole where only national politics can break through. So today I wanted to look at a story that might, on its face, seem like it has nothing to do with climate or energy. And warning: It’s a little bit of a weird one.
Last week, OpenAI released what it described as the solution to more than 700 open problems in mathematics. Many of the problems, such as the Quasi-Riemann hypothesis, had gone unsolved for decades. Some of the solutions came with proofs written in the programming language Lean.
The release made a stir in part because OpenAI had reached the solutions by using an internal model — that is, a version of ChatGPT not yet open to the general public. In a statement, the Association for Human Mathematics lambasted OpenAI for using an internal model to do research, violating what it described as a precept of AI-driven math research. (I’ve since seen speculation that OpenAI may not have even meant to solve the problems, but gave them to the internal model as a test … and then got the answers.) It’s also not clear whether all of OpenAI’s 700 solutions are correct — in many cases the proofs are so intricate that mathematicians are still wrapping their heads around them.
“There are some sad stories related to their users getting scooped [and] conflicts of interest,” Levent Alpöge, a mathematician at Anthropic, posted on X. “It’s obviously the most significant moment in mathematical history.”
On Friday night, the UCLA mathematician Terence Tao gave a pre-planned lecture at Caltech about what he called “Math 2.0”; it considered the revolution the field had seemingly undergone in the previous few days. (He posted the slides to his blog over the weekend, and I’m using them to summarize his talk here.) For most of math’s history, he said, the field operated under “proof scarcity,” in which finding a solution to an open math problem and confirming it as true was “difficult and rare,” requiring “significant human expertise.”
But AI, it has turned out, is well suited to solving math problems. This is partly because math, like the large language models themselves, is entirely conceptual, so confirming a proof as true requires no recourse to the physical. But it’s also because math’s solutions are “objectively verifiable”: “There is broad consensus on what constitutes a correct and complete proof of a given problem,” and thanks to the existence of proof programming languages like Lean, they can even be checked by computer.
The end result is that math is now entering a world of “proof abundance,” he said.
That is, perhaps surprisingly, a problem for math’s practitioners, and it will mandate a new intellectual regime for the discipline. Mathematicians have often used open problems as “lighthouses,” Tao wrote, “not destinations to be reached … but useful guides to explore the mathematical landscape.” Mathematicians often learn more in the solving than in the solution, in other words. But if mathematicians can now generate shortcuts to math problems without knowing how they got there, or even how the problem works, then actual human mathematical understanding will suffer. (One way to understand this is that mathematicians are now dealing with the same problem that math teachers have faced since the invention of the pocket calculator: How do you confirm students actually understand the material? Except the world’s most elite mathematicians themselves are the students in question.)
This disconnect can pose its own AI alignment problems, Tao said, analogizing math to pharmaceuticals. Suppose an advanced AI found what appears to be a cure for cancer that can pass a stage 3 clinical trial: “After a large amount of compute, it produces a cocktail of previously unknown chemicals which it claims, when mixed and injected into a patient, will kill all their cancer cells,” he said. It even generates a programmatic proof of the cocktail’s effectiveness.
“Before injecting this cocktail into your bloodstream,” he asked, “would you find it reassuring to know that there is at least one human cancer expert who understands — even partially — the mechanism behind this cure?” If not, you can see mathematicians’ problem, confronted by a surfeit of proofs that seem to work, but nobody who can explain how or why they do.
Now, Tao’s analogy is somewhat peculiar because something like this actually does happen all the time in medicine: Doctors still don’t fully understand how many drugs work, including acetaminophen, SSRIs, and lithium. (That said, those compounds were identified by trial and error, not by a mechanical superintelligence.) But the broader situation that Tao is painting — as well as the crisis posed by OpenAI’s 700 proofs — get at a significant question with economic importance far beyond just math: Will AI solve the economy’s secular attention shortage or worsen it?
This question has greater import than it may seem — but let me qualify what I mean by “attention shortage.” Writing in 1971, the economist Herber Simon observed the sudden superabundance of information that had exploded in every economic domain. There were more facts, data, news articles, and opportunities than any individual or organization knew what to do with. He pointed out that this newfound “wealth” of information implied an insufficiency of something else: attention.
“What information consumes is rather obvious: it consumes the attention of its recipients,” he wrote in Designing Organizations for an Information-Rich World. “Hence a wealth of information creates a poverty of attention and a need to allocate that attention efficiently among the overabundance of information sources that might consume it.”
He wrote this, of course, well before the advent of internet, smartphones, sensors, or networked cameras — all of which have worsened the problem. But in the ensuing half century, the economy has learned to deal (or at least intermittently manage) this secular scarcity of attention. Much of what we now call knowledge work is devoted to filtering, siphoning, processing, and otherwise attending to the information superabundance.
AI is, in theory, supposed to help address this same set of problems. AI is commodified attention — or, at least, that is its promise. (The most important machine learning paper of the past decade, after all, is entitled “Attention Is All You Need.”) Many AI products, such as Meta’s Muse, now want you to believe that by ceding control of your email, your calendar, your restaurant reservations, and your digital life to AI, you will gain an attentional edge. The AI will do the grunt-work of attending to boring things for you, and you will feel less overwhelmed. If this vision comes true, the economy’s mismatch of information and attention will prove to be a short-lived historical blip.
But the past week of math news and Tao’s “Math 2.0” regime suggest a different scenario is more likely, at least in the immediate near term. By allowing far faster and more automated information production, AI will create a new, more vicious, and even more abstract form of information overload. Every profession and intellectual discipline will be overwhelmed with new papers, ideas, observations, proofs, or choices. Yet the human understanding required to convert this new information into useful action will become even more scarce. In such a world, AI will not solve the economy’s attention shortage, but worsen it.
I’m not sure which world would be worse for humanity, to be candid. One world suggests the eventual automation of all human effort. But in Tao’s world, many of us might still have jobs — they will just involve even more filtering, sorting, and processing of an ever-deepening pile of automated idea generation than we do today.
And what is the connection to climate and energy? One easy connection might be to the permitting process: If you think a new transit line (at the local level) or transmission line (at the state or federal level) could be overwhelmed with procedural concerns 10 years ago, wait until you see what happens when information itself can be mechanically produced. But that is only one example of a more general problem. Soon, if not already, any process of providing input to an important policy question — on energy, decarbonization, or anything else — will be overwhelmed with facially high-quality analysis. It will be left to policy officials and elected leaders to sort through it.
This past weekend’s storms caused flooding and property damage up and down the coast — and it’s going to get worse.
California has around 3,400 miles of shoreline, ranging from the wild, foggy beaches of the North Coast to the sunbather-studded sands of Orange and San Diego counties. That’s a whole lot of border to share with the Pacific Ocean, especially when the water is as hot and tempestuous a neighbor as it is right now.
Just ask the city of Long Beach, which this weekend was on the receiving end of some Super El Niño mischief. Swells from the storm briefly dubbed Hurricane Rachel “annihilated” beachfront mansions and flooded city streets, causing pieces of the local boardwalk to “shred away.” “It’s never happened like this before,” one resident of 64 years told the New York Post.
But while things might look bad in California at the moment, they can still get much worse. One disaster modeler recently estimated the state could see as much as $3 billion in flooding and mudslide-related losses alone this winter — not to mention coastal erosion, king tides, and storm swell. Governor Gavin Newsom declared a state of emergency at the end of September, while many cities, including San Diego, have declared their own local emergencies.
El Niño will likely peak in December, meaning that towns and cities across the state have just a few remaining weeks to finalize projects, whether that means improving drainage in landslide-prone environments such as Rancho Palos Verdes or distributing NOAA weather radios in areas likely to lose power, as emergency managers are in Santa Cruz. The approaching winter storms, combined with El Niño, represent “a humbling reminder of the ongoing effects of climate change and the importance of emergency preparedness,” Laath Martin, the public affairs lead for the city of Long Beach, wrote to me in an email.
El Niño is a cyclical phenomenon, occurring when temperatures in a particular stretch of the Pacific Ocean rise half-a-degree Celsius above the average of the preceding 30 years. But there are signs these natural variations are happening less predictably because of climate change, and we know for sure that a warmer atmosphere makes the baseline for its impacts worse: king tides, Kelvin waves, and storm surge piggyback on top of rising sea levels to result in more severe coastal flooding and erosion. A warmer atmosphere also holds more water, which means more rain — perhaps 200% above normal — which, in turn, results in flooding and mudslides further inland, as well.
“Based on what I am seeing now, I am officially concerned,” Daniel Swain, a climate scientist at the University of California Agriculture and Natural Resources, said last week after reviewing the latest outlook. There’s a reason this year’s El Niño is being called a Godzilla.
In general, the weather pattern causes the jet stream to shift south in the winter, bringing wetter and snowier conditions to the lower U.S. while the northern part of the country stays drier and mild. (It’s also responsible for a weaker Atlantic hurricane season, as we’ve already seen this year.) In addition to El Niño-driven Kelvin waves, warm bulges of water that raise the sea level on the coast by as much as 18 inches, the state of California — and particularly southern California — sits directly in a storm track that will deliver “atmospheric rivers” of heavy rain to a region prone to landslides and flash floods.
In many parts of the state, that rain will test the best-made plans in addition to plans deferred. In Los Angeles, the Department of Sanitation and Environment, or LASAN, has told the City Council it has concerns about the ability of the aging wastewater pipes and plants to handle heavy rainfall associated with a supercharged El Niño. In San Diego, which requires some $3.3 billion to upgrade what is in some places a century-old wastewater system, emergency managers are preparing to work with what they have by clearing debris and brush that could back up in the drains, CalMatters reports. In both cases, the time required for systemwide repairs far exceeds the time remaining before the winter’s supercharged atmospheric rivers are due to arrive. (Rezende told me inland flooding affects more businesses and residents in San Diego than coastal flooding, since the population in the city is set further back from the coastline.)
The city of Roseville, northeast of Sacramento, by contrast, is leaning on decades of flood planning to get through the season. After a series of back-to-back storms in 1986 that killed 13 people and caused $400 million in damage, the city and FEMA invested $39 million to upgrade Roseville’s infrastructure, including widening streams and adding levees and stormwater bypass channels. With more accurate floodplain modeling that has “helped keep new construction at higher elevations,” Helen Dyda, the city manager’s public information officer told me that “less than 7% of the city is within a floodplain” today. Dyda added that the city prepares for winter storms every year — it has some 160 miles of creek shoreline, after all — but that the El Niño-specific preparations are, as a result, more similar to routine maintenance: “clearing more dense vegetation and fallen trees from key creek areas.”
Long Beach is caught somewhere in the middle. After swells from Hurricanes Marie and Polo hammered the city in September, Long Beach hastily developed a seven-point plan to strengthen its peninsula in the near and long term. It will also begin a $11.4 million dredging project this fall that will place 415,000 cubic yards of sand on the beach as a buffer zone. “While this effort will achieve a much-desired result, it will not stop the ocean from pulling sand from the peninsula with every wave, especially during the significant weather systems Long Beach continues to experience,” Martin, the city’s public affairs lead, wrote to me. “Back-passing will need to continue to return sand back to the peninsula each day until more permanent, long-term man-made and environmental solutions can be identified, permitted and implemented.”
In certain cities, preparations for the peak of El Niño overlap with ongoing repairs from the last bad storm season. In Santa Cruz County, the 2016 El Niño caused an estimated $9 million in damage, while many in the community of Pajaro are still recovering from the flood damage caused by a series of severe atmospheric rivers in 2023. “We have a list of hazards that the city is vulnerable to, and we plan for all of them not individually, but all together,” Meredith Albert, Santa Cruz’s emergency management manager, told me. She added that many of the city’s preparedness activities and El Niño initiatives, like urging the community to be prepared to spend 72 hours unsupported, overlap with other disasters it works year-round to prepare for, like earthquakes, landslides, and wildfires.
“El Niño turns up the volume a little bit, but it doesn’t necessarily change our hazard landscape,” is how Albert put it to me.
Santa Cruz has not declared a local state of emergency, and Albert told me they won’t until they “run out of resources.” Other cities, like San Diego, have declared one preemptively. “In the past, you’d have to go through a longer review if you wanted to make some headway on projects, and sometimes that would take many weeks or many months of permitting,” Rezende said. “With a state of emergency, we streamline that process and get projects in the queue.”
Both Rezende and Albert told me the governor's statewide emergency declaration mostly helps state agencies position themselves for a faster response or has implications for higher-level permitting processes. (In Carlsbad, for example, which has seven miles of badly eroding beach, just one mile is controlled by the city; the other six are managed by the State Parks.) The state has also teamed up with ICEYE, a satellite imaging company, to receive information about flooding even in the dark or through rain clouds.
No state of emergency, though, can make it so a city can replace a century-old sewer system by Christmas or reengineer a beach by the time January’s storms begin to make landfall. But if a Godzilla analogy fits the onslaught of a super El Niño, it also offers a classic disaster-movie lesson on how to survive it.
Albert’s advice for how to prepare? Ask a neighbor for a cup of sugar. Take their dog for a walk. Build a relationship that could prevent a tragedy. “We know that our city will be cut off for at least a couple of days,” she told me of a hypothetical major disaster, referring back to Santa Cruz’s experience after the 1989 Loma Prieta earthquake, which cut off the city’s power, communication, and supply lines. “And we also know that we can’t build those relationships during the disaster. We’re trying to build them before.”
The city is doing a lot to prepare for the storm, she said. “But the question is also, what are all of us doing?” Albert went on. “You know better than I do, at the city level, who’s not going to receive that alert,” whether that be an elderly or unhoused neighbor or a nonnative English speaker who might not receive or understand emergency communications.
“Check in on a neighbor” is easier said than done — active engagement and connection to one’s community is trending downward in most parts of the U.S. But the people and places that bounce back from disaster and tragedy are almost uniformly the ones that look after each other. Borrowing a cup of sugar, to this introvert, sounds like a nightmare. But there’s never been a better time than a Godzilla El Niño to bake a poorly resourced cake.
Heatmap News is looking for an ambitious, energetic senior editor to join our growing newsroom.
The senior editor will report to the deputy editor of the website and will be tasked with assisting in running all aspects of our coverage. This individual will be the primary editor on many of the site’s stories, including breaking news, features, and long-term projects, on topics ranging from permitting reform to decarbonized fuels to greenhouse gas accounting to the electric vehicle market. This person will also play a role in overseeing and furthering our cross-platform efforts such as newsletters, events, and podcasts. Additional duties will include managing and maintaining the site’s social media presence and digital production on stories, newsletters, and podcasts.
Candidates should be intellectually curious news junkies with a deep interest in climate change and the energy transition. They should have a proven ability to work in a fast-paced digital newsroom, spot great angles, line edit stories, and change hats quickly as needed. They should also be responsible, reliable, and a good colleague.
Candidates should have 5+ years experience editing for a digital publication. A background in climate or energy coverage is an obvious plus, but compelling candidates from other verticals, particularly politics and business, will also be considered. Heatmap is a fully remote workplace, so candidates from all U.S. locales are encouraged to apply.
Above all, candidates should be passionate about Heatmap’s mission and absolutely thrilled about building something from the ground up.
The salary minimum is $100,000 and the maximum is $120,000. Competitive benefits, unlimited paid time off, and a generous equity plan, which gives employees a real stake in the company, are also offered. This position is remote.
Interested candidates should send a brief cover letter and resume to editors@heatmap.news with the subject line ‘Senior Editor Application.’
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