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As climate writers, my colleagues and I spend a lot of time telling readers that places are hot. The Arabian Peninsula? It’s hot. The Atlantic Ocean? It’s hot. The southern U.S. and northern Mexico? Hot and getting hotter.
But here’s a little secret: “Hot” doesn’t really mean … anything. The word is, of course, of critical importance when it comes to communicating that global temperatures are the highest they’ve been in 125,000 years because of greenhouse gases in the atmosphere, or for public health officials to anticipate and prevent deaths when the environment reaches the point where human bodies start malfunctioning. But when you hear it’s “100 degrees out,” what does that really tell you?
Beyond that you’re a fellow member of the Fahrenheit cult, the answer is: not a lot. Humans can “probably avoid overheating” in temperatures of 115 degrees — but only if they’re in a dry room with 10 percent relative humidity, wearing “minimal” clothing, and not moving, The New York Times reports. On the other hand, you have a high chance of life-threatening heat stroke when it’s a mere 90 degrees out … if the humidity is at 95%. Then there are all the variables in between: if there’s a breeze, if you’re pregnant, if you’re standing in the shade or the sun, if you’re a child, if you’re running a 10K or if you’re napping on your couch in front of a swamp cooler.
In order to better specify how hot “hot” is, a number of different equations and techniques have been developed around the world. In general, this math takes into account two main variables: temperature (the one we all use, also known as “dry bulb” or “ambient air temperature,” which is typically measured five feet above the ground in the shade) and relative humidity (the percentage of air saturated with water vapor, also known as the ugly cousin of the trendier dew point; notably Canada’s heat index equivalent, the Humidex, is calculated from the dew point rather than the relative humidity).
In events like the already deadly heat dome over the southern United States and northern Mexico this week, you typically hear oohing and ahhing about the “heat index,” which is sometimes also called the “apparent temperature,” “feels like temperature,” “humiture,” or, in AccuWeather-speak, the “RealFeel® temperature.”
But what does that mean and how is it calculated?
The heat index roughly approximates how hot it “actually feels.”
This is different than the given temperature on the thermometer because the amount of humidity in the air affects how efficiently sweat evaporates from our skin and in turn keeps us cool. The more humidity there is, the less efficiently our bodies can cool themselves, and the hotter we feel; in contrast, when the air is dry, it’s easier for our bodies to keep cool. Regrettably, this indeed means that insufferable Arizonans who say “it’s a dry heat!” have a point.
The heat index, then, tells you an estimate of the temperature it would have to be for your body to be similarly stressed in “normal” humidity conditions of around 20%. In New Orleans this week, for example, the temperature on the thermometer isn’t expected to be above 100°F, but because the humidity is so high, the heat toll on the body will be as if it were actually 115°F out in normal humidity.
Importantly, the heat index number is calculated as if you were standing in the shade. If you’re exposed to the sun at all, the “feels like” is, of course, actually higher — potentially as many as 15 degrees higher. Someone standing in the New Orleans sun this week might more realistically feel like they’re in 130-degree heat.

Here’s the catch, though: The heat index is “purely theoretical since the index can’t be measured and is highly subjective,” as meteorologist Chris Robbins explains. The calculations are all made under the assumption that you are a 5’7”, 147-pound healthy white man wearing short sleeves and pants, and walking in the shade at the speed of 3.1 mph while a 6-mph wind gently ruffles your hair.
Wait, what?
I’m glad you asked.
In 1979, a physicist named R. G. Steadman published a two-part paper delightfully titled “The Assessment of Sultriness.” In it, he observed that though many approaches to measuring “sultriness,” or the combined effects of temperature and humidity, can be taken, “it is best assessed in terms of its physiological effect on humans.” He then set out, with obsessive precision, to do so.
Steadman came up with a list of approximately 19 variables that contribute to the overall “feels like” temperature, including the surface area of an average human (who is assumed to be 1.7 meters tall and weigh 67 kilograms); their clothing cover (84%) and those clothes’ resistance to heat transfer (the shirt and pants are assumed to be 20% fiber and 80% air); the person’s core temperature (a healthy 98.6°F) and sweat rate (normal); the effective wind speed (5 knots); the person’s activity level (typical walking speed); and a whole lot more.
Here’s an example of what just one of those many equations looked like:

Needless to say, Steadman’s equations and tables weren’t exactly legible for a normal person — and additionally they made a whole lot of assumptions about who a “normal person” was — but Steadman was clearly onto something. Describing how humidity and temperature affected the human body was, at the very least, interesting and useful. How, then, to make it easier?
In 1990, the National Weather Service’s Lans P. Rothfusz used multiple regression analysis to simplify Steadman’s equations into a single handy formula while at the same time acknowledging that to do so required relying on assumptions about the kind of body that was experiencing the heat and the conditions surrounding him. Rothfusz, for example, used Steadman’s now-outdated calculations for the build of an average American man, who as of 2023 is 5’9” and weighs 198 pounds. This is important because, as math educator Stan Brown notes in a blog post, if you’re heavier than the 147 pounds assumed in the traditional heat index equation, then your “personal heat index” will technically be slightly hotter.
Rothfusz’s new equation looked like this:
Heat index = -42.379 + 2.04901523T + 10.14333127R - 0.22475541TR - 6.83783x10-3T 2 - 5.481717x10-2R 2 + 1.22874x10-3T 2R + 8.5282x10-4TR2 - 1.99x10-6T 2R 2
So much easier, right?
If your eyes didn’t totally glaze over, it actually sort of is — in the equation, T stands for the dry bulb temperature (in degrees Fahrenheit) and R stands for the relative humidity, and all you have to do is plug those puppies into the formula to get your heat index number. Or not: There are lots of online calculators that make doing this math as straightforward as just typing in the two numbers.
Because Rothfusz used multiple regression analysis, the heat index that is regularly cited by the government and media has a margin of error of +/- 1.3°F relative to a slightly more accurate, albeit hypothetical, heat index. Also of note: There are a bunch of different methods of calculating the heat index, but Rothfusz’s is the one used by the NWS and the basis for its extreme heat alerts. The AccuWeather “RealFeel,” meanwhile, has its own variables that it takes into account and that give it slightly different numbers.
Midday Wednesday in New Orleans, for example, when the ambient air temperature was 98°F, the relative humidity was 47%, and the heat index hovered around 108.9°F, AccuWeather recorded a RealFeel of 111°F and a RealFeel Shade of 104°F.
You might also be wondering at this point, as I did, that if Steadman at one time factored out all these variables individually, wouldn’t it be possible to write a simple computer program that is capable of personalizing the “feel like” temperature so they are closer to your own physical specifications? The answer is yes, although as Randy Au writes in his excellent Substack post on the heat index equation, no one has seemingly actually done this yet. Math nerds, your moment is now.
Because we’re Americans, it is important that we use the weirdest possible measurements at all times. This is probably why the heat index is commonly cited by our government, media, and meteorologists when communicating how hot it is outside.
But it gets weirder. Unlike the heat index, though, the “wet-bulb globe temperature” (sometimes abbreviated “WBGT”) is specifically designed to understand “heat-related stress on the human body at work (or play) in direct sunlight,” NWS explains. In a sense, the wet-bulb globe temperature measures what we experience after we’ve been cooled by sweat.

The “bulb” we’re referring to here is the end of a mercury thermometer (not to be confused with a lightbulb or juvenile tulip). Natural wet-bulb temperature (which is slightly different from the WBGT, as I’ll explain in a moment) is measured by wrapping the bottom of a thermometer in a wet cloth and passing air over it. When the air is dry, it is by definition less saturated with water and therefore has more capacity for moisture. That means that under dry conditions, more water from the cloth around the bulb evaporates, which pulls more heat away from the bulb, dropping the temperature. This is the same reason why you feel cold when you get out of a shower or swimming pool. The drier the air, the colder the reading on the wet-bulb thermometer will be compared to the actual air temperature.
Wet bulb temperature - why & when is it used?www.youtube.com
If the air is humid, however, less water is able to evaporate from the wet cloth. When the relative humidity is at 100% — that is, the air is fully saturated with water — then the wet-bulb temperature and the normal dry-bulb temperature will be the same.
Because of this, the wet-bulb temperature is usually lower than the relative air temperature, which makes it a bit confusing when presented without context (a comfortable wet-bulb temperature at rest is around 70°F). Wet-bulb temperatures over just 80, though, can be very dangerous, especially for active people.
The WBGT is, like the heat index, an apparent temperature, or “feels like,” calculation; generally when you see wet-bulb temperatures being referred to, it is actually the WBGT that is being discussed. This is also the measurement that is preferred by the military, athletic organizations, road-race organizers, and the Occupational Safety and Health Administration because it helps you understand how, well, survivable the weather is, especially if you are moving.
Our bodies regulate temperature by sweating to shed heat, but sweat stops working “once the wet-bulb temperature passes 95°F,” explains Popular Science. “That’s because, in order to maintain a normal internal temperature, your skin has to stay at 95°F degrees or below.” Exposure to wet-bulb temperatures over 95°F can be fatal within just six hours. On Wednesday, when I was doing my readings of New Orleans, the wet-bulb temperature was around 88.5°F.
The WBGT is helpful because it takes the natural wet-bulb temperature reading a step further by factoring in considerations not only of temperature and humidity, but also wind speed, sun angle, and solar radiation (basically cloud cover). Calculating the WBGT involves taking a weighted average of the ambient, wet-bulb, and globe temperature readings, which together cover all these variables.
That formula looks like:
Wet-bulb globe temperature = 0.7Tw + 0.2Tg + 0.1Td
Tw is the natural wet-bulb temperature, Tg is the globe thermometer temperature (which measures solar radiation), and Td is the dry bulb temperature. By taking into account the sun angle, cloud cover, and wind, the WBGT gives a more nuanced read of how it feels to be a body outside — but without getting into the weeds with 19 different difficult-to-calculate variables like, ahem, someone we won’t further call out here.
Thankfully, there’s a calculator for the WBGT formula, although don’t bother entering all the info if you don’t have to — the NWS reports it nationally, too.
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Rep. Jeff Van Drew was defeated by ... another wind opponent.
Democrat Zack Mullock unseated Representative Jeff Van Drew, one of offshore wind’s biggest foes, on Tuesday night in the race for New Jersey’s second district. But while Mullock is a fan of renewable energy, he’s still a man of the south Jersey shore — and unlikely to be a champion for turbines off his coast.
District 2 encompasses the entire lower quarter of the state, covering six coastal counties from Atlantic City down to the tip of Cape May and around to the Delaware Bay. The area is a hotbed for offshore wind opposition, where groups like Protect our Coasts NJ have filed legal challenges against almost every wind project proposed in the region.
After heading to Congress in 2019, Van Drew, who was previously a Democrat, switched parties and became a key ally to this movement. He called for a moratorium on offshore wind development, held hearings on offshore wind “industrialization”, and requested that the Government Accountability Office investigate the industry. He also worked with the Trump administration to block projects that were under construction.
During a debate in late October, Mullock accused Van Drew of flip flopping on wind, arguing that the congressman was a staunch supporter of the industry during his decade-long tenure in the New Jersey legislature. Mullock, who is currently serving his second term as mayor of the city of Cape May, summed up his own position by citing a resolution he signed in 2023 calling for a moratorium on surveying and acoustic testing for offshore wind development pending an investigation into a spate of whale deaths. He signed it due to “concerns” about the environment and commercial fishing, he said.
“I believe very much in our future with renewable energy,” he said. “We need to go full steam ahead with solar panels. And yes we should do wind where it is appropriate, where it doesn't hurt our environment and it doesn't hurt our commercial fishing industry.”
Mullock’s campaign website says he supports federal investments in renewable energy and incentives for energy-efficient homes. He also wants “stricter enforcement of the Clean Air Act and the Clean Water Act,” and to fund coastal resiliency and other “smart infrastructure” projects that protect against climate impacts. He also campaigned in support of a data center moratorium.
Early signs point to a rough election for AI infrastructure.
We’ve seen enough: If this was the data center election, it was a really bad night for the industry.
Democratic campaigns and their affiliated Super PACs spent bigly on data center-themed attack ads. The ads came in various flavors. Some ads painted a vote for tax cuts as aiding data center developers. Others brought up candidates’ previous support for data centers or stock the candidate may have held in the tech industry or AI infrastructure developers. As Election Day approached, the data center industry sought to bat back claims that their sector’s poor reputation with the electorate would sway the results. People may have soured on their industry, they argued, but people weren’t going to vote based on that position.
Results are still coming in, but so far congressional races heavily featuring these data center attacks are heavily going in Democrats’ favor. In addition, these races have so profoundly shifted that it’ll be challenging for the industry to argue they played no role in the outcome.
Some of the most illustrative examples are obvious. In Georgia, Democrat Keisha Lance Bottoms campaigned on a statewide data center moratorium and won control of the governor’s mansion, becoming the first black woman to ever lead a U.S. state. Similar results in Ohio where Amy Acton flipped party control of the governor’s seat with a campaign that included going hard against data centers. In Pennsylvania, two Democrats who focused on data centers in their races have flipped Republican districts: Scranton mayor Paige Cognetti and firefighter Bob Brooks. In New Jersey, Cape May mayor Zack Mullock rode data center attacks to defeat Rep. Jeff Van Drew, the biggest opponent of the offshore wind industry. In Virginia, Democrat Shannon Taylor rode data center-laden attacks to take control of the Richmond area congressional seat from Rep. Rob Wittman.
If you’re arguing this election was decided by data centers, your best proof point: Democrat Gina Hinojosa has taken control of the governor's mansion in Texas, defeating incumbent Greg Abbott, who’d sought recently to take a hard line against the industry. Hinojosa ran on going further, calling to pass a law completely pausing data center development across one of the industry’s favorite states. She won a decisive victory. So did Democratic Texas Agriculture Commissioner candidate Clayton Tucker, who I explained months ago became one of anti-data center Facebook’s favorite online personalities.
But it makes sense that data centers would matter a lot in Texas, which could be compared to Virginia in terms of their buildout. When you inspect the election results more closely, they tell a more complicated story about the upper boundaries of these data center attacks.
For decades, Greenville and Spartanburg County have been GOP vote strongholds and reliable for both Republican congressional candidates and statewide campaigns. The congressional district gave Donald Trump at least a 20-point cushion in the 2024 presidential election, according to Decision Desk HQ. Last week, I explained for subscribers to The Fight how Courtney McClain, a novice candidate living one mile from a controversial data center proposal, was running against incumbent Rep. William Timmons. I couldn’t find much in the way of online ad spending on either side in this race and it’s never been on the radar of most political observers as a campaign that could somehow flip party control. But the data center debate in Spartanburg County has been immense.
Tonight, Timmons kept his ordinarily ruby red district by slim single digits after running even for most of the night. But this swing was essentially the same as the national margin. And because Timmons didn’t lose, this actually feels like a crucial distinction – data centers were not deciding races themselves in all cases. Democrat Annie Andrews defeated Republican Darlene Graham in a result driven by Democratic overperformance and GOP underperformance in this area, but it’s challenging to tie this result to the data center issue at all. Anything from the economy and the Iran War to Graham’s deceased brother and his baggage could be blamed for this result from this heavily evangelical region.
However, it will be challenging for the data center sector to differentiate themselves from this outcome, especially since a pro-data center Super PAC – Building the Future – publicly waded into the race in support of Graham only to lose. “Darlene Graham’s loss is a black eye for the data center industry,” wrote Teddy Schleifer of The New York Times on election night.
The same story played out in Georgia’s 1st district, which includes the city of Savannah. OpenAI is developing a controversial data center project in Effingham County, northwest of Savannah and the congressional race – which like South Carolina’s 4th had comparatively little spending – has been chock full of data center mudslinging, with the Democrat Amanda Hollowell calling for broader moratoria on development.
Effingham County went for Trump by almost 50 points in 2024. As of this story’s publication, the Republican, Jim Kingston, is winning by a single percentage point with 93% of the vote in. Most of what’s left is in Effington. Should this candidate win, it’s safe to say it’s because voters in this county looked past data centers, or did not link their vote for a national candidate to the local development.
On Election Night, Effingham County formally tabled any decision on the OpenAI data center. So at least on the ground level, people are paying close attention to these results.
After taking two seats in a special election last year, the party gained a third in the midterms.
Democrats claimed two seats on the Georgia Public Service Commission in a special election last year, ending almost 20 years of unanimous Republican control over the regulator.
One of those winning Democrats, Peter Hubbard, ran again this year for a full six-year term in a rematch against Republican Fitz Johnson. The other open seat this year saw Sheila Edwards running in an open race against Republican Josh Tolbert.
Both Hubbard and Edwads won, securing a 3–2 Democratic majority on the Public Service Commission.
“Over the last 12 months, Georgian consumers have made one thing clear: They are tired of rising utility bills and they are hungry to see change. Georgia’s sea change moment for energy policy has arrived,” Charles Hua, the executive director of the utility-focused advocacy group PowerLines, told me.
The Democrats have not been shy about what their priorities will be on the commission.
“Winning control of the Georgia Public Service Commission means prioritizing lowering power bills instead of constantly increasing corporate profits, ramping up the deployment of clean energy technologies, and focusing the people in our decision-making as state regulators,” Hubbard said in a statement on his website.
Edwards, for her part, made it clear where she stands on data centers specifically in an October debate with Tolbert. “They came into our communities,” Edwards said. “They didn’t pay any taxes. They are using our water, using our electricity, and they’re being a public nuisance to the communities that they’re coming into.”
Hubbard also talked about data centers on Heatmap’s Shift Key podcast back in June. “I advocate for a whole-of-government approach, because while the Public Service Commission really only has oversight over the power side of things — where that power comes from and how much data centers are paying on their tariff — there’s much larger issues in terms of water use, in terms of the tax incentives,” he told my colleague Robinson Meyer. “The estimate is $3.5 billion in tax abatements this year in Georgia, uncollected revenue that data centers otherwise would be willing to pay.”
The race has seen outsize spending and interest from major figures not accustomed to dealing in utility regulator races. (Just 10 states have elected utility commissions, period.) Kamala Harris appeared at a virtual fundraiser for the Democratic candidates in Georgia, as well as Democratic hopefuls to the Arizona Corporation Commission. The solar energy industry spent hundreds of thousands of dollars in support of the Democrats in Georgia. Meanwhile, anonymous donors pumped millions of dollars into Tolbert’s bid.
Democrats swept into the Georgia PSC last year on a wave of dissatisfaction with rising electricity prices, especially rate hikes attached to the construction of two new nuclear reactors at the Vogtle Electric Generating Plant, which ran years behind schedule and billions of dollars over budget. In the runup to the election, the PSC approved a three-year base rate freeze proposed by Georgia Power in an attempt to head off public dissatisfaction.
In the past year, rates in Georgia have gone up by less than 1% across the state on average, according to the Heatmap-MIT Electricity Price Hub, while rates are up over 18% in the last three years and over 6% in the past two years.
Shares in Southern Company, the parent company of Georgia Power, were down slightly more than 0.5% in after-hours trading Tuesday night.