Scientists hope to prevent deaths from climate change, but heat and cold are more complicated than we thought. Libby Cowgill is an anthropologist at the University of Missouri who hopes to revamp the science of thermoregulation. Libby Cowgill, an anthropologist in a furry parka, has wheeled me and my cot into a metal-walled room set to 40 F. A loud fan pummels me from above and siphons the dregs of my body heat through the cot's mesh from below. A large respirator fits snug over my nose and mouth. The device tracks carbon dioxide in my exhales--a proxy for how my metabolism speeds up or slows down throughout the experiment. Eventually Cowgill will remove my respirator to slip a wire-thin metal temperature probe several pointy inches into my nose. Cowgill and a graduate student quietly observe me from the corner of their so-called "climate chamber. Just a few hours earlier I'd sat beside them to observe as another volunteer, a 24-year-old personal trainer, endured the cold. Every few minutes, they measured his skin temperature with a thermal camera, his core temperature with a wireless pill, and his blood pressure and other metrics that hinted at how his body handles extreme cold. He lasted almost an hour without shivering; when my turn comes, I shiver aggressively on the cot for nearly an hour straight. I'm visiting Texas to learn about this experiment on how different bodies respond to extreme climates. I jokingly ask Cowgill as she tapes biosensing devices to my chest and legs. After I exit the cold, she surprises me: "You, believe it or not, were not the worst person we've ever seen." Climate change forces us to reckon with the knotty science of how our bodies interact with the environment. Cowgill is a 40-something anthropologist at the University of Missouri who powerlifts and teaches CrossFit in her spare time. She's small and strong, with dark bangs and geometric tattoos. Since 2022, she's spent the summers at the University of North Texas Health Science Center tending to these uncomfortable experiments. Her team hopes to revamp the science of thermoregulation. While we know in broad strokes how people thermoregulate, the science of keeping warm or cool is mottled with blind spots. "We have the general picture.

A study reveals that extreme heat accelerates biological aging even more than smoking or drinking. It is well known that heat causes exhaustion in the body due to dehydration. A recent study concluded that extreme heat accelerates the aging of the human body, a worrying fact given the increasing frequency of heat waves due to climate change. The researchers are not talking about the effects of solar radiation on the skin, but biological aging. Unlike chronological age--that answer that you give when asked how old you are--your biological age reflects how well your cells, tissues, and organs are functioning.

Forecasting in real-world settings requires models to integrate not only historical data but also relevant contextual information, often available in textual form. While recent work has shown that large language models (LLMs) can be effective context-aided forecasters via naïve direct prompting, their full potential remains underexplored. We address this gap with 4 strategies, providing new insights into the zero-shot capabilities of LLMs in this setting. ReDP improves interpretability by eliciting explicit reasoning traces, allowing us to assess the model's reasoning over the context independently from its forecast accuracy. CorDP leverages LLMs solely to refine existing forecasts with context, enhancing their applicability in real-world forecasting pipelines. IC-DP proposes embedding historical examples of context-aided forecasting tasks in the prompt, substantially improving accuracy even for the largest models. Finally, RouteDP optimizes resource efficiency by using LLMs to estimate task difficulty, and routing the most challenging tasks to larger models. Evaluated on different kinds of context-aided forecasting tasks from the CiK benchmark, our strategies demonstrate distinct benefits over naïve prompting across LLMs of different sizes and families. These results open the door to further simple yet effective improvements in LLM-based context-aided forecasting. 1

Sign up for the Slatest to get the most insightful analysis, criticism, and advice out there, delivered to your inbox daily. Summer just started, and the first significant heat wave of the season is almost over. Some 265 million people across the Midwest and the eastern United States have experienced a week of temperatures in the 90s and triple digits, with a slew of all-time records set on Tuesday. While extreme heat waves can be caused by any number of factors, this particular one is thanks to a phenomenon called a heat dome: a ridge of atmospheric pressure that settles over a region like, well, a dome. Or, as the National Weather Service's Alex Lamers so wonderfully described it to NPR, think of it as a lid placed over a grilled cheese, which, as we all know, makes the cheese melt much faster.

Zubaida starts her day at eight in the morning, sorting discarded plastics, glass, and chemicals with her bare hands, to collect items she can sell. With waste-segregation centers in this part of East Delhi currently shut down, she and other waste-pickers from the Seemapuri slum work outside by a dusty road through the hottest hours of the day, under the blazing sun. There is no fan or shade. With Delhi's heat wave season here, they are constantly exposed to intense high temperatures. On June 11, the India Meteorological Department (IMD) issued a red alert for Delhi, warning of a high risk of heat illness and heat stroke.

Extreme heat is the deadliest weather-related hazard in the United States. Furthermore, it is increasing in intensity, frequency, and duration, making skillful forecasts vital to protecting life and property. Traditional numerical weather prediction (NWP) models struggle with extreme heat for medium-range and subseasonal-to-seasonal (S2S) timescales. Meanwhile, artificial intelligence-based weather prediction (AIWP) models are progressing rapidly. However, it is largely unknown how well AIWP models forecast extremes, especially for medium-range and S2S timescales. This study investigates 2-m temperature forecasts for 60 heat waves across the four boreal seasons and over four CONUS regions at lead times up to 20 days, using two AIWP models (Google GraphCast and Pangu-Weather) and one traditional NWP model (NOAA United Forecast System Global Ensemble Forecast System (UFS GEFS)). First, case study analyses show that both AIWP models and the UFS GEFS exhibit consistent cold biases on regional scales in the 5-10 days of lead time before heat wave onset. GraphCast is the more skillful AIWP model, outperforming UFS GEFS and Pangu-Weather in most locations. Next, the two AIWP models are isolated and analyzed across all heat waves and seasons, with events split among the model's testing (2018-2023) and training (1979-2017) periods. There are cold biases before and during the heat waves in both models and all seasons, except Pangu-Weather in winter, which exhibits a mean warm bias before heat wave onset. Overall, results offer encouragement that AIWP models may be useful for medium-range and S2S predictability of extreme heat.

Heatwaves (HWs) are extreme atmospheric events that produce significant societal and environmental impacts. Predicting these extreme events remains challenging, as their complex interactions with large-scale atmospheric and climatic variables are difficult to capture with traditional statistical and dynamical models. This work presents a general method for driver identification in extreme climate events. A novel framework (STCO-FS) is proposed to identify key immediate (short-term) HW drivers by combining clustering algorithms with an ensemble evolutionary algorithm. The framework analyzes spatio-temporal data, reduces dimensionality by grouping similar geographical nodes for each variable, and develops driver selection in spatial and temporal domains, identifying the best time lags between predictive variables and HW occurrences. The proposed method has been applied to analyze HWs in the Adda river basin in Italy. The approach effectively identifies significant variables influencing HWs in this region. This research can potentially enhance our understanding of HW drivers and predictability.

Millions of Americans are currently dealing with a heat wave across the US, so staying cool is important. There are many ways to deal with the scorching heat, and the good news is that quite a few of the tools that can help are on sale for Prime Day. These range from the obvious Prime Day air conditioner and tower fan deals, but you can also find discounted cooling sheets and even a mattress that can help transfer your body heat during the night for better sleep if you are in fact sleeping and not obsessively tracking our Prime Day liveblog. We test products year-round and handpicked these deals. We'll update this guide periodically throughout the sale event.

In the opening chapter of "The Ministry for the Future," science-fiction author Kim Stanley Robinson details a calamitous heat wave that kills almost all the residents of a small town. In another chapter, he imagines a catastrophic flood that wipes out Los Angeles. The late Octavia Butler described a Southern California reeling from years of drought in "Parable of the Sower," and Paolo Bacigalupi writes about a near-future Southwest that's also been devastated by drought. Sci-fi writers have long conceived worlds in which extreme weather events upend the lives of its inhabitants, but with every passing, warming year, their scenarios feel more prophetic. Last September, record-shattering temperatures nearly broke the state's power grid, and according to a Times investigation, extreme heat waves are killing more Californians than official records show.

The recent heatwave has been tough to bear. The days are long and humid, and the nights offer little relief. I find myself cranky and short-tempered, and even the simplest tasks seem to take twice as much effort. I know I'm not alone in feeling this way - the entire city seems to be struggling under the weight of the heat. Even so, I can't help but appreciate the beauty of a summer day.