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Chamber of Commerce, oil groups urge Trump to reject diesel export ban
American business, energy and manufacturing groups on Wednesday urged President Trump to reject calls to impose a diesel export ban after the president said he was weighing this move in an effort t…
Hearing on NextEra-Dominion utility merger scheduled in Fairfax
Virginia's state regulatory body has scheduled a Northern Virginia hearing as it weighs a proposed merger between Dominion Energy and Florida-based NextEra Energy.
Crew Studies Advanced Health Tech and Gears Up for Next Crew Swap
Ultrasound scans using augmented reality and artificial intelligence topped the health research schedule aboard the International Space Station on Wednesday. The Expedition 75 crew also collected blood and saliva samples to study how the immune system adapts to weightlessness. The orbital residents are now preparing for a crew swap as NASA’s SpaceX Crew-13 mission announces a launch date.
UFC Veteran Encourages Gable Steveson to Leave Jon Jones
UFC veteran Matt Brown has encouraged heavyweight prospect Gable Steveson to leave Jon Jones and find someone else to coach him. Steveson was shockingly defeated by Sean Sharaf on the UFC 331 main card this past Saturday in the biggest upset in UFC history, based on the odds. Following the bout, Steveson left the cage […] The post UFC Veteran Encourages Gable Steveson to Leave Jon Jones appeared first on HEAVY.
Early childhood BMI trajectories predict later cardiometabolic health risks
Childhood obesity predicts later cardiometabolic disease, but single-time weight measures may miss dynamic growth information.
JPMorgan Weighs Opening Card Business to Private Credit
J.P. Morgan Chase is reportedly exploring whether other funding sources could approve some of the cards it rejects. That's according to a report late
AI Boom, Politics, Inflation Stoke Anxiety Across Big Law
AI’s ascendance, polarized politics, and stubborn inflation are weighing down legal professionals, survey shows.
DA Larry Krasner faces an uncertain political future as Democrats weigh what could come next
New questions emerged this week about Krasner’s political ambitions and his potential bid for Philly mayor. Meanwhile, others are angling for his job.
Horiguchi Returns Versus Almabayev At UFC Qatar
The UFC Flyweight division is hot right now. Just days ago at UFC 331, Joshua Van cemented his rule atop the 125-pound roost with a violent decision win over former divisional kingpin Alexandre Pantoja. Van is expected to face Manel Kape in his next title defense, but otherwise, the division is wide open for any […]
Stanford researchers weigh AI applications in education, science
As AI becomes increasingly capable, Stanford researchers explore how it can extend human capabilities in education, science and the social sciences.
Detroit Pistons Slip Weight Clause Into Jalen Duren Contract
With training camp opening next week, the Detroit Pistons still have not been able to reach a long-term agreement with restricted free agent Jalen Duren
Russia's neighbor reveals personal appeals to Trump as US weighs NATO troop pullback in Europe
Lithuanian President Gitanas Nausėda revealed he sent two letters to Trump urging U.S. troops to stay on NATO's eastern flank amid Russia threat.
Qualcomm releases Android chip built for AI as memory shortage weighs on smartphone market
The overall smartphone market is expected to contract 14% in terms of units shipped in 2026.
When treachery abounds, entertainment resounds - The Voice of San Francisco
Betrayal is disheartening and debilitating, unless it’s happening to someone in a movie. Then, it’s diverting. For example, The Weight is a tension-loaded drama that follows a criminal expedition into the wilds of the Pacific Northwest in the 1930s and hinges on shady people depending on each other in extreme circumstances. As for The Musical, […]
Poor sleep health in late pregnancy linked to higher childhood obesity risk
New research has found that mothers with poor sleep quality in late pregnancy had babies with lower weight in the first 6 months of life, but higher weight after age 1-2 years.
Can AI Be Slowed Down? Stanford HAI Experts Weigh the Risks, Rules and Race Ahead
In a new series called 'Prompt Response,' Stanford’s Surya Ganguli, Diyi Yang and Rob Reich examined emergent agent behavior, recursive self-improvement, independent evaluation and whether a 'kill switch' can make advanced AI safer.
Portsmouth housing solutions, AI threats, political views: Letters
Letters package: Writers weigh in on Portsmouth housing policy, AI risks, NH politics, Maine fisheries and international affairs.
MORNING BUSINESS REPORT: Seniors use weight loss drugs, Apple settlement, Disney trip deals
More seniors are using drugs like Ozempic, customers can claim part of an Apple settlement, and Disney offers promotional deals. Here's the Morning Business Report for Sept. 22.
Is 50 the new 60?
Subscribe TL;DR: Younger generations are showing signs of worse health compared to earlier-born cohorts at the same age This backward “drift” is showing up both in mortality risk and chronic disease Worsening trends in obesity and diabetes are the most consistent signals Taking the long view, we’ve made astonishing gains in health and life expectancy in the last century. Global average life expectancy has more than doubled from 32 years in 1900 to 73 years in 2024. (But don’t forget, there were still old people when life expectancy was 32). As people lived longer, they also generally lived healthier along the way. It turns out that avoiding things that can kill you early, like malnutrition and lots of childhood infections, also keeps you healthier later in life. In a classic 2004 paper, Finch and Crimmins proposed that cohorts of children who benefited from fewer early life infections had less lifetime exposure to inflammation and cardiovascular disease later in life, accelerating mortality improvements at older ages. Poor nutrition in the womb has also been linked to a higher risk of later chronic disease. The upshot is that improvements in childhood health can pay dividends many decades later. The combination of better living conditions (nutrition, sanitation) and medical advances (antibiotics, vaccines, blood pressure meds, etc) meant that people’s healthy lifespan generally expanded, even as they lived longer. Aging researchers call this best-case scenario “compression of morbidity”—meaning we delay the onset of disease and disability even faster than the years of life we are adding. During my 20+ year research career, we could generally bank on the idea that younger generations would not only live longer but also keep getting healthier along the way. “60 is the new 50” as they say… Enter “Generational Health Drift” Sadly, this expectation of steady progress may be changing. You’ve probably heard that US life expectancy gains have slowed to a crawl in the past couple of decades. Mortality improvements are also slowing (though less dramatically) in many other high-income countries (you can read more about that in a review paper I wrote here). Mortality is a very blunt health measure, but it is often a good barometer for the broader population health trends happening underneath. And we are now seeing that younger generations may be in worse health at similar ages compared to earlier born cohorts. My collaborator Prof. George Ploubidis at University College London coined this worsening health in more recently born cohorts “generational health drift.” “Generational health drift” is bad news on multiple fronts. Most obviously, we don’t want our health progress to go backward. But the timing is also bad, since our populations are aging. In demographic terms, “population aging” means that the proportion of the population at older ages (i.e >65 years) is increasing. Fun demography fact: Current population aging is not due to the recent declines in the birth rates making the news, but declines in fertility decades ago, after the “baby boom.” As baby boomers reach older ages, the smaller cohorts behind them mean the percentage of older adults will increase. For example, the share of the population age 65 and older in the US increased from 12.4% in 2004 to 18.0% in 2024. This story of population aging was written long ago. Many worry that population aging will put pressure on health care and pension systems. But if people reach older ages in better health than in years past, those fiscal pressures would be less dire than projected. Healthy older people can also continue to contribute to society in many valuable ways, including paid work, caregiving, community service….even high political office 🤷. On the flip side, if younger generations reach retirement age in worse health and with more disabling conditions, this could magnify the societal challenge of population aging. Evidence for worsening generational health A recent paper that I LOVED in the Proceedings of the National Academy of Sciences by Dr. Leah Abrams and colleagues examined which birth cohorts (aka generations) were behind worsening US mortality. Behold the Lexis diagram (cue swooning demographers). Calendar time is on the x-axis, age on the y-axis. Birth cohorts can be followed over time as they age on the diagonal lines moving up and to the right. This figure plots the year-on-year % change in all-cause mortality at a given age. Green shading indicates mortality improvements over time, white is stagnation, and gray shading indicates worsening mortality. Following the diagonal line for those born in 1950, you can see a noticeable shift from green to gray that follows this cohort for most of their lives. This gray shading shows generally worsening mortality for the 1950 to 1959 birth cohorts compared to their predecessors across all ages. Concerningly for my GenX and elder millennial peeps, there was also a deterioration in mortality for birth cohorts born in the 1970s and 1980s, visible as dark gray areas at ages 30 to 45 during the 2010s. While some of these mortality changes reflect specific shocks such as the opioid epidemic, most deaths still occur from major causes of death such as cardiovascular disease and cancer. For cancer, the gray in the top left corner of the figure below reflects the legacies of smoking for older cohorts, followed by a period of green with improvements in cancer mortality as smoking rates declined. But the white/gray shading in the bottom right corner highlights a stagnation and reversal of the cancer trends, with cohorts born around 1970 to 1985 experiencing worsening cancer mortality. This deterioration was most noticeable for colon cancer mortality, possibly linked to obesity or dietary factors. Not just dying more, but less healthy along the way. A recent paper by Dr. Laura Gimeno of University College London (of which I am a co-author), found evidence that more recently born cohorts in Great Britain have stagnating or worsening health. A stylized picture of what“generational health drift” might look like: The review paper found: Rates of childhood overweight and obesity were highest among Gen Z. Rates of diabetes in the 40s almost doubled from 3.1% among the Baby Boomers to 5.9% in Generation X. Gen Z reported higher rates of poor mental health in adolescence compared to earlier-born groups. These UK results are consistent with studies showing worsening health across generations in the US as well. A 2021 US study found that more recently born cohorts had worse biological markers (like blood pressure and blood sugar) than earlier generations at the same age. A separate 2022 study of Americans aged 50 and over found that more recently born generations had a higher number of chronic diseases, with younger age of disease onset. A 2024 Lancet paper found that in the US, women born in 1945 had 33% obesity prevalence at age 50, rising to 48.2% for women born in 1970 turning 50. So what’s going on, and can we turn it around? We don’t have a definitive answer for what’s causing the deteriorating health of younger cohorts, but circumstantial evidence points to worsening trends in obesity and diabetes in both the US and UK. Remember that cohort trends reflect lagged effects of early environments, and younger generations have faced both earlier onset and more severe obesity across their lifetimes. Despite these very concerning trends, the future is not set in stone. We’ve reversed poor generational health trends before: drops in smoking are a major reason cancer and heart disease deaths fell so dramatically in recent decades. GLP-1 drugs may finally turn the tide against rising rates of obesity and diabetes, though it is still early days. But things could also get worse…for example from a return to higher levels of childhood infectious diseases that can have a lasting impact on health. See for example: [ ](https://jenndowd.substack.com/p/dont-you-forget-about-measles-the) [ Don’t You Forget About Me(asles): The Virus That Erases Immune Memory ](https://jenndowd.substack.com/p/dont-you-forget-about-measles-the) Jenn Dowd, PhD · March 24, 2025 [ Read full story ](https://jenndowd.substack.com/p/dont-you-forget-about-measles-the) Even as an optimist, emerging data on the “generational health drift” has my full attention. For most of my research career, we took it for granted that each generation would be healthier than the last. But if present trends continue, **50 could be the new 60….**and Gen Z celebrities will soon look older than Paul Rudd :). Stay well, Jenn Share the Health! If you found this post useful, please share it with a friend. Share
Newsom eyes 2028 as Democrats weigh their political future
Join The Hill’s Ian Swanson, Amie Parnes and special guest Democratic strategist Garry South, who has advised California Gov. Gavin Newsom (D), for a special “Fight for 2028” centered o…
Minogue calls for federal probe into $2B state contract awarded to political heavyweights
Republican gubernatorial candidate Mike Minogue is calling on U.S. Attorney Leah Foley to investigate “everything around” the $2 billion state contract awarded to politically connected bidders.
My predictions for Meta Connect 2026
Join me in guessing what will be unveiled at Meta Connect 2026, including exciting news about a new lightweight mixed-reality headset.
ICE fears weigh on Latino business owners as DeLauro tours Fair Haven
Connecticut representative Rosa DeLauro visited restaurants and a retail store in New Haven’s majority-Latino Fair Haven neighborhood, where business owners said customers’ fear of ICE activity was driving down sales.
Congressional leaders warn White House against adding controls over NIH grants
Political officials are weighing the creation of a commission to review awards by the National Institutes of Health, The Post reported.
Nicole Kidman urges fans to ‘demand’ a season 4 for ‘Lioness’: ‘We need loud voices’
Nicole Kidman weighs in on the shocking ‘Lioness’ season 3 finale and what might come next for the Paramount+ series.
Gov. Pritzker shares details on health, weight loss journey
Governor JB Pritzker shared new details about his health and weight loss journey.
Germany’s political center suffers historic blow, Turkey weighs coming to Saudi Arabia’s aid, Major TV networks support outlets banned from White House
Two weeks ago, German Chancellor Friedrich Merz was “shocked” when his conservative CDU party got creamed by the hard right AfD in local elections in the state of Saxony-Anhalt. That was just the start.
Oxford Saïd Turns 30, Recalling Its Start In A Working Hospital
At 30, the school runs the world's top-ranked executive MBA, according to QS, and its leaders are weighing how big to grow.
JB Pritzker Says He Used GLP-1s to Lose 80 Pounds
Gov. JB Pritzker of Illinois, widely seen as a potential presidential candidate, revealed in an interview on “CBS Mornings” that he had been on a GLP-1 regimen since 2024.
Swiss business groups pressure parliament over UBS capital rules before vote
ZURICH, Sept 21 (Reuters) - Swiss business groups have weighed into the debate on tougher capital rules for UBS, writing to lawmakers to lobby against what they say risks being "excessive" regulation drawn up for the bank after the 2023 collapse of C...
Swiss business groups pressure parliament over UBS capital rules before vote
ZURICH, Sept 21 (Reuters) - Swiss business groups have weighed into the debate on tougher capital rules for UBS, writing to lawmakers to lobby against what they say risks being
Dramatic before and after photos that show off Abby Lee Miller's 127lb weight loss - as Dance Moms star turns 61
Dance Moms star Abby Lee Miller has undergone a major weight loss journey, see her before and after transformation photos
Is $300K enough? Economist weighs Nashville small business relief amid higher property tax
As Nashville businesses face higher property tax costs, Metro is looking at a $300,000 small-business incentive aimed at providing some relief.
Most Sports Parents Say There's More Good Than Harm In Youth Sports, Survey Finds
By Dennis Thompson HealthDay ReporterMONDAY, Sept. 21, 2026 (HealthDay News) — Sports parents overwhelmingly say the benefits of organized competition outweigh the drawbacks for them and their kids, a new survey has found. Nearly 9 out of 10 sports parents (89%) said the benefits of youth sports ...
Tobias Forge’s ‘V/H/S Mixtape’ Segment, Swedish Horror ‘Trespassers,’ ‘The End’ by ‘Midsommar’ Production Designer on Mylla Films Slate (EXCLUSIVE)
Swedish boutique genre specialist Mylla Films, brainchild of “Midsommar” producer Patrik Andersson and Nordic indie distribution heavyweight Jakob Abrahamsson (CEO of NonStop Entertainment), has turne...
Arman Tsarukyan Issues Statement Following Big UFC 331 Win
UFC lightweight contender Arman Tsarukyan issued a statement following his big win at UFC 331 over Mauricio Ruffy.In the co-main event of UFC 331, Tsarukyan knocked out Ruffy with a standing elbow and punches with just four seconds left in the first round.The fight was scheduled for five rounds, but Tsarukyan didn’t even need a […] The post Arman Tsarukyan Issues Statement Following Big UFC 331 Win appeared first on HEAVY.
Vitek Vanecek making case to be third goalie as Islanders weigh Semyon Varlamov's health risk
Nobody knows what the demands of an 84-game season — the travel, the practices, the 25 to 30 games the Islanders hope to get from their backup spot — will do to Varlamov’s knees.
Wake county, state leaders weigh in ahead of Atrium-WakeMed merger vote
The Wake County Board of Commissioners is scheduled to vote Monday on proposed merger between WakeMed and Atrium Health. Some Commissioners tell WRAL they're still skeptical, while others say the deal will serve North Carolinians.
Vocci's ring adds a new form factor to meeting note-taking
Vocci's lightweight ring costs $249, and might pose some privacy questions
Scientists Discover New Compound That Burns Fat Without Killing Your Appetite
Unlike GLP-1 drugs, which suppress appetite and reduce energy intake, a newly identified molecular compound helps cells burn more energy without changing food intake or exercise and has shown promise in mouse models. The most successful new obesity drugs largely work by helping people eat less. Researchers at UC Berkeley are exploring a different strategy:
Rare earth exposure causes 3-fold increase of health risk to China’s newborns
Research tracking pregnant Chinese women over a two year period shows link between critical mineral exposure and low baby birth weights.
Rare earth exposure causes 3-fold increase of health risk to China’s newborns
Research tracking pregnant Chinese women over a two year period shows link between critical mineral exposure and low baby birth weights.
Jodi's Journal: Weighing the price of data privacy
In a week of discussion over who’s watching us on the road, Jodi considers how data privacy questions could land next in the workplace.
Political Pulse: NMDOJ demands answers from PNM on billing complaints, Google considers data center in New Mexico, & lawmakers weigh gas tax hike
ALBUQUERQUE, N.M. (KRQE) –This week on the New Mexico Political Pulse, the New Mexico Department of Justice sent a letter to PNM, calling for an explanation following customer compla…
It'll be controversial! Liverpool's eye bizarre new transfer
Liverpool have a new transfer plan in mind and it'll prove controversial. The Reds need to have a big think on this one.Liverpool are weighing up their transfer plans for the January transfer window a...
Author Michael Clinton weighs in on the changing science of longevity
The author reconsiders aging.
Sean Sharaf Pulls Off Biggest Upset in UFC History
Heavyweight Sean Sharaf pulled off the biggest upset in UFC history when he knocked out Gable Steveson in just 12 seconds at UFC 331. Sharaf stormed across the cage and caught Steveson with a massive left hook that immediately knocked him out cold for the biggest win of his MMA career to date and the […] The post Sean Sharaf Pulls Off Biggest Upset in UFC History appeared first on HEAVY.
UFC 334 announced, heavyweight title fight headlines massive NYC card
UFC 334 full card announced during 331 broadcast
Are politicians normal people? New Yorkers weigh in
Elevance Health (ELV) Stock May Be Undervalued On Reaffirmed 2026 Guidance
Elevance Health has had a solid run over the past year, and the stock is now trading with recent news about its earnings outlook fresh in investors' minds. The core question is whether the current share price is warranted by the healthcare insurer's ability to keep converting its profit story into sustainable earnings per share. The stock has gained 33.6% over the past 12 months, which puts more weight on whether that move is supported by the underlying earnings power of the...
The Big Holes in Wearable Heart Rate Variability And Readiness Scores
On September 9th, Apple announced it was revamping its Apple Watch Health Sensing System, rolling out a Readiness score (0 to 10), and increasing the frequency of heart rate variability (HRV) outputs 24-fold. This can be viewed as upping its competition with various other consumer wearable sensors. These “readiness scores” as a composite of multiple metrics, with heart rate variability (HRV) being front and center for most. The majority of Americans are now using wearable sensors, which equates to well over 100 million adults. HRV and Readiness scores are increasingly being marketed as a measurement of autonomic nervous system health, a digital marker for future disease, a clock for biological age, and a holistic metric to promote healthspan and even longevity. (Apple also introduced a new longevity tab and “Health Age”.) None of this has been proven. In this edition of Ground Truths I am going to review what we know about heart rate variability and readiness scores. Heart Rate Variability HRV is the variation in normal heart cycle timing. The variability of the heart rate, the barely perceptible millisecond changes in time between consecutive heart beats (see R-R intervals in the Figure below, left panel), is due to interplay between the sympathetic and parasympathetic (vagal nerve) inputs. Distinct from heart rate, individuals with the same heart rate can have very different HRVs. It is a rough reflection of the autonomic nervous system (ANS) activity, inadequate to say whether a person’s ANS function is abnormal. For more than three decades, heart rate variability (HRV) has been measured and several studies have found an association of low HRV and clinical outcomes, particularly a link with higher all-cause and cardiovascular mortality. There have also been less well established links of low HRV to risk of early cognitive impairment, dementia, mental illness, Type 2 diabetes and substance abuse. An important reminder is that HRV is a surrogate marker without any established cause-and-effect relationship. If you increase your HRV, that doesn’t mean it will improve health outcomes. In fact, there is no hard evidence for that. All that work linking to health outcomes was done with electrocardiogram (ECG) derived HRV. Now, in the era of consumer wearables, this is getting assessed differently, by optical pulse (yes, the lights you see) plethysmography (PPG) or what is called pulse rate variability (PRV). They are not the same, as shown below (right panel) and only concordant when the delay between the ECG and pulse is kept constant, which basically means at rest. I should mention there’s also what I will call MPV, a mattress mechanical movement sensor, a derived heart rate variability, that companies like Eight Sleep use, even further away from directly measuring HRV. HRV has not one uniform measurement but many different types of quantification, such as RMSSD, the magnitude of difference between successive R-R intervals of normal sinus beats (N-N) or SDNN, the standard deviation of NN intervals, both in milliseconds. SDNN is one of the so-called frequency domain HRVs (others are LF, HF, LF/HF). Different wearable sensors use different metics; Apple has relied on SDNN and nearly all of the others use RMSSD, which is generally considered the more accurate metric. There’s also the different length of time measured, such as for a matter of minutes, all day, or an overnight’s sleep. Short measurements are especially problematic since they don’t capture enough of respiratory modulation and other factors that influence HRV. Share Ground Truths How well does HRV correlate with PRV? There are very limited studies, especially independently done. One that is commonly cited was conducted by Air Force researchers in only 13 healthy adults assessing Oura ring 3 and 4, Whoop 4.0, and Garmin Fenix 6 and showed a correlation coefficient of 0.88 to 0.97 and a mean absolute percentage error from 6 to 10%. The correlation is not a perfect 1.0, but there’s at least a fairly high level of correlation. HRV is supposed to increase during the night due to takeover of the parasympathetic nervous system, and higher during deep sleep. A recent example of my 1 week, all day “HRV,” and one during sleep is shown below. As you can see, the N of 1 data are inconsistent for the same days from different sensors (Oura, AppleWatch, Fitbit Air, and Eight Sleep) by patterns, absolute numbers, and comparison with prior days and weeks. The largest study in over 8 million Fitbit users (the old version, not Google Fitbit Air, introduced in May 2026) gives you a sense of the effect of age, sex, and the 2 different main HRV (here PRV) metrics, with RMSSD on the left and SDRR (=SDNN) on the right below. That study, from data collected in 2018, is a major outlier, since all the more recent ones are tiny with respect to sample size. Many of the companies have not had independent evaluation of their HRV, such as Eight Sleep, but have published a low standard error on their website. There are some other published studies on the correlation between HRV and PRV, but they are all small and only in healthy adults. A scoping review emphasized the lack of study in underrepresented individuals, including the aged, people of color (which affects the PPG signal), and individuals who are underweight or obese. Add the typical adult age 60 plus with one or more chronic diseases. For example, one study in over 900 adults found poor correlation of HRV and PRV, non-uniformly underestimated across many chronic diseases (cardiovascular, endocrine, neurological, respiratory, and others), concluding PRV is “an invalid surrogate for HRV.” A recent systematic review of 43 studies comparing HRV and PRV found reasonable pooled absolute standardized error (HRV as gold standard) but only 10 of the studies provided quantitative synthesis in ideal conditions. Their main conclusion was similarly cautious: “PPG-derived HRV [PRV] should not be regarded as universally interchangeable with ECG-derived HRV across all devices, populations, and recording contexts.” Factors Affecting HRV and PRV That gets me to the long list of factors that affect HRV (and PRV) besides the device, the type of measurement (RMSSD, SDNN or others), the person’s signal, the sensor site, the duration of data capture, if weighting by sleep stage is used, how artifact is processed and corrected. And this list is not complete!: Oura puts out data from their community of users (who input data) on what affects their overnight HRV. The factors currently provided are: no alcohol (increase 8%), melatonin (increase 2%, float tank (increase 2%), wine (decrease 4%), and party (decrease 14%) in overnight HRV. Must be some big parties! Subscribe What is a PRV measurement good for? It has been falsely characterized as an index of “autonomic balance” and a specific indicator of stress. A 2018 review of the studies available for HRV and its relationship to stress, not using any of the current wearables, found that stress can lower HRV. But so can many other factors. The non-specificity of the signal, indexed to the table above, is striking. Evidence from a UK Biobank study of over 46,000 participants with actual HRV looked at genetically predicted HRV, a genetic risk score, that failed to show the expected HRV-mortality link, indicating that _HRV is likely not causa_l, but rather a reflection of person’s physiologic state. A review of consumer wearable HRV data from 5 longitudinal studies showed that nighttime PRV was not associated with perceived stress, and surprisingly higher HRV, in the largest cohort (N=717 participants), was correlated with higher stress. An Oura ring cohort of 525 first-year college students found a link between overnight PRV and perceived stress, but that was also seen with resting heart rate, sleep, and respiratory rate. Several very small studies have examined the relationship of HRV and athletic injuries or guiding training with mixed, and predominantly negative results. HRV biofeedback training with paced breathing had no significant effect on reducing stress or raising HRV, as demonstrated with sham controlled trials. When HRV for multiple days showed a decline in conjunction with body temperature, the Oura ring published data for prediction of Covid. The WHOOP company sponsored an observational study, published in 2026, of 30,000 users for 72 weeks, without a control group, that reported reduced alcohol intake (5.8 % points) by self-report. That doesn’t tell us much, and particularly about the merits of HRV for behavioral change. If you use the same device and conditions as longitudinal trends for multiple (at least 2-3) weeks that may be the one way to get something useful from the measurements. Data for overnight sleep with minimal motion and using RMSSD is the best proxy for real HRV. The reason to look at trends rather than any given night is that it more likely represents something, even though you won’t know with certainty what the “it” is. Keep in mind there are no data, no peer-reviewed evidence, to show that HRV fluctuation in-person has any correlation with health outcomes. Share Readiness Scores These are proprietary scores that integrate different metrics for each of the wearables: no algorithms have been disclosed. They are unvalidated against health outcomes. In a review of 14 composite health scores of readiness and recovery, HRV contributed 86% to the scores, followed by reading heart rate (79%), physical activity and sleep duration (both at 71%). That review noted the substantial variability in measurement protools and lack of standardization. Sleep staging is notoriously inconsistent and inaccurate by these sensors, which adds further to the HRV uncertainties for what the scores, which use sleep stage data, mean. Only resting heart rate has been shown consistently across devices to be extremely accurate. I’ve made a Table to summarize what we know about which metrics are included, the scores, any peer-reviewed studies that compared the readiness score with health outcomes, and the corresponding (if any, NA-not available) citation. You will note that some companies do not use the term “readiness," such as WHOOP for recovery, and Garmin, which has 2 different scores, one of which is Body Battery. Eight Sleep uses the term “Fitness Score.” They all include HRV; Apple includes a new metric they call “Recovery HRV” which among other components uses 7-days of sleep, but it is unclear what this means or how it is differentiated from other scores (there are clearly no data for outcomes). We have no knowledge of how the different components are weighted or whether any of these scores are better than resting heart rate, HRV alone, physical activity, or any other single metric. Since none of these are standardized, they are not interchangeable, so if you get a 90 for Oura that has no relationship to a 90 on a Google Fitbit Air. Notably, the company can update its algorithm for readiness score at any point without notification to device users. Without any useful evidence of actionability for these scores or established relationship with health outcomes, it is hard to make a case for their value. At the Apple recent announcement they showed their Readiness score (0-10) on the watch (Figure below) but there are no published data on this score, not even on their website. It’s available only on their new Watch Series 12 or Ultra 4 [of course, ;-)]. That exemplifies the problems with these scores, lack of data and evidence for being meaningful to promote health. Perhaps the best study (which isn’t saying much) is the WHOOP Recovery for golfer performance, because it did correlate with an objective outcome, even though there was no control group and the authors were all from the company. Among the 389 pro golfers, an absolute 10-per cent point increase in Recovery score was associated with about 0.5 fewer strokes per round. But that’s hardly a health outcome! WHOOP is also conducting a study in over 2,700 runners to see if their recovery score will be linked to less injuries and improved performance, but that is not yet published and has no control group or randomization. Putting This in Context For two decades I’ve been enthusiastic about the potential for digital health and particularly wearable biosensors. Over the years, we’ve seen some great progress for their ability to promote physical activity and accurately detect atrial fibrillation (the first FDA cleared deep learning AI for consumers). That work was the subject of rigorous research. But there are holes in the data and evidence for other metrics. One notable one is the “VO2 max” story that I wrote about earlier this year. At that time many subscribers asked me to cover heart rate variability, which I finally got to here. When I dived into the research and publication for HRV and readiness scores, I expected to find at least some that were of high quality and demonstrated their utility by linkage to health outcomes. To my surprise, I found none. The wearable sensor measurements for HRV (PRV) are, for the most part, accurate, but that validation work has only been done in small studies of healthy adults and does not take into account the long list of factors, from the device, software side, and the user side, that affect HRV measurements. Moreover, this metric chiefly relies on optical sensing and, as we have learned for heart rate PPG sensing, may be less accurate in people of color. Keep in mind that all of the health outcome association evidence comes from ECG-derived HRV; none are from wearable sensor data. I will repeat the key point: there's no peer-reviewed evidence to show that in-person HRV fluctuation—or efforts to raise your HRV— has any correlation with health outcomes. For those of you who look at your HRV on awakening, or even 2+ week trends of it being low, I hope this context helps to relieve any anxiety. Yes, low HRV (not PRV) has been shown to increase risk of some diseases as summarized above. But efforts to raise your HRV—a surrogate metric— has not been established for improving any health outcomes. HRV does not have any evidence of causality (the genetic evidence actually goes against this possibility). In this summary, I have not included data for other wearable sensors such as Polar, Samsung, Withings, Suunto, Amazfit, Coros, Ultrahuman, or additional mattress sensors. These are beyond my first-hand experience, and as far as I know from my in-depth review none have any peer-reviewed published data that differ from the 6 sensors I’ve reviewed here. From the points I’ve gone over above, we’re not ready for readiness scores. Besides being proprietary, they are predominantly based on metrics that have their own issues. It’s compounding the problem, like building a house without a solid foundation that has never undergone a rigorous inspection, and then selling it. Like I mentioned for PRV, you can look at trends over weeks rather than any single day, to get a handle, but even that may not be helpful. There’s simply no evidence that these scores meaningfully relate to health outcomes. I’d emphasize they might, but that requires doing prospective or randomized studies to prove it. None exist. There’s great promise for HRV/PRV utility_. For example**,**_ Prof Maiken Nedergaard, who discovered the brain glymphatics that are essential in eliminating metabolic waste products from the brain during sleep, has posited that HRV could be a non-invasive marker for neuromodulator oscillations, brain-body regulatory circuits, and brain clearance. That would be extremely useful, but like everything else on HRV and readiness scores it requires solid research and validation. The lay media isn’t helping much to get the story straight. Earlier this year The Economist published a piece entitled “The most useful indicator of your overall health” which ordained HRV as an “accumulated stress score.” That’s akin to the false assertion about VO2max: “V02 max is the singular most powerful marker for longevity.” As I’ve summarized here, that is not established. The fact is that so many things can lower HRV, including physical exercise (especially an intense workout), reduced sleep quality, stress, the list above, no less the device, signal, and software. Whatever fluctuations observed have not been correlated with any health outcome. Sadly, “datamaxxers” are widely using HRV and readiness scores that have never been validated to mean anything. We already know that for some people using the sensors for sleep metrics, it can induce “orthosomnia,” an obsession to get high sleep quality, with associated high levels of anxiety. In an experiment done by a company to promote sleep quality for its employees, “For those employees who did use the trackers, many reported feeling perfectly rested until their tracker told them they had had a terrible night. Others were told that they had slept like a baby when they had actually been lying awake worrying about the quality of their sleep. “ The same problem can result from preoccupation with HRV or readiness scores, with anxiety that would lead to further reduction in both. It you are using a wearable like >100 million American adults, it’s OK to look at these data, but contextualized with the major caveats reviewed here. If you are one to require evidence that HRV or readiness scores are linked to health outcomes, you may not even want to look. The companies make it hard to turn them off! Let me end with the companies that make and sell wearables. Apple’s doubling down on HRV (24-fold more reporting and heart rate very 5 seconds) and introduction of a Readiness score tells us that consumers have bought into these metrics and they are joining the club. However, all of this is occurring with a backdrop of tens millions of users, claims about the data that are not backed up by adequate evidence, marketing way out in front of whatever limited data exists, and not being transparent about their readiness score algorithms. The companies can well afford to do the research that is needed to connect these metrics with health outcomes show, once and for all, that increasing HRV or using readiness scores promotes our health. If they believed and invested in the products they are selling, we’d not be in this position of not knowing. That’s essentially where we are with HRV and readiness scores. Perhaps someday this will change and we’ll have good reason to embrace them. NB: I wrote this post. No AI. I have no conflicts of interest with any of its content. Loading... Ground Truths has 215,000 subscribers from every US state and 214 countries. There are over 300,000 followers of Ground Truths so more than 90,000 folks who can easily convert to be free subscribers. Your subscription to these free essays and podcasts makes my work in putting them together worthwhile. If you’re not a subscriber, please join! If you found this interesting PLEASE share it! Share Ground Truths The proceeds from all voluntary paid subscriptions go to support our summer internship program. It enabled us to accept and support a record number of 62 summer interns that joined us in 2026! These are high school, college and medical students selected from thousands of applicants. We couldn’t do this expanded program without the funds coming in through Ground Truths. Thank you!
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Engrams Embedding Entendre: Codesign for Efficient DRAM/SSD Offloading
Engram extends standard token embeddings with learned multi-token lookups. Recurring local patterns retrieve vectors directly, reducing the need to reconstruct them through attention and feed-forward layers. With Engram model architecture optimization, it allows for lower HBM capacity to be needed for models at the same quality. This does not mean there won’t be an insane demand for HBM but it just means that model architecture will continue to innovate around constraints. This model architecture design is naturally codesigned for parameter offloading: each token accesses a few embedding rows whose addresses depend on token IDs, not hidden states. The runtime can prefetch those rows from host DRAM while earlier layers compute, keeping the table outside HBM without transferring entire weight matrices. Our Memory model contains our latest estimates of quarter by quarter HBM, DRAM, & NAND supply and demand. Offloading frees HBM for model weights and KV cache, potentially supporting larger batches or more concurrent sessions. When DRAM becomes the next constraint, NVMe offers another tier. Recommendation systems already cache frequently or recently accessed embedding rows in faster memory while backing colder rows with SSDs. After NVIDIA roadmap had to change due to massively despec’ing Rubin Ultra from 1024GB to now ~200GB of HBM per chip, model architecture optimizations like emgram maybe helpful. Our DeepSeek-V4.1-Flash configuration uses roughly 189 GiB of memory for Engram. We replace it with a memory-mapped (mmap) file and measure serving performance with offload to SSD. Later on in our report, we will show our Engram offloading experiments along with the official InferenceX agentic inference serving results on Engram models like DeepSeekv4.1 Flash across all 6 NVIDIA GPU SKUs along with MI355X. Unsurprisingly, the CUDA Moat is still mogging MI355X on the ultra popular DeepSeekV4.1 Flash model. We also show how even on high capacity HBM SKUs, offloading emgrams to DRAM could result in even better performance for most of the pareto than keeping the emgram in HBM. Our benchmark has been widely reproduced, validated and/or supported by almost every major buyer of compute from Google Cloud to Microsoft Azure to Oracle, to Meta and many more. Furthermore, it has the support of the ML community including from vLLM, LMCache, SGLang, PyTorch, Huggingface and the support of major labs like OpenAI, MiniMax, ZAI, Qwen, Moonshot Kimi, etc. Star the InferenceX GitHub repository if you find the open-source benchmark and data useful!. InferenceX is the only inference benchmark in the world to have TPUv7, Jalapeño, Nvidia Rubin NVL72, AMD, and soon, SambaNova and Trainium. Due to how realistic AgentX scenario is to real world agentic inference workloads, AMD has committed to collaborating on MI455X UALoE72 too. DeepSeek did not release the original paper’s two trained Engram models. We replicated its setup on fineweb-edu using the released code and training hyperparameters, at an estimated 6E18 FLOPs per run. We observed the same U-shape scaling: Engram improved performance over pure MoE baselines. We also reproduced DeepSeek’s results, where earlier-layer representations with Engram resembled those of later layers. Like the original Engram paper, it is possible to probe Engram’s gate scores to see what n-grams DeepSeek-V4.1-Flash makes the most use of. Our gate scan finds names, code fragments, relational phrasing, and boilerplate. These examples prioritize interesting-ness over gate strength. One unexpected result was Wright : Ace Attorney. These examples suggest learned memory optimizes the training objective, not a judgment of which facts deserve storage. Licenses, bibliography fragments, API scaffolding, and website furniture can provide prediction shortcuts, so the value of additional Engram capacity may depend on what survives data preparation. This does not show that table capacity is “wasted”: the evaluation-corpus scan establishes neither training exposure nor the capacity occupied by each category. For offloading, strong gates do not identify cache-hot rows. Low gates do not automatically save reads either: computing the gate requires the retrieved key and undoes the performance gain of a fused kernel. Skipping reads would require a separate usefulness predictor before retrieval. In the original paper’s inference-time ablation, factual-knowledge benchmarks retained just 29–44% of their original performance, while reading comprehension retained 81–93%. This is due to the training–inference mismatch. The resulting degradation therefore measures this trained model’s dependence on Engram, not the performance difference between models trained with and without it. In our ablations, suppressing Engram worsens token likelihood across all evaluated domains, especially encyclopedia text and several code corpora. Surprisingly, GSM8K accuracy stays within measured run-to-run variation and removing Engram has no effect. Engram is not a detachable dictionary beside an unchanged MoE. Removing it changes downstream features and expert selection. We tested whether rerouting hurts or compensates by holding tokens fixed in a teacher-forced experiment on CRUXEval, a code-reasoning benchmark of small Python functions where the model predicts a function’s output from its code and an input, and scoring the reference answer. Removing Engram raised answer loss from 0.2848 to 0.3093 bits/token. Forcing the ablated model to use the original Engram-on expert choices made it worse still, at 0.3375 bits/token. Rerouting partially compensates for the missing memory. Memory features and expert selection work together, rather than following a clean “memory stores facts; experts reason” division. On the same CRUXeval, removing Engram during either phase reduced accuracy and increased generated tokens; removing it throughout produced the largest changes. Keeping Engram for prefill leads to more correct answers than keeping for decode likely due to semantically richer KV cache transferred to decode workers, allowing it to mitigate some of the performance loss. Engram’s table is large, but each lookup is small. DeepSeek-V4.1-Flash requests 24 rows at each of two Engram layers, about 12.4 KiB per processed token position across the model, or 3.1 KiB per GPU when split across four GPUs. Currently as of Day 7 since Model Release, MI355X is still 2-4x worse performance per dollar compared to B200 even when normalized by Mi355X’s lower TCO. Our full total cost of ownership breakdown comes from our AI Cloud TCO Model along with monthly market surveys of over 100+ gpu clouds & gpu cloud customers. On the Day 0 release of DeepSeekv4.1 Flash, NVIDIA vLLM works out of the box with zero issues across all 6 SKUs: H100, H200, B200, B300, GB200, GB300! This was thanks to the amazing work by the NVIDIA & Interact teams! In comparison, AMD vLLM did not work on day 0 for DeepSeekv4.1 Flash.Source: SemiAnalysis InferenceX AMD’s vLLM documentation points to using vllm/vllm-openai-rocm:deepseekv41-flash-0909, but from hour 0 of the model release to hour 23, AMD has not publicly released the image. AMD claims, “SPEED IS THE MOAT,” yet it has still not released it by the 23rd hour. We wish that, going forward, the AMD team has a better process for hour 0 model releases. Eventually when they did publicly release for “day 0” image support, performance-wise, it is currently up to 14.8x worse perf per dollar than H200 and up to 42x worse perf per dollar than B200/B300. The power of the CUDA MOAT is NVIDIA’s collaboration with its massive 6 million-developer community ecosystem including most of the vLLM & SGLang & Tokenspeed maintainers which means that CUDA is optimized on day 0. Overall, AMD did make significant improvements but the performance per dollar is still currently 2-4x worse than B200. AgentX Engram DRAM Offloading Improving Performance The HBM and DRAM offload use the same GPU kernel to select and dequantize rows. With HBM, it reads GPU memory; with Unified Virtual Addressing (UVA), it reads pinned host memory directly. Both support full decode graphs. Moving the table into HBM accelerates only the sparse lookup, leaving decoder computation and communication unchanged, resulting in little overall benefit while consuming memory otherwise available to KV cache. Another benefit of Engram offloaded to DRAM which means you can reduce the communication overhead by using less HBM GPUs per replica. For example, when enabling Engram offloading on B300, we are able to switch from TP4 to now TP2 which improves the pareto curve by up to 1.6x. When iso-model quality, less HBM is required as the engrams could be offloaded to host DRAM. Thus HBM bandwidth matters way more than HBM capacity. For inference workloads where memory bandwidth matters the most, 4-hi HBM provides the best $/bandwidth and therefore lowest cost per token. If China continues to make more and more revolutionary model architecture innovations, soon it could potentially 0Hi HBM stacks. [ ](https://newsletter.semianalysis.com/p/long-live-the-short-king-why-4-hi) [ Long Live the Short King: Why 4-hi HBM Wins ](https://newsletter.semianalysis.com/p/long-live-the-short-king-why-4-hi) Myron Xie, Bryan Shan, and 3 others · Sep 13 [ Read full story ](https://newsletter.semianalysis.com/p/long-live-the-short-king-why-4-hi) Moreover, on B300 and week-0 stack, moving the Engram table back to HBM did not improve results and stay within run-to-run variance. This is a result of the work optimizing DRAM offload, such as async, and overlap. SSD Offloading On B200, we created a unoptimized vLLM fork and stored the Engram tables in memory-mapped files on local SSDs. File backing lets the OS reclaim table pages when other applications need RAM. Pages already cached in memory can be served without reading the SSD again. Furthermore, note that we were unable to turn on GDS The unoptimized SSD implementation changes how rows reach the GPU. It copies row IDs to the CPU, deduplicates them, gathers the requested rows into pinned buffers, copies those rows back to the GPU and dequantizes them. This work runs between segments of the GPU execution graph. Native UVA performs row selection and dequantization directly on the GPU, avoiding the CPU round trip. A warm filesystem cache removes physical SSD reads, but leaves the coordination, row gathering and transfers. This is why a file already cached in RAM can still perform worse than a pinned DRAM table. The comparison measures the whole serving path; it does not separate the time spent on each of these operations. B200 DRAM dominates both measured SSD serving curves in total tokens per dollar and P90 interactivity. Near 125 tokens/s/user, DRAM delivers 121 million total tokens per dollar versus 52 million for SSD. For production serving, SSD offloading is likely not worth the tradeoff. On the B200 configurations we measured, SSD offloading loses on both measures: every observed SSD point has a DRAM alternative that delivers higher P90 interactivity and more total tokens per dollar. The only points where Cheaper storage does not automatically produce a cheaper inference service. Moving Engram to SSD leaves the same four expensive GPUs and the rest of the server in place. Reclaiming RAM only creates an economic benefit if it enables a cheaper server configuration or additional useful capacity. The current unoptimized path provides neither benefit, and the filesystem cache still consumes RAM when table pages are resident. Next we will look at the mechanisms and specific implementation of ngrams from DeepSeekv4.1 Flash, LongCat, Qwen3.8 Flash Next.
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What Does the Science of Climate Change Really Look Like?
Editor’s Note: This is the second in a three-part series on how the Right should think about environmental and climate policy. Read Chris Barnard on Reclaiming Environmental Policy from the Left. More than a decade ago, the world’s governments negotiated and signed the Paris Climate Agreement, committing to hold global warming well below 2 degrees Celsius. In the following years, climate had immense cultural power. Greta Thunberg emerged. Fortune 500 companies established net-zero plans. The U.S. got the Inflation Reduction Act. Then the pendulum swung back. President Donald Trump returned to the Oval Office, speaking of green energy as a “scam” and carbon footprints as a “hoax” and on all matters of international policy emphasizing bilateral engagement and power over globalism and cooperation. The technology companies that had been at the forefront of net-zero pledges and green leadership discovered the importance of all-of-the-above power to their visions for artificial intelligence and began quietly postponing or removing their targets. On the left side of the political spectrum, rising concerns about inflation and cost pushed climate lower down in the stated priorities of voters and stump speeches of politicians. The moment is ripe for a reset on the politics of climate change and for conservatives especially to chart a course that acknowledges and addresses the real challenges in plausible ways. So what should we think about climate change as we enter a post-peak climate era? If it is neither an apocalypse nor a hoax, what will hold up as a durable view of climate change? And how does it project onto the concerns and priorities of the right-of-center’s emerging coalition? New to Commonplace_? Subscribe below to get the magazine in your inbox._ Subscribe A Solid Foundation As the politics and economics of climate careened over the past ten years, the physics carried on regardless. In 2015, the year the Paris Climate Agreement was adopted, the world emitted 41.2 gigatonnes of carbon dioxide. By 2025, emissions had risen only 2.4%, to 42.2 gigatonnes, because falling emissions from land use offset increasing emissions from fossil fuels. But slow growth in annual emissions is not rapid decline, let alone net-zero, so carbon dioxide kept accumulating in the atmosphere, going from 399 to 426 parts per million. Global temperature kept rising too, from about 1.1 degrees Celsius above the 1850–1900 average in 2015, to 1.4 degrees above it in 2025. None of this should surprise anyone. Even most prominent skeptics, like the authors of the 2025 report commissioned by the Trump administration’s Department of Energy, accept the basic physics. Carbon dioxide added to the atmosphere at industrial volumes accumulates and traps heat that would otherwise escape to space. That heat warms the upper ocean and increases temperatures at the surface. Increased ocean heat and melting of land ice cause sea levels to rise. Changes in the climate become noticeable to us as subtle shifts in temperature and precipitation, seasons arriving early or late, changes in the surrounding ecosystem, and weather extremes. The much more meaningful debate is not about whether these things are happening, but about what it all means for human societies. (While it is a proxy measure of overall risk, no one experiences global surface temperature.) This debate invokes at least three interesting questions: how much today’s warming is showing up in regional climate trends, how much more warming we should anticipate, and how extreme weather events can be understood in the context of climate change. Recent scientific advances give us new insights into each of these, but there is still much to learn. This is the context in which the next generation of conservative leaders will be the first to deal with significant climate change as a fact, not a forecast. It will be with them for their entire careers. Our evolving scientific picture of climate change will come from weather and climate records stretching further into the past, new kinds of observations in the present, better modeling tools for the future, and simply more time to observe the emergence of climate signals and their tangible effects on ecosystems and communities in the United States and around the world. The policy landscape will be shaped by not only the impacts of changes in the climate, but also by the ways in which societies respond and by the emergence of new technologies for both altering the trajectory of emissions and adapting to new climate realities. Global climate records now show the fingerprints of warming in different phenomena around much of the world. The IPCC, in its most recent assessment report, documents warming trends over all land regions, even as natural variability adds substantial variance to local trends. And the highest temperature extremes have become more intense and frequent, almost everywhere, since the 1950s. Scientists are highly confident that these changes are attributable to human influence. But confidence in detecting trends and attributing them to human influence degrades across heavy precipitation events; drought trends are heterogeneous and not attributable to human activity with great confidence. For hurricanes, tornadoes, and other severe storms there is even less confidence in trends or their relationship to climate change. In general, a fair summary of the evidence is that for well-observed phenomena, like surface temperature or heavy rainfall, with a clear relationship to warming, our multidecadal observations are consistent with human influence overcoming natural variability over long time periods and extremes increasing. For regions that are sampled more sparsely, or phenomena with a higher noise-to-signal ratio, we will need to observe them longer to understand the magnitude of the climate signal or improve dynamical understanding using models and observations together. But for Climate For those who can’t wait, we also have new techniques that attempt to understand the role climate change has in influencing particular extreme events. When the climate is changing and disaster strikes, it is natural to ask whether that disaster was somehow “caused” by climate change. For scientists and policymakers acting in good faith, answering that question helps develop a more accurate picture of the problem, how it may be getting worse, and what preparations we should be making to respond to it. It may, at some point, give some weight to how liability is assigned by courts or adaptation funding is distributed by society. But how we ask this question is extremely important. It is easy to get the analysis wrong by discounting the role that meteorology plays. As meteorologist Theodore Shepherd explained in a clear 2016 review of climate attribution methods, “if a weather or climate event is truly extreme in the present climate, then perforce it requires unusual meteorological conditions, which means that climate change is at most a contributing factor.” Share Scientists have two ways to probe climate as a contributing factor, both of which have entered media coverage of extreme weather events. One asks a probabilistic question: How much more likely is a particular event (e.g., a temperature record over a particular area) amid global warming? The answer involves using historical records and computer simulations to estimate the likelihood of such an event in both a changed and a preindustrial climate. The findings are less about the specific event, and more about events of that nature. The other question is: How has the changed climate affected the specific event in question? Here, scientists try to understand what a similar event would have looked like in the preindustrial climate. This is sometimes called the storyline approach, where the story is the specific meteorological details of the event. These methods offer ways to test the intuition of scientists about real weather extremes. In late June and early July of 2021, a persistent high-pressure ridge, or heat dome, set up over the Pacific Northwest and an extraordinary heat wave affected the area from Oregon to British Columbia. For six days, it shattered temperature records across the region and hundreds died from heat-related causes, in an area where such high, and persistently high, temperatures were well outside of experience and many live without air conditioning. Scientists have studied its connection to climate change using multiple approaches. This specific event was created by a rare combination of meteorological factors, a strong high-pressure ridge created the conditions for extreme heat, which occurred on top of higher average temperatures in the region from global warming. Probabilistic analyses showed that climate change increased the likelihood of such an event by at least 8-fold to more than 100-fold. One standout example found that such an event had effectively zero probability of occurring in the preindustrial climate. The enormous range in these assessments reflects how hard it is to estimate probabilities of events at the tail of the historical record. Estimates of the effect on the temperature of the event are more clustered. A recent review paper documents how multiple methodologies have found a positive influence, roughly 1-2 degrees Celsius of an anomaly that exceeded 15 degrees, of climate change on the temperature magnitude of the event. Multiple studies have investigated and found some positive influence of climate change in other extreme events. Attribution studies found climate likely increased the heavy rainfall that accompanied Hurricane Helene in North Carolina and surrounding regions in 2024. The extensive fires that struck Los Angeles in 2025 illustrate how the causal chain can become messy, though. Studies do detect a positive influence of climate on the event’s likelihood, but while climate change likely contributed to underlying aridity, it would not have played a role in the heavy winds or land practices that preceded disaster. These event attribution studies will become more common for extreme, or damaging, weather events. They can be produced quickly, and often are reported before peer review. As the Pacific Northwest heatwave example shows, when multiple methods converge on a positive attribution, the finding should probably carry some weight even if you have to be careful about accepting the results from a single study. I expect that as climate change proceeds and the climate thus departs further from a preindustrial counterfactual, the influence will become more detectable across a variety of extreme events and more easily identified. This will be used to cast blame, but can also be used to inform how communities and society adapt to ongoing change. We May Still Be Surprised One positive development, insofar as less climate change is better, has been that our central estimates for future climate change should probably be revised downward. Mostly, that is because the high-end warmings that scientists regularly analyzed about ten to 20 years ago, driven by high emissions throughout the twenty-first century, now appear to be somewhere between unlikely and impossible. At one time, the upper end of mainstream climate projections extended well into 4 to 6 degrees Celsius of warming by the end of this century, which, models suggest, would have wrought enormous real-world damage. Current energy and policy trends now point toward 2.5 or 3 degrees. Damages and risks are commonly modeled as increasing steeply with more warming, so this is already a better-than-previously-expected outcome for the climate (which is independent of the physical response to emissions). But we should maintain a wide range for plausible outcomes and prepare for the possibility of being surprised. Emissions trajectories are subject to deep uncertainty, the physical climate response is still developing, and whatever change occurs in the climate will then be mediated through unpredictable economic, social, and political institutions. Over the past decade, the pace of warming surprised some keen observers and appeared to accelerate, though not yet outside the range of expectation provided by climate models. The reasons for that apparent acceleration are being actively studied (as was the apparent pause in warming from 1998 to 2012), but no single driver has emerged. Some blame it on the El Niño, variability which would have no bearing on climate. Some think it is a result of factories in East Asia and global shipping fleets cutting aerosol emissions, which in the strongest version of the argument would indicate higher climate sensitivity to carbon-dioxide emissions. Others are more measured, not yet ready to draw solid conclusions as to whether climate projections require revision. We will have to see. Long-Term Thinking Climate change asks us to think over long time scales. But the pace of human-driven warming is compressing a large global change into a century. Changing weather patterns and extreme events are already causing adjustment costs and damages and will do more. Adaptation will help, but it is not free. For some communities, these costs will erode livelihoods and well-being, and may force migration. Are we prepared for large-scale managed retreats in the United States? Thankfully, American wealth, geographical diversity, and moderate climates may leave us better prepared than many around the world. But wealthy countries can still suffer serious disruption from narrowly concentrated costs, even if they appear entirely manageable in aggregate. Readers of Commonplace are familiar with the challenges of rapidly adapting to economic forces. The displacement that came from the China Shock is barely perceptible in aggregate GDP and employment data, but it affected millions of people and those people were far less mobile than economic models tended to assume. Deindustrialization rippled through the nation with enormous effects for not only our economic vitality, but also our national security. The forces surrounding climate change may not be so different; the world gets richer and must accept some diffuse costs. Those may be modest overall, but cause all manner of unpredictable effects with which policymakers must cope. In the case of the China Shock, our faith in a growing pie served us poorly. We’ll need to do better on climate. Leave a comment
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