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E&E News
4 days ago
- Climate
- E&E News
‘Biggest, baddest' rainfall events are getting worse
Texas hill country. Central North Carolina. New Mexico. Chicago. Kansas City. New York. Flash floods have wreaked havoc across the country this summer, transcending geography, topography and the built environment from the rural Southwest to the largest cities in the Midwest and Northeast. The outcomes have been fueled, in each case, by slightly different factors. Hard concrete surfaces in Chicago and New York forced rainwater to pool in the streets or pour into the subways. Wildfire scars near Ruidoso, New Mexico, left the soil loose and vulnerable to floods. Hilly terrain in Kerr County, Texas, sent runoff cascading into the nearby Guadalupe River, which swiftly overflowed its banks. Advertisement But a common ingredient triggered them all: explosions of torrential — and in some cases, record-breaking — rainfall. These heavy precipitation events are among the clearest symptoms of climate change, scientists say. Copious studies warn that they're already happening more often and becoming more intense, and they'll continue to worsen as global temperatures rise. And the most catastrophic rainfall events may be worsening the fastest, some experts say. 'The biggest, baddest, rarest extreme precipitation events are precisely those which are going to increase the most in a warming climate,' Daniel Swain, a climate scientist at the California Institute for Water Resources, said in a live YouTube talk shortly after the Texas floods struck in July. 'There is really abundant scientific evidence for this at this point.' Intensifying rainfall events are the product of simple physics, scientists explain. A warmer atmosphere can hold more water, increasing the odds that moisture-laden clouds will drop rainfall bombs when they burst. That rule has been well established for nearly 200 years. A 19th-century equation known as the Clausius-Clapeyron relation — still widely referenced by researchers today — dictates that air can hold about 7 percent more moisture with every degree Celsius of warming. But in recent years, scientists have noticed an alarming trend. Extreme storms in some parts of the world appear to be defying the Clausius-Clapeyron relation, producing far more rainfall as temperatures rise than the equation would predict. One recent study examined the influence of climate change on the unusually active 2020 Atlantic hurricane season. It noted that extreme short-term rainfall rates produced by the 2020 storms appear to have scaled at about twice the rate suggested by the Clausius-Clapeyron relation, given that climate change has warmed the Atlantic Ocean basin by as much as 0.9 degrees Celsius. In general, there's increasing evidence that the 'most intense convective downpours — meaning the heaviest torrential rain events from thunderstorms, specifically — are already increasing at a rate that greatly exceeds that of other types of precipitation,' Swain said. It's a phenomenon scientists have dubbed the super-Clausius-Clapeyron rate. Researchers are still investigating the reasons it's happening. At least one recent study, published in April, suggests the trend could be a statistical quirk caused by an increase in the frequency of thunderstorms compared with milder rainfall events. In other words, it's not that the storms themselves are defying established physics — the strongest kinds of storms are just becoming more common. That study focused only on storms in Europe, meaning more research is needed to understand what's happening with rainfall events around the globe. Still, the authors note that rainfall rates are clearly increasing faster than expected in some cases — and that's a trend scientists should account for when making projections for the future. At the same time, researchers have pointed to other ways climate change may be supercharging the worst precipitation events. One recent study warns that long-lasting summer weather patterns, such as extended heat waves or lingering storms, are on the rise — and physical changes in the atmosphere, driven by global warming, may be to blame. When already heavy rainfall events stall in place, they can dump massive volumes of water on a single location, triggering life-threatening floods. Put together, the science suggests that communities should prepare for record-breaking storms and flash flood events to continue worsening across the U.S., researchers warn. These events have been 'significantly underestimated as a hazard in a warming climate,' Swain said in his YouTube talk. 'There's a lot of evidence right now with the most recent science … that these are precisely the kinds of events that are going to increase the most, and in fact already are, and much faster than 'ordinary' precipitation events.'
Scientific American
15-07-2025
- Climate
- Scientific American
AI Couldn't Forecast the Texas Floods
CLIMATEWIRE | Artificial intelligence is showing promise when it comes to weather forecasting, but it still couldn't predict the Texas floods. The best-performing weather models during the July 4 floods were traditional ones specially designed to produce local forecasts at high resolution. Global-scale models were far less accurate — and so were AI models, weather experts say. 'All those new fancy AI models? They missed it too,' said Daniel Swain, a climate scientist at the California Institute for Water Resources, in a live YouTube talk on July 7. On supporting science journalism If you're enjoying this article, consider supporting our award-winning journalism by subscribing. By purchasing a subscription you are helping to ensure the future of impactful stories about the discoveries and ideas shaping our world today. Some meteorologists say that could change. AI weather models are starting to exhibit an ability for deep learning of atmospheric physics, which means they could be capable of forecasting unprecedented weather events based on atmospheric conditions. New AI models are "certainly capable of predicting 'out-of-sample' events — events that they haven't seen before,' said Corey Potvin, a scientist at NOAA's National Severe Storms Laboratory in Norman, Oklahoma. But looming budget cuts at NOAA — along with years of lagging federal investment in AI weather systems — are a major hurdle for the improvement of federal AI weather models, experts say. It's the latest example of how President Donald Trump's efforts to shrink government could hobble the country's weather forecasting capabilities, at a time when extreme weather is on the rise. Kim Doster, NOAA's director of communications, said in an email that budget cuts would not negatively impact the agency's research and forecasting priorities. Commerce Secretary Howard Lutnick, head of the department that houses NOAA, "is committed to integrating advanced technologies like AI to deliver the fastest, most accurate data to Americans," she said. "This administration is working hand-in-hand with meteorologists and scientists to modernize research, cut forecast lead times, improve mapping, and streamline operations across the bureau." Today's most advanced AI weather prediction models largely exist in the private sector. Many of them failed to see the Texas floods coming with the same accuracy as the high-resolution traditional forecasts. One major reason is that many AI models are still focused on forecasting large-scale weather patterns at the global level, according to Russ Schumacher, a meteorologist at Colorado State University and Colorado's state climatologist. 'Forecasting precipitation at the local scale is very challenging, and has not really been the focus of most of the AI models in use now,' he said in an email. That's despite some recent suggestions that the Texas forecasts could have benefited from more investment in AI prediction at the National Weather Service. Tim Gallaudet, who served as acting NOAA administrator during the first Trump administration, suggested in a July 7 op-ed that NWS should 'incorporate more artificial intelligence' into its atmospheric, oceanic and hydrologic modeling systems for more accurate forecasts during incidents like the Texas floods. But some scientists have expressed concerns about AI's ability to forecast record-breaking weather events, like the extreme rainfall that triggered the Texas floods. AI systems are often trained on historical weather data, and extreme events are — by definition — rare. That means there aren't many examples of them for AI systems to learn from. In a 2023 comment published in the scientific journal Nature, weather experts Imme Ebert-Uphoff and Kyle Hilburn warned that AI systems are 'often unpredictable when the program operates under conditions that it has never encountered before,' adding that extreme weather events 'might therefore trigger highly erratic predictions.' Potvin predicted new AI models could forecast rare events, though not quite as accurately as they would if they had lots of examples to train on. And although most AI models are still focused on large-scale weather patterns, high-resolution models are likely on the horizon. NOAA is working on some local weather-modeling projects that include AI components. The National Severe Storms Laboratory's experimental Warn-on Forecast system, or WoFS, is designed to rapidly incorporate radar and satellite observations into a high-resolution model. It can produce updated forecasts about every 15 minutes, increasing meteorologists' ability to accurately warn communities about sudden extreme events, like flash floods. NSSL scientists are also perfecting an AI version of WoFS, known as WoFSCast. By design, it can only perform as well as the original non-AI model — but it can theoretically produce forecasts much faster and with far less computing power, making it a cheaper option for local NWS offices. There's also NOAA's High-Resolution Rapid Refresh model, known for its ability to forecast storms at the local scale. HRRR was one of the models that best predicted the rainfall in Texas — and scientists are developing an AI version as well, a model known as HRRRCast. 'As far as I know, WoFSCastand HRRRCast are the only [AI] models currently being developed for higher resolution prediction,' Potvin said. Lag in investment NOAA still lags far behind the private sector when it comes to investment in AI weather prediction. That's a big concern for NWS forecasts, some experts say. AI is swiftly becoming a new frontier in weather modeling, and it could easily become an asset to NWS meteorologists — if NOAA had more resources to invest. 'The private sector is well ahead of where NOAA is now, to the point that even if we were in normal budget cycles, I'm not sure they could catch up,' Mary Glackin, former president of the American Meteorological Society, said at an AMS-hosted panel last week. Meanwhile, the White House has proposed around $2.2 billion in cuts to NOAA in its budget request for fiscal year 2026. Chief among these is the elimination of NOAA's entire research arm. That includes the agency's large network of cooperative research institutes and laboratories, like the NSSL, where researchers are still improving forecasting systems like WoFS and its AI counterpart. Scientists have warned that these cuts would damage NOAA's weather forecasting capabilities, putting communities at risk when extreme weather events strike. The private sector alone can't make up for lagging federal investments in weather forecasting technology, scientists and meteorologists have warned. Agencies like NWS are invested in public service and free forecasts, with the aim of ensuring that all U.S. communities — even those with limited resources — have access to high-quality, life-saving weather warnings. More public-private partnerships could help NOAA get a jump on AI weather system development, Glackin suggested. Such an arrangement 'meets the needs of the private sector, who are looking for a profit and a competitive edge, but remains true to the public service concept and not leaving the least behind,' she said. But such partnerships require the continued existence of research infrastructure at NOAA — which might not survive if Congress follows through with Trump's proposed cuts. Meanwhile, AI isn't the only frontier in weather forecasting. Traditional weather models also improve year over year as scientists collect and incorporate more data. That's how hurricane forecasts become so advanced over the last few decades. "As big a fan as I am of AI, it would be a mistake to put all of our investment into AI and then neglect the traditional side of weather modeling,' Potvin said. 'Because that in the end, would be undercutting future AI development.' Meteorologists have warned that traditional weather forecasts will plateau — or even degrade — if Trump's proposed cuts go into effect and hamstring NOAA's research capabilities. 'I worry about the loss of investments in science,' Brad Colman, another former AMS president, said at the July 10 panel. 'That's our seed corn, and the impact of that will be long-lasting. So I really hope that a greater wisdom will prevail, and that we will maintain that capacity.'
