Could Florida's St. Johns River witness flash floods similar to Texas that claimed 120 lives?
According to the National Hurricane Center, several tropical waves this week could turn into more significant storms, but no catastrophic activity is predicted for the next week.
Forecasters are particularly monitoring the region where storm Chantal formed earlier this month. Dexter will be the next named storm of the hurricane season.
Meteorologists and scientists are warning about the effects of Trump's severe cuts to scientific organisations.
In late June, the National Oceanic and Atmospheric Administration (NOAA) announced that the Defense Meteorological Satellite Program (DMSP) would 'discontinue ingest, processing, and distribution of all DMSP data no later than June 30, 2025, ' Irish Star reported.
NHC monitoring four tropical waves
The National Hurricane Center is keeping an eye on four tropical waves that have the potential to intensify into more severe storms.
Although the tropical Atlantic is predicted to stay calm for the next few days, forecasters caution that there is a less probability of another tropical depression or storm developing from July 15 to 18 in the same area along the southern Atlantic coast, especially the northeast Gulf, which they were tracking closely in early July.
An extended region of comparatively low pressure that travels from east to west throughout the tropics is called a wave. It may result into a development of tropical cyclone.
Also Read: Photos: Trump, Melania tour flood-ravaged Kerr County as President vows Texas relief; 'Never seen anything like this'
Could Texas-style flash floods occur on the St. Johns River?
According to Jessie Schaper, a meteorologist and hydrology program manager at the National Weather Service in Melbourne, there is a slim likelihood of flash floods along the St. Johns River, despite the fact that Florida has an abundance of the moist tropical air that led to the rainfall which triggered the devastating floods in Texas, reported Daytona Beach News-Journal.
On being asked about the possibility of flash floods in Florida, Schaper stated, 'Absolutely not.'
'We do not have the terrain here that they do in Texas Hill Country, so that type of thing we'd never see on the St. Johns,' she stated. 'It is a very slow-moving river. It drains a large area, but it's essentially flat.'
Over its 310-mile course, the St. Johns River has an extremely modest elevation drop of less than 30 feet. The St. Johns River Water Management District claims that it is one of the 'laziest' rivers in the entire world, with an average dip of roughly 1 inch every mile.
The soil, which soaks water very quickly, is another significant distinction between Florida and Texas, according to Schaper.
The Guadalupe River overflowed after heavy rains on July 4th, causing flash floods in Texas that claimed lives of at least 120 people and left several others missing, as per AP. It is worth considering whether the St. Johns River in Florida could experience the same devastating flooding.
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The recent flash floods in Texas underscore that lives are at risk from extreme weather events that climate change has made more common. And researchers have found that shorter forecast lead times since 2009 have prevented hundreds of millions of dollars in hurricane damage -- per beyond headline-making events, the weather next week has economic implications. Businesses of all stripes make or lose money based on the forecast: retailers with far-flung supply chains, energy companies moving fuels around the country, even baseball teams watching for a good news is that we may be poised to enter a new golden age of AI-enabled weather prediction. That heat wave that scorched the East Coast last month? WindBorne says its software first flagged that 15 days out, two to four days before competing forecasts. There's a catch, though. These new deep learning forecasts are built on data provided for free by public science agencies. In the United States, that relationship is threatened by the Trump administration's heavy cuts to the National Oceanic and Atmospheric Administration, or NOAA, which houses the National Weather Service. The Public-Private Symbiosis Every day, at more than 100 weather stations across the United States, a weather service worker fills a latex balloon with helium and launches it to collect atmospheric measurements -- until it flies too high and pops. These flights, which began in the 1930s, have been reduced because of staff cuts during the chaotic first months of the second Trump the government, from the National Aeronautics and Space Administration to the Pentagon, the Trump administration's appointees have aimed to push the government's technical capacity into the private sector. Some in the weather industry -- and free-market Republicans -- see NOAA's forecasting work as a prime candidate for outsourcing and have called for the agency to be "dismantled." 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The software could be learning physics, simply matching patterns or using some effective combination of the two."When you do a physics-based model, you're being smart," Creus-Costa said. "When you do a deep learning model, you don't have to be smart. We're not writing down the physics. We're just having it learn."Using artificial intelligence modelling, WindBorne says, its day-ahead temperature forecasts are 37% better than those performed by the European Center for Medium-Range Weather Forecasts, an organization that supports the European equivalents of the National Weather Service. (WindBorne releases the data so others can validate it.)In addition to NOAA, the startup sells its weather insights to investment funds and is working with arms of the U.S. military, which has a vital interest in the weather. The Limits of Deep LearningFor all the excitement about these new techniques -- Microsoft and Google also have AI weather models, as does the Air Force -- they have their Chantry, a mathematician who leads the operational AI weather forecasting project at the European Center for Medium-Range Weather Forecasts, said the field of meteorology was still figuring out what the relationship between physics-based and AI models would be. The weather service, whose forecasts have fallen behind those at the European center, does not operate its own AI forecasting model, but teams up with private companies to support their learning models have proved uniquely useful for complex events that are tricky for physics-based models, like the paths of hurricanes or cold fronts over the Midwest, a notably tricky place to forecast because of the Rocky models tend to be better at analyzing fine details. AI forecasts typically cover areas of 25 to 50 square miles. Most people need to know the weather in a much smaller area; government-run physics models analyze areas of around 6 square miles or less. WindBorne spotted heavy rains before the Texas floods, but not with the kind of granularity to deliver evacuation warnings. The company's goal is to reach a much smaller resolution in the years ahead, said Todd Hutchinson, WindBorne's chief the influential weather-model creator, said WindBorne "is one of a few companies trying to do both data acquisition and also do the modelling." He added, "They also seem to be quite good at both."The Trump administration's cuts have imposed another limit, too. For now, weather forecasting models based on deep learning remain dependent on data releases from the physics-based models at the public weather agencies. Those paint a wide-ranging universe of observations onto a 3D grid as often as four times a day, from which the AI models can learn. Keisler cofounded Brightband, a company that is developing software that can ingest observation data directly into AI models, but its work is in its early President Donald Trump's inauguration, NOAA employees have been pushed to resign, resulting in nearly 2,000 departures. While the White House budget doesn't reduce forecasting spending directly, it cuts spending on satellite and radar systems, and Trump's recently enacted domestic policy bill cut millions of dollars in leftover Biden administration funding for improved forecasts. Some changes seem ideological -- the removal of a data set about extreme weather events -- while others baffle meteorologists: NOAA will no longer distribute data from a U.S. military weather satellite program that is seen as vital to hurricane nominee to lead NOAA, Neil Jacobs, who was cited for violating the agency's code of scientific ethics during the president's first term, endorsed the White House's cuts at his confirmation hearing last week, but also promised to restore the extreme weather data set and invest in computing. He told lawmakers that "even if artificial intelligence can't do something better, if it can do it faster and more efficiently, I think it's worth using."Congress could still reverse some or all of these cuts through the budget process in the months ahead, but current and former members of the weather service's staff say the loss of data and human expertise will degrade the accuracy of forecasts and potentially endanger lives."We will continue to fulill our core mission of providing lifesaving forecasts, warnings and decision support services," a NOAA spokesperson said in a the fast changes happening in U.S. weather research put WindBorne in a complicated spot. The company needs NOAA's data, wants its business and hopes to do a better job of forecasting weather than the government currently can -- but the team of balloon-flying, AI-training techies are regular people, too."I have my personal philosophies that are not aligned with, like, what's best for our private weather company," Dean told me. "You don't want to live in this capitalist nightmare of like, 'Pay 10 bucks for today's weather.' That's too far."
