In October 2024, Hurricane Milton was one of many fastest-growing storms on document over the Atlantic Ocean. The hurricane’s speedy achieve in depth caught meteorologists off guard, which meant the affected communities had been stunned too. The storm finally claimed 15 lives and triggered US $34 billion in damages because it tore throughout Florida.
Why was Milton’s explosive progress so onerous to anticipate? This failure stemmed from a scarcity of fine climate information. The type of information you may get solely by flying a suitably outfitted aircraft straight right into a growing storm. One of these mission requires human pilots to place their lives in danger to launch dropsondes—sensors dangling from parachutes—that may collect essential atmospheric measurements. If meteorologists can get that treasured information in time, they’ll typically use it to supply life-saving predictions.
WindBorne’s high-tech climate balloons keep aloft for weeks, a substantial enchancment over the hours that at this time’s customary climate balloons spend within the environment. WindBorne Programs
However hurricane hunters can fly solely so many missions, and most storms develop in locations that plane can’t safely attain, comparable to over huge ocean expanses. So we’re left with large information gaps exactly the place essentially the most harmful climate begins.
WindBorne Systems, the corporate I cofounded in 2019, is pioneering a greater technique to predict the climate. Our strategy begins with cutting-edge climate balloons and ends with our proprietary AI weather-forecasting system. Hurricane Milton’s dramatic arrival final yr gave us our first alternative to look at such a climate system instantly and to foretell a hurricane’s path because the storm advanced.
The WindBorne crew arrives earlier than daybreak to arrange a balloon launch at Bodega Bay, Calif. Christie Hemm Klok
At WindBorne, primarily based in Palo Alto, Calif., we’ve developed a classy sort of long-duration climate balloon. These World Sounding Balloons (GSBs), as we name them, can maneuver by means of the environment and comply with dynamic flight paths by browsing the winds. Within the lead-up to Milton, we launched six of these balloons, carrying dropsondes, from a protected distance away, in Cellular, Ala. Inside the subsequent 24 hours, the balloons had been in a position to enter the hurricane and launch their dropsondes to measure temperature, strain, and humidity, together with wind speed and path—data that doubtlessly might have helped forecasters decide precisely how the hurricane would behave.
The sensors that acquire climate information for every World Sounding Balloon are encased in plastic. Christie Hemm Klok
This dropsonde deployment, the primary ever by climate balloon, demonstrated that it’s doable to launch airborne sensors with out the same old prices and dangers to human life. And when our staff ran the collected information by means of our AI-based forecasting mannequin, WeatherMesh, its predictions of Milton’s path had been extra correct than these from the U.S. National Hurricane Center. Alas, as a result of our dropsonde launch was an experiment meant to check our expertise’s capabilities, the outcomes we obtained couldn’t be disseminated to the general public in actual time. Nevertheless it was however a fantastic accomplishment: WindBorne proved definitively that AI forecasts can outperform the type of climate fashions our society has relied on for many years.
Our mission at WindBorne is to construct what we liken to a “planetary nervous system”—an end-to-end AI-based forecasting system that may collect huge quantities of climate information and remodel that information into correct and well timed forecasts. Simply as an individual’s nervous system continually sends data from all components of the physique to the mind, our planetary nervous system gathers observations from all around the Earth and sends them to our AI mind.
Our system, which requires each superior data-collection {hardware} and complex AI modeling, can radically enhance how folks use climate predictions to make choices in areas comparable to nationwide protection, renewable energy, and agriculture. With climate change rising the frequency and cost of extreme weather occasions like Milton, we hope to supply higher forecasts to assist society navigate this new actuality.
WindBorne’s Stanford Origins
WindBorne began as a 2015 venture within the Stanford Student Space Initiative, when Andrey Sushko (now WindBorne’s CTO) and another college students turned eager about extending the flight period of standard climate balloons. Most climate balloons burst after simply a few hours in flight, accumulating information for less than a single up-down cycle as they ascend, pop, after which drop again right down to the bottom. These balloons virtually by no means go far past their continental launch websites, leaving the air above oceans, deserts, and different distant areas underobserved. That’s problematic as a result of climate is world: A disturbance that begins close to the west coast of Africa can become the following catastrophic storm to hit North America.
Whereas engaged on the venture, we found that the flight limitations of standard climate balloons imply that they’re observing solely about 15 % of the globe. We realized that if we improved the {hardware} and control systems, we might create climate balloons that self-navigate and intelligently “surf” the wind, permitting them to remain aloft for much longer than standard balloons—suppose weeks as an alternative of hours.
John Dean cofounded WindBorne in 2019. Jason Henry/The New York Occasions/Redux
I cofounded the corporate in 2019 with 4 of my friends from Stanford, and later took on the position of CEO. At the moment, we had been nonetheless within the early R&D phases for our balloons. The results of that work was a design for autonomous, long-duration balloons that talk with operators by way of satellite tv for pc. In 2024, we launched our first AI forecasting mannequin, WeatherMesh, to ingest the info from the balloons and provides them high-level directions on the place to fly subsequent to fill in particular information gaps.
The principle envelope of a WindBorne balloon is constituted of a skinny, clear movie simply 20 micrometers thick—lower than half the thickness of a human hair—and the entire meeting weighs lower than 2 kilograms. Every balloon has a bag of sand used as ballast; the balloon can launch sand to rise increased or vent gasoline to descend to a special wind present. Every balloon’s onboard autonomous system plots how one can use the winds at totally different elevations to achieve the areas specified by its WeatherMesh directions.
Our GSBs, which acquire orders of magnitude extra information than single-use dropsondes, make up Atlas, our world constellation. Right now, our GSBs can fly for properly over 50 days at altitudes starting from floor stage as much as round 24 kilometers. Atlas, which generally has lots of of balloons within the air at any time, collects extra in situ information every day than the balloons managed by the U.S. Nationwide Climate Service.
Following our time at Stanford, the WindBorne staff constructed a enterprise by scaling our Atlas constellation and offering climate information as a service. At first, the balloons’ navigation was guided by outcomes from a standard numerical weather-prediction mannequin that ran on a supercomputer. However operating that mannequin required lots of of occasions as a lot computing energy as AI climate fashions do. As our constellation proved able to accumulating huge quantities of information, we knew we would have liked to construct a mannequin that might not solely effectively direct our balloon constellation but in addition assimilate its large datasets.
The Limitations of Conventional Forecast Strategies
At the moment, most climate forecasts depend on physics-based numerical weather prediction. Within the United States, this job is dealt with by the federal authorities’s Global Forecast System (GFS), which ingests information from satellites, ground stations, radar techniques, and a worldwide community of standard climate balloons. It runs on a supercomputer 4 occasions a day, utilizing a way referred to as information assimilation to supply forecasts that reach as much as 16 days out. Information assimilation interprets new information alongside historic information to give you essentially the most correct forecast doable.
For the launch, the balloon is mounted on a hoop that’s aligned with the wind. Christie Hemm Klok
However therein lies the issue: Forecasting fashions are solely as correct as the info they’re fed. With a lot of the worldwide environment not being usually probed by balloons, present forecasts are hamstrung by the sparseness of the datasets out there to them. You’ve in all probability seen a hurricane’s forecast cone shift dramatically from sooner or later to the following. That volatility is available in half from the unfinished information driving these fashions. What’s extra, physics-based fashions require monumental computing assets, which translate into excessive operational prices.
Over the previous few years, AI models have disrupted weather forecasting, proving that they’ll generate quicker, less expensive, and extra correct predictions compared with the prior gold customary of physics-based numerical climate fashions. When the Chinese language firm Huawei launched its Pangu-Weather mannequin in 2023, it served discover that AI forecasting couldn’t solely compete with physics-based fashions, nevertheless it might even outperform them. Different latest AI climate fashions embrace Google DeepMind’s GraphCast and AIFS from the European Centre for Medium-Vary Climate Forecasts. However our system outperforms all of them, generally by a really giant measure.
The balloon is initially doubled up [top] to make it extra maneuverable earlier than launch. Then Andrey Sushko, cofounder and CTO of WindBorne Programs, releases the balloon. A screenshot [bottom] reveals information gathered by the balloon in actual time. Photographs: Christie Hemm Klok; Screenshot: WindBorne
Whereas they proceed to smash information, AI fashions (together with ours) nonetheless make use of conventional physics-based fashions in a number of methods. For starters, all AI fashions are skilled on historic climate information and predictions produced by standard techniques. With out them, the mannequin must depend on uncooked, real-time observations for coaching information, with out historic context.
AI fashions additionally inherently lack a complicated understanding of physics, so conventional fashions present a baseline to make sure that AI-generated predictions are bodily believable. This help is particularly necessary throughout excessive climate occasions, when physics-based fashions might help AI fashions simulate uncommon circumstances primarily based on atmospheric rules.
How We Constructed our AI Climate-Forecasting Mannequin
When the WindBorne staff got down to construct the preliminary model of WeatherMesh, we had three most important targets. First, it needed to be cheap to run. Second, it wanted to be no less than as correct as the highest physics-based fashions. Third, it needed to ship forecasts with a excessive spatial decision, offering fine-grained predictions on the size of tens of kilometers.
We determined to make use of an structure primarily based on what are referred to as transformers—the identical expertise that powers large language models like ChatGPT—as a result of transformers can course of big datasets effectively as soon as they’re skilled. This structure consists of what AI professionals confer with as an encoder-processor-decoder construction. The encoder transforms uncooked climate information—issues like temperature, wind, and strain—into a less complicated compressed format generally known as latent area, the place patterns are simpler for the mannequin to work with. The processor then runs calculations on this latent area to foretell how the climate will change over time. To create longer-range forecasts, we merely run the processor step a number of occasions, with the output of the final prediction step serving because the enter for the following. Lastly, the decoder interprets the outcomes again into real-world climate variables.
Every WindBorne balloon incorporates ballast that may be launched to achieve altitude. Christie Hemm Klok
A technician connects sensors to a valve (white and blue circle) that vents gasoline to scale back altitude. Christie Hemm Klok
We skilled our first climate mannequin at our headquarters utilizing a cluster of some dozen Nvidia RTX 4090graphics processing items (GPUs), which value far lower than counting on cloud-computing companies to deal with lots of of terabytes of atmospheric information. Organising our personal machines paid off. The {hardware} set us again about $100,000, however had we run all our coaching experiments within the cloud as an alternative, it simply would have value 4 occasions as a lot.
The primary model of WeatherMesh was smaller, quicker, and cheaper to function than the AI climate fashions created by tech giants. Throughout coaching, it used about one-fifteenth the computing energy of DeepMind’s GraphCast and one-tenth that of Huawei’s Pangu-Climate. Its small dimension makes its stellar efficiency all of the extra notable: It outperformed each these AI fashions and conventional physics-based fashions.
The early accuracy features of WeatherMesh could be attributed to our data-collection technique. Our GSBs acquire 30 to 50 occasions as a lot information as do standard balloons, and we feed that information instantly into WeatherMesh. We measured our mannequin’s accuracy primarily based on frequency of errors compared with different physics- and AI-based fashions. In 2024, we beat each Huawei’s Pangu-Climate and DeepMind’s GraphCast to develop into essentially the most correct AI forecasting mannequin on the planet. On the time this text is being revealed, in October 2025, WeatherMesh retains the lead.
Every balloon has an antenna that allows it to speak by way of satellite tv for pc. Christie Hemm Klok
A technician assembles the valve used to vent gasoline.Christie Hemm Klok
Our preliminary model of the mannequin took in information and output forecasts at 0.25-degree decision (about 25 kilometers per grid cell) to match the decision of ERA5, a extensively used historic climate dataset. Right now, WeatherMesh additionally features a element that may present forecasts for chosen areas at a decision of about 1 km.
Most AI climate fashions prepare on historic datasets like ERA5, which organizes a long time of atmospheric information right into a constant framework. However we additionally needed WeatherMesh to run “stay,” ingesting real-time balloon observations and up-to-date analyses from the U.S. and European businesses. That transition was difficult, as a result of most AI fashions carry out worse after they shift from rigorously curated historic information to messy real-world feeds.
To deal with this situation, we constructed specialised adapters primarily based on a sort of neural-network structure generally known as U-Internet, which excels at studying spatial options throughout totally different scales. These adapters translate real-time information into the identical inside format used for WeatherMesh’s coaching information. On this manner we preserved the advantages of coaching on ERA5 whereas nonetheless delivering correct real-time forecasts.
Constructing On Success With WeatherMesh-4
Following the success of our preliminary WeatherMesh mannequin, we launched the second, third, and fourth variations of the mannequin in speedy succession. WeatherMesh-4 predicts customary atmospheric variables at 25 vertical ranges all through the environment. It additionally predicts a variety of circumstances on the floor, together with temperature and dewpoint at 2 meters from the bottom, wind velocity at 10 meters and 100 meters, minimal and most temperatures, precipitation, photo voltaic radiation, and complete cloud cowl. It might produce a full forecast each 10 minutes primarily based on the newest observations. In distinction, conventional world climate fashions replace each 6 hours.
Copper wires threaded by means of the plastic assist management the gas-venting system. Christie Hemm Klok
The balloon materials is simply 20 micrometers thick, and every balloon weighs lower than 2 kilograms when totally assembled. Christie Hemm Klok
We’ve run in depth benchmarks to match the newest model of WeatherMesh with different widespread forecasting techniques. We’ve discovered that the mannequin’s predictions for the Earth’s floor and environment are as much as 30 percent more accurate than these from a standard mannequin from the European Centre for Medium-Vary Climate Forecasts, and in addition surpass outcomes from DeepMind’s newest mannequin, GenCast, on most evaluations.
Constructing an end-to-end system means all the pipeline should work in concord. Our balloon constellation can’t afford to attend 12 hours for a brand new forecast; it wants near-constant refreshes to navigate the skies. In the meantime, the AI mannequin makes use of recent atmospheric information from the balloons to enhance the accuracy of its forecasts. Balancing these necessities pressured us to get inventive about how we moved the info and ran the mannequin, however finally we produced a strong system that’s quick and responsive.
What’s Subsequent for WindBorne
Within the coming years, our purpose is to broaden our Atlas balloon constellation to about 10,000 GSBs flying at any time, launched from about 30 websites worldwide. To realize that purpose we’ll want roughly 300 launches per day, or 9,000 monthly. By 2028, we imagine all the globe could possibly be below near-continuous remark by Atlas, from the distant Pacific to the polar ice caps. And we proceed to check the boundaries of what’s doable: WindBorne lately stored a balloon aloft for a record-breaking 104 days.
Conventional climate balloons keep aloft for only some hours and don’t go removed from their launch websites. Annie Mulligan/Houston Chronicle/Getty Pictures
We’re not aiming to make physics-based climate fashions out of date. We see a future the place AI and conventional strategies function facet by facet, every reinforcing the opposite. Governments, researchers, and firms can lean on these improved forecasts to information catastrophe preparedness, aviation, supply-chain logistics, and extra. Our planet’s climate challenges are solely going to accentuate because the local weather continues to vary, and improved forecasts are key to serving to us put together.
Wanting again at Hurricane Milton, it nonetheless feels surreal that our balloons managed to experience right into a storm of that scale. But that was the second WindBorne proved {that a} new and agile system might ship actual worth the place legacy strategies fall quick. In a world the place an additional 12 or 24 hours of warning can imply the distinction between security and devastation, end-to-end AI forecasting presents a revolution in how folks can observe, predict, and defend themselves from essentially the most highly effective forces on Earth.
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