HomeArtificial IntelligenceHow AI Makes Weather Better and Cheaper

How AI Makes Weather Better and Cheaper

Did you know how AI makes the weather better and cheaper? See how the weather is deducted through artificial intelligence. A black box packed with computer processors flew from California to Uganda in the first few days of February. The 4-foot-tall, squat box resembled a massive audio amplifier. Its duty was to forecast the weather more accurately than any other system the country utilized once it was established in Kampala.

AI atom California business

Atmo AI, the California business that manufactured the product, intends to replace it by this summer with a more impressive creation. An elegant, metallic supercomputer that is 8 feet tall and has 20 times more power. The co-founder and CEO of Atmo, Alexander Levy, describes it as being positioned as the iPhone of global meteorology.

  1. Smartphone weather deduction

That’s a tribute to Apple Inc.’s reputation for design and marketing. Consumers who had never possessed desktop computers purchased smartphones in large numbers in various nations. Similarly, Atmo claims that governments need how AI to make the weather better, cheaper expensive supercomputers and data centers. Required to produce cutting-edge weather forecasts, every country that isn’t a global superpower will pay for its less expensive device instead.

  1. Uganda National Meteorological Authority 

But, Atmo is shipping its beta version, the simple black box, to its first client, the Uganda National Meteorological Authority (UNMA). With the pressing issue, it seems sensible to prioritize function over form. Landslides, floods, and a biblical locust plague that destroyed fields recently struck Uganda. 

Following intermittent rain and drought, the locusts surprised officials unprepared for the swarms. However, the acting executive director of UNMA, David Elweru, says it opened our eyes.

Countries’ Devastation and AI Role

Many countries experiencing such devastation need more cutting-edge planning tools. Artificial intelligence software, according to Atmo, is the solution. The reaction starts with predictions, according to Levy. “We are condemning people to calamity and misery if we expect nations to respond to events simply after they have occurred.” It’s a new strategy. Only a few weather bodies have tried AI systems in meteorology, even though it presents significant problems. The majority of nations need more resources to attempt.

  1. Stephen Kaboyo’s weather prediction

Officials from Uganda inked a multi-year agreement with Atmo, but they will not disclose the details. But, according to Stephen Kaboyo, an investor who advises Atmo in Uganda, the UNMA chose the firm because its product was “way, way cheaper” than rivals. In February, the dry season in Kampala, Kaboyo spoke with a caller as the city was battered by rain.

He stated of the weather, “We haven’t seen this before. Who can predict what will occur throughout the following three seasons?

Read Also: What is an example of conversational AI?

Frequently Asked Questions

How can Intelligence improve weather forecasting?

A representative for Nearmap stated that “AI allows the ability to go and see aerial imagery of places over the duration, which can help forecast a region’s state of preparation for future weather events.”

How does machine learning aid in weather prediction?

Machine learning models might ultimately completely replace conventional numerical weather prediction models. These systems would analyze thousands of historical weather maps to learn how weather systems typically act instead of solving a set of difficult physical calculations as the models do.

Which innovation has improved weather forecasting the most?

Any meteorological instrumentation now includes radar as a standard component. In addition to determining the type and intensity of precipitation, it is frequently used to find and track it. Radar is additionally employed to predict precipitation from hurricanes, winter storms, and thunderstorms.

Which machine learning system is most effective at forecasting the weather?

The authors created a computer vision weather prediction system dubbed Deep Learning Weather Prediction using a convolutional neural network as its basis (DLWP). In contrast to conventional numerical how ai make weather better cheaper prediction models, which produce analytical models of physical principles, the model is trained on historical weather data.

Weather stations over Uganda

Three forecasting radars and more than 100 weather stations are spread over Uganda. Last summer, Atmo started sending information from these sensors into its California office, a residence in the Berkeley Hills where Levy resides. His co-founder Johan Mathe also lived there up until recently. The black box on how AI makes the weather better and cheaper, programmed by Mathe, the director of technology, sat on the ground floor before being transported to Kampala. Crunching Uganda’s data with a loud hum from its spinning processors.

Atmo had positioned a sizable world map behind the box, highlighting the nations with which it had or desired to have agreements. You don’t have to be insane to work here; we’ll train you, read a placard in the room.

  • Levy tech entrepreneurs’ weather prediction

Several tech entrepreneurs believe navigating the bureaucracy required to work with governments is absurd. Atmo, though, is determined to pitch public agencies. Governments themselves are “the crucial organizations—the ones that stand to gain and lose,” according to Levy.

Computers for forecasting weather

The purpose of computers was to forecast the weather. The first digital computer, the ENIAC, built by the U.S. Army, spent the entire day in 1950 issuing the first machine forecast in history. Computers become faster with time. They employed the conventional numerical weather prediction model, which divides the Earth’s surface into grids with cells for computing temperatures, winds, and humidity before spitting out a forecast.

German researcher theory how AI makes the weather better and cheaper.

Yet, in these simulations, each grid zoom-in necessitates an ever-increasing increase in processing power. Computers have found it challenging to keep up as satellite photographs have added more snapshots of the Earth in recent years, according to Martin Schultz, a research researcher at Germany’s Jülich Supercomputing Centre. As a result, the National Oceanic and Atmospheric Administration established two machines in 2020. Bringing its total capacity to more than 40 petaflops, giving it even more than 15,000 times. The achievement power of the most recent Mac computer. Some of the largest supercomputers in the world are used for weather forecasting.


Theoretically, artificial intelligence may produce how AI improves the weather and cheaper comparable projections with less computing. Early studies have indicated improvement in “nowcasting,” or weather forecasting, in the following hour or two. Schultz estimates that about 20 “critical” meteorological applications have begun to use AI in the last five years. But, recognizing a picture or concluding a phrase is more manageable for robots than predicting the weather. As a result, turbulence, high-pressure systems, and other atmospheric volatile characteristics are indicated for various times in the hour, day, and week ahead.

Awais khan is a technology enthusiast with a passion for writing about the latest and greatest in the tech industry. With over 02 years of experience in Information Technology, he has a wealth of knowledge to share with readers. Awais has a strong background in IT, and I am always on the lookout for the next big thing in the world of technology. we are excited to be able to share insights and experiences with you through Awais khan's writing on this website.


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