Move Over Wandavision, Climavision Is Taking On Big Weather With AI
A new weather tech startup says it has created a new artificial intelligence (AI)-powered weather radar and satellite network to take on big weather.
Climavision, which has $100 million in private equity funding, has created a high-resolution weather radar and satellite network that combines lower altitude, proprietary data with machine learning and AI technology.
Chris Goode, CEO of Climavision, says the new sensing network will fill the coverage gaps in the existing NOAA and NWS systems across the US. Goode adds that the current weather surveillance model provides a picture of weather at a given moment, but the picture is not complete.
“The US, like many other governments across the world, relies on a network of weather radars known as NEXRAD and these are strategically placed across the country to collect weather data, in real-time,” said Goode. “In addition to NEXRAD, they also use other forms of weather collection, such as weather balloons and aircraft sensors which are deployed to collect additional data points at different parts in the atmosphere.”
“There are gaps in coverage between radars in the NEXRAD network and gaps in the mixing levels of the atmosphere, where volatile weather forms, and at the lowest levels, where this weather occurs,” added Goode. “The Climavision system will fill in those gaps with critical weather radar infrastructure and bring real-time data with space-based observations to get a complete view of what’s happening from the ground up.”
“Once we collect data direct from the source, we use AI, machine learning and IoT to process, interpret and distribute the data,” said Google. “We’re applying the most sophisticated technology to public datasets so that beyond our data collection, we can learn even more from what is already available.”
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Goode says that traditional weather observations consist of multiple variables, including temperature, wind, pressure, and humidity, which are interconnected and complex.
“We employ AI and machine learning to perform quality control of these observations which come from multiple platforms and various channels based on their respective sensitivity to different components of the atmosphere at different atmospheric levels,” said Goode. “Machine learning, AI like the Artificial Neural Network (ANN) and regression are used to extract the most impactful meteorological information and to integrate the information from different platforms.”
Goode says that the company is bringing a fundamental shift in weather forecasting.
“We can all agree that weather is one of the few phenomena with almost universal application. Understanding weather more intimately, in more detail, and with greater lead time impacts every person, every business, every industry,” said Goode. “So having a better understanding of what’s happening in the atmosphere – one or two hours earlier, sometimes even just minutes earlier – has the potential to save money and, more importantly, save lives.”
“If you don’t know what’s headed your way – flash flooding, hail, snow, tornadoes – you can’t possibly prepare,” adds Goode.
The company plans to rollout the technology in Q4 2021.