Micro-weather forecasting platform updated to ‘next level’

Micro-weather forecasting platform updated to ‘next level’

Market news |
By Rich Pell

Supporting minute-by-minute, street-by-street-level forecasts, HyperCast is based on the company’s Weather Operating System (Weather OS), which combines “Weather-of-Things” data – including cell tower signals, and data from connected cars, airplanes, drones and IoT devices – with AI-driven models that analyze the data at resolutions of hundreds of meters and minutes.

The new version of HyperCast offers an enhanced user experience, updated infrastructure for quick deployment of new features – such as impact analysis – and new layers, map views, and timeline.

“Reliable weather forecasts are essential, not a ‘nice-to-have,'” says Effie Artidi, Chief Product Officer at ClimaCell. “Knowing when to expect snow or high-speed winds, or where exactly lightning will strike, and when, is critical to businesses.”

“It impacts everything from staffing overtime to maintenance needs, supply and demand expectations, customer satisfaction, and, most importantly, safety,” says Artidi. “It’s time businesses have the level of accuracy they need with insights tailored to their specific  business questions.”   

In May the company unveiled its stealth mode Numerical Weather Prediction (NWP) division, operating from Boulder, CO, and its microscale and on-demand NWP platform, ClimaCell Bespoke Atmospheric Model (CBAM). Last month it launched its Road Risk Score, a rating system of how current and forecasted weather conditions impact road conditions on a road-by-road level across the United States.


Related articles:
Microweather startup eyes global coverage
New weather system promises ‘vastly improved’ global forecasting
Weather forecast algorithm helps spot dangerous cloud formations
IBM AI weather tool enables predictive business forecasting
Hyperlocal air quality sensing startup scales to combat climate change

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