Artificial Intelligence Is Reshaping How Colorado Meteorologists Forecast the State’s Volatile Weather
Why It Matters
Colorado’s weather is among the most unpredictable in the country, with rapid temperature swings, severe thunderstorms, and historically variable snowpack posing constant challenges to public safety and planning. As artificial intelligence tools gain traction among Colorado meteorologists, the technology promises faster, more detailed forecasts that could give residents and emergency managers more reliable warning time.
What Happened
Meteorologists gathered Friday for a panel discussion at the fourth annual Colorado SunFest at the University of Denver to discuss how AI is transforming weather prediction across the state. The conversation brought together working forecasters who described a meaningful shift already underway in how they build and evaluate forecast models.
Joel Gratz, founding meteorologist of OpenSnow, explained that the primary advantage AI offers is not necessarily greater accuracy in any single forecast, but dramatically increased speed — enabling forecasters to run far more model simulations in the same amount of time. “Instead of running that forecast one time, five times, 10 times, you run it 50 times, 100 times, eventually you run it 1,000 times and see what those probabilities are,” Gratz said during the panel.
9News senior meteorologist Chris Bianchi said he turned to AI models more heavily while forecasting one of Colorado’s driest winters on record, a season marked by historically low snowpack and a late-March heat wave. He said he watched AI-driven guidance outperform traditional numerical models in real time. “I now look at the AI model over the numerical models, the old models — and that is new as of probably two months ago,” Bianchi said.
By the Numbers
- 1,000 simulations: The approximate number of forecast model runs AI makes possible, compared to far fewer under traditional methods.
- 40 years: The span of historical tornado report data used to train one AI model on Gratz’s team, combined with lightning, hail, and wind data.
- 2 minutes: The update interval of a system Gratz described that estimates near-term probability of lightning or tornado activity.
- 5 years: The window within which Bianchi expects AI to reliably produce accurate forecasts extending up to two weeks out.
- 4 annual events: Colorado SunFest, now in its fourth year, has become a venue for these applied technology discussions.
Zoom Out
The shift described by Colorado forecasters reflects a broader national trend. Major meteorological agencies and private weather firms across the country have been integrating machine-learning tools into their forecasting pipelines, with the National Oceanic and Atmospheric Administration’s decades of open historical data playing a foundational role. Gratz specifically credited NOAA’s data archives as essential to training AI models capable of identifying severe weather patterns. Colorado’s use of AI in weather forecasting mirrors wider debates in the state about how artificial intelligence is being deployed across industries. Colorado lawmakers have separately considered regulations focused on informing consumers when AI technology is used in various applications, reflecting growing public scrutiny of the tools.
Veteran meteorologist Mike Nelson, retired chief meteorologist at Denver7, noted during the panel that AI represents the latest in a long series of technological advances in forecasting — but emphasized that human judgment remains central to the process.
What’s Next
Bianchi projected that within five years, AI-driven forecasts accurate out to two weeks could become routine, a substantial improvement over current five-day outlooks. “I think within five years, you’re gonna see pretty darn good AI-driven forecasts up to two weeks out,” he said, while acknowledging that level of confidence is not yet something he is ready to state publicly on air.
Gratz’s team continues refining event-specific AI models, including systems that assess tornado and thunderstorm probability on a rolling two-minute cycle, drawing on radar, satellite, and atmospheric data simultaneously. As AI-powered technologies expand in Colorado across sectors from law enforcement to infrastructure, the meteorology community’s adoption of the tools offers one of the clearer demonstrations of practical, real-world application — and its limits.