Kate Musgrave
Colorado State University-Fort Collins, CO·Earth & Environmental Science
Hurricanes endanger lives and property through several hazards at once: storm surge, inland flooding, and damaging winds that can include tornadoes. Better forecasts of these combined hazards matter directly for emergency decisions.
- Fields
Earth & Environmental Science
Computer Science
- Topics
hurricane forecasting
tropical cyclones
artificial intelligence
- Grants
- 1 known grant, through Jul 2027
What they work on
- Connect guest artificial-intelligence researchers and their hurricane models to NOAA's Hurricane and Ocean Testbed (HOT), with the project team serving as intermediary between AI developers and the operational testbed.
- Develop a tiered test protocol for evaluating AI hurricane and hazard models within the HOT testbed, and extract insights into how those models produce their forecasts.
- Identify the computing and personnel infrastructure HOT would need to support AI models, as the technical basis for an AI-ready testbed expansion.
- Design an expansion framework for HOT through meetings with testbed users and a dedicated workshop, then plan the expansion and assess which elements generalize to other weather testbeds.
More about the research
New forecasting models built with artificial intelligence (AI) look promising, but the researchers who build them and the forecasters who could use them operate in largely separate worlds, and the facilities forecasters use for testing were not designed with AI in mind.
Why it matters
Communities on the coast and inland face hurricane hazards including surge, flooding, and damaging winds. By planning a path for AI hurricane models to be tested in NOAA's operational testbed, this work could help forecasters at the National Hurricane Center adopt methods that improve hurricane and hazard predictions, supporting warnings that protect life and property. Lessons learned may also transfer to other forecasting testbeds considering AI.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
Haiyan Jiang
Florida International University, FL·Earth & Environmental Science
Characterize how tropical cyclone rainfall distribution and asymmetry change before, during and after landfall, using statistical analysis of long-term satellite observations.
Gary Lackmann
North Carolina State University, NC·Earth & Environmental Science
Assess how a warming climate shifts tropical cyclone activity and landfall locations in the North Atlantic, using observations and global climate model simulations that resolve individual storms.
Steven Greybush
Pennsylvania State University, PA·Earth & Environmental Science
Design and optimize a deep learning nowcasting system for convection initiation that combines forecasting, diagnosis and generation of storm scenarios, trained on high-resolution satellite, radar and surface weather data.
The school
Colorado State University-Fort Collins: 23 labs on PI Pages, $466M a year on research, 276 research doctorates a year.
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