Michael French
Stony Brook University, NY·Earth & Environmental Science
Every hazard a severe thunderstorm produces, from large hail to tornadoes, depends on its updraft. The updraft is the column of rapidly rising air that builds the cloud and its precipitation.
- Fields
Earth & Environmental Science
Physics
- Topics
supercell
thunderstorm
tornado
- Grants
- 1 known grant, through Mar 2027
What they work on
- Establish a firm link between updraft area at middle and low levels and the occurrence of tornadoes and large hail in more than 100 supercells, using an automated algorithm that detects ZDR columns in dual-polarization radar data.
- Quantify how much vertical alignment of the supercell updraft is needed for tornado production, using ZDR-column positions at different heights as a proxy for updraft tilt.
- Determine whether conditions in the near-storm environment control updraft size and alignment, combining radar-derived updraft proxies with environmental data.
- Combine updraft size and tilt results with the ZDR-KDP separation vector, a second dual-polarization radar signature, to improve predictors of tornado formation and peak tornado intensity for possible nowcasting use.
More about the research
Past studies suggest that wider updrafts produce stronger tornadoes and larger hail. They also hint that upright updrafts, rather than tilted ones, are more likely to spawn tornadoes. The problem is that updrafts are very hard to measure directly. Better measurements could help forecasters warn the public before a storm produces a strong tornado or very large hail.
Why it matters
Supercell thunderstorms cause the most damaging tornadoes and hail in the United States. Radar-based estimates of updraft size and tilt could give National Weather Service forecasters new warning tools. These could flag storms that are about to produce strong tornadoes or very large hail, helping communities take shelter sooner.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
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.
Chengsi Liu
University of Oklahoma, OK·Earth & Environmental Science
Develop a machine-learning-guided adaptive inflation method that corrects under-dispersive ensembles (forecast sets that are too similar to one another) in storm regions during radar data assimilation.
Lynn McMurdie
University of Washington, WA·Earth & Environmental Science
Determine how large-scale weather patterns and water vapor transport shape the character of snowfall events over Colorado's Park Range, using a winter-long radar and balloon dataset combined with numerical modeling.
The school
Stony Brook University: 32 labs on PI Pages, $319M a year on research, 289 research doctorates a year.
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