paper
2021
Extremes & hazards
New model or method
Classical ML (trees, GP, linear, kernels)NOAA (incl. GFDL, PSL, GSL, NCEP/EMC)University of Oklahoma (AI2ES) Journal
2021-01-01
043
Jan 2021
Brice E. Coffer, Michaela Kubacki, Yixin Wen et al.
PAMM
NOAA (incl. GFDL, PSL, GSL, NCEP/EMC), University of Oklahoma (AI2ES)
Random forest on RUC pre-storm sounding data discriminates tornadic from nontornadic storms, with feature analysis showing pressure has little impact.
Machine Learning with Feature Importance Analysis for Tornado Prediction from Environmental Sounding Data
In one sentence. Random forest on RUC pre-storm sounding data discriminates tornadic from nontornadic storms, with feature analysis showing pressure has little impact.
Labels
- Topic
- Extremes & hazards
- Type
- New model or method
- Method
- Classical ML (trees, GP, linear, kernels)
- Domain
- Regional
- Data
- NWP analysis or forecasts (IFS, GFS, ...)
- Status
- Research
- Identifiers
- DOI:10.1002/pamm.202000112 OpenAlex:W3042754474
- Added
- 2026-10-22
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