paper
2020
Observations & remote sensing
Extremes & hazards Application study
Classical ML (trees, GP, linear, kernels) Preprint
2020-01-01
008
Jan 2020
Alexander J. DesRosiers, Bell, Michael M., Barnes, Elizabeth et al.
Digital Collections of Colorado (Colorado State University)
Random forest automates quality control of tail Doppler radar data from Hurricane Michael's rapid intensification, classifying over 99% of radar gates correctly.
Airborne radar quality control and analysis of the rapid intensification of Hurricane Michael (2018)
In one sentence. Random forest automates quality control of tail Doppler radar data from Hurricane Michael's rapid intensification, classifying over 99% of radar gates correctly.
Labels
- Topic
- Observations & remote sensing, Extremes & hazards
- Type
- Application study
- Method
- Classical ML (trees, GP, linear, kernels)
- Domain
- Local / station
- Data
- Radar
- Status
- Research
- Identifiers
- DOI:10.25675/3.04762 OpenAlex:W3119760797
- Added
- 2026-10-22
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