paper
2021
Extremes & hazards
Application study
Classical ML (trees, GP, linear, kernels) Journal
2021-11-15
008
Nov 2021
Rupsa Bhowmick, Jill C. Trepanier, Alex M. Haberlie
International Journal of Climatology
Random forest classifies whether southwest Pacific tropical depressions develop into storms with 91% test accuracy, with aerosol optical depth among the top predictors.
Southwest Pacific tropical cyclone development classification utilizing machine learning and synoptic composites
In one sentence. Random forest classifies whether southwest Pacific tropical depressions develop into storms with 91% test accuracy, with aerosol optical depth among the top predictors.
Labels
- Topic
- Extremes & hazards
- Type
- Application study
- Method
- Classical ML (trees, GP, linear, kernels)
- Domain
- Regional
- Data
- ERA5 / reanalysis, Other
- Status
- Research
- Identifiers
- DOI:10.1002/joc.7457 OpenAlex:W3212130345
- Added
- 2026-10-22
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