paper
2023
Extremes & hazards
Probabilistic & ensemble forecasting New model or method
Classical ML (trees, GP, linear, kernels)Princeton University Journal
2023-12-18
026
Dec 2023
Joseph W. Lockwood, Thomas Loridan, Ning Lin et al.
Journal of Hydrometeorology
Princeton University
PCA with quantile regression forests yields probabilistic over-ocean tropical cyclone rainfall maps for the North Atlantic, reaching storm-total correlation of 0.96 with satellite data.
A Machine Learning Approach to Model Over-Ocean Tropical Cyclone Precipitation
In one sentence. PCA with quantile regression forests yields probabilistic over-ocean tropical cyclone rainfall maps for the North Atlantic, reaching storm-total correlation of 0.96 with satellite data.
Labels
- Topic
- Extremes & hazards, Probabilistic & ensemble forecasting
- Type
- New model or method
- Method
- Classical ML (trees, GP, linear, kernels)
- Domain
- Regional
- Data
- km-scale or high-res simulation, Satellite
- Status
- Research
- Identifiers
- DOI:10.1175/jhm-d-23-0065.1 OpenAlex:W4389925296
- Added
- 2026-10-22
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