paper
2020
Nowcasting
Post-processing & calibration New model or method
Classical ML (trees, GP, linear, kernels)0–6 h Journal
2020-10-22
012
Oct 2020
Yiwen Mao, Asgeir Sorteberg
Weather and Forecasting
Random forest post-processing of radar nowcasts and NWP for hourly precipitation occurrence at 41 Norwegian stations, improving skill and reducing false alarms.
Improving Radar-Based Precipitation Nowcasts with Machine Learning Using an Approach Based on Random Forest
In one sentence. Random forest post-processing of radar nowcasts and NWP for hourly precipitation occurrence at 41 Norwegian stations, improving skill and reducing false alarms.
Labels
- Topic
- Nowcasting, Post-processing & calibration
- Type
- New model or method
- Method
- Classical ML (trees, GP, linear, kernels)
- Time scale
- 0–6 h
- Domain
- Regional
- Data
- Radar, NWP analysis or forecasts (IFS, GFS, ...), Station / in-situ
- Status
- Research
- Identifiers
- DOI:10.1175/waf-d-20-0080.1 OpenAlex:W3093785987
- Added
- 2026-10-22
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