paper
2019
Nowcasting
Probabilistic & ensemble forecasting New model or method
Classical ML (trees, GP, linear, kernels)0–6 hETH ZurichMeteoSwiss Journal
2019-07-25
051
Jul 2019
Loris Foresti, Ioannis Vasileios Sideris, Daniele Nerini et al.
Weather and Forecasting
ETH Zurich, MeteoSwiss
Neural networks and quantile trees nowcast precipitation growth and decay in Swiss Alps radar archive, with persistence inputs cutting RMSE by 20-30% in mountains.
Using a 10-Year Radar Archive for Nowcasting Precipitation Growth and Decay: A Probabilistic Machine Learning Approach
In one sentence. Neural networks and quantile trees nowcast precipitation growth and decay in Swiss Alps radar archive, with persistence inputs cutting RMSE by 20-30% in mountains.
Labels
- Topic
- Nowcasting, Probabilistic & ensemble forecasting
- Type
- New model or method
- Method
- Classical ML (trees, GP, linear, kernels)
- Time scale
- 0–6 h
- Domain
- Regional
- Data
- Radar
- Status
- Research
- Identifiers
- DOI:10.1175/waf-d-18-0206.1 OpenAlex:W2963511153
- Added
- 2026-10-22
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