paper
2019
Post-processing & calibration
New model or method
Classical ML (trees, GP, linear, kernels)6 h–3 daysMET Norway (Norwegian Meteorological Institute) Journal
2019-12-27
047
Dec 2019
John Bjørnar Bremnes
Monthly Weather Review
MET Norway (Norwegian Meteorological Institute)
Neural-network quantile function regression with Bernstein polynomials postprocesses 60 h ensemble wind speed at 125 Norwegian stations, improving quantile skill score by nearly 1%.
Ensemble Postprocessing Using Quantile Function Regression Based on Neural Networks and Bernstein Polynomials
In one sentence. Neural-network quantile function regression with Bernstein polynomials postprocesses 60 h ensemble wind speed at 125 Norwegian stations, improving quantile skill score by nearly 1%.
Labels
- Topic
- Post-processing & calibration
- Type
- New model or method
- Method
- Classical ML (trees, GP, linear, kernels)
- Time scale
- 6 h–3 days
- Domain
- Local / station
- Data
- NWP analysis or forecasts (IFS, GFS, ...), Station / in-situ
- Status
- Research
- Identifiers
- DOI:10.1175/mwr-d-19-0227.1 OpenAlex:W2980462578
- Added
- 2026-10-22
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