paper
2020
Post-processing & calibration
Local & station forecasting Application study
Classical ML (trees, GP, linear, kernels)6 h–3 daysMétéo-France (incl. CNRM) Journal
2020-03-05
043
Mar 2020
Driss Bari, Abdelali Ouagabi
SN Applied Sciences
Météo-France (incl. CNRM)
Machine-learning regression diagnoses horizontal visibility from mesoscale NWP forecasts; abstract not available, so the scope is inferred from the title.
Machine-learning regression applied to diagnose horizontal visibility from mesoscale NWP model forecasts
In one sentence. Machine-learning regression diagnoses horizontal visibility from mesoscale NWP forecasts; abstract not available, so the scope is inferred from the title.
Labels
- Topic
- Post-processing & calibration, Local & station forecasting
- Type
- Application study
- 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:10.1007/s42452-020-2327-x OpenAlex:W3009579196
- Added
- 2026-10-22
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