paper
2024
Hybrid physics-ML & parameterization
New model or method
Classical ML (trees, GP, linear, kernels)Météo-France (incl. CNRM) Journal
2024-02-21
047
Feb 2024
Donald P. Cummins, Virginie Guémas, Sébastien Blein et al.
Boundary-Layer Meteorology
Météo-France (incl. CNRM)
Machine learning is used to reduce parametrization errors in polar surface turbulent flux schemes; abstract unavailable, so classification relies on the title.
Hybrid physics-ML & parameterization
Reducing Parametrization Errors for Polar Surface Turbulent Fluxes Using Machine Learning
In one sentence. Machine learning is used to reduce parametrization errors in polar surface turbulent flux schemes; abstract unavailable, so classification relies on the title.
Labels
- Topic
- Hybrid physics-ML & parameterization
- Type
- New model or method
- Method
- Classical ML (trees, GP, linear, kernels)
- Domain
- Regional
- Status
- Research
- Identifiers
- DOI:10.1007/s10546-023-00852-8 OpenAlex:W4392017812
- Added
- 2026-10-22
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