paper
2021
Post-processing & calibration
Global medium-range NWP New model or method
Classical ML (trees, GP, linear, kernels)6 h–3 days Other
2021-04-28
012
Apr 2021
Yuval Yevnin, Yaron Toledo
preprint
Deep learning improves wind forecasts from reanalysis, which then force a wave model, giving about 10% gains in wind and wave height over the Mediterranean and over 35% in the Aegean.
A Hybrid Deep Learning Model for Improved Wind and Wave Forecasts
In one sentence. Deep learning improves wind forecasts from reanalysis, which then force a wave model, giving about 10% gains in wind and wave height over the Mediterranean and over 35% in the Aegean.
Labels
- Topic
- Post-processing & calibration, Global medium-range NWP
- Type
- New model or method
- Method
- Classical ML (trees, GP, linear, kernels)
- Time scale
- 6 h–3 days
- Domain
- Regional
- Data
- ERA5 / reanalysis, NWP analysis or forecasts (IFS, GFS, ...)
- Status
- Pre-operational / experimental
- Identifiers
- DOI:10.1002/essoar.10506907.1 OpenAlex:W3210202320
- Added
- 2026-10-22
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