paper
2023
Hybrid physics-ML & parameterization
Sub-seasonal to seasonal New model or method
Seasonal to annual Journal
2023-04-21
012
Apr 2023
Lirong You, Xiaoxiao Tan, Youmin Tang
Atmospheric Research
Builds a deep-learning westerly wind burst parameterization intended to improve ENSO prediction; the abstract is missing, so gains are unknown.
Hybrid physics-ML & parameterization
Construction of deep-learning based WWBs parameterization for ENSO prediction
In one sentence. Builds a deep-learning westerly wind burst parameterization intended to improve ENSO prediction; the abstract is missing, so gains are unknown.
Labels
- Topic
- Hybrid physics-ML & parameterization, Sub-seasonal to seasonal
- Type
- New model or method
- Time scale
- Seasonal to annual
- Domain
- Global
- Status
- Research
- Identifiers
- DOI:10.1016/j.atmosres.2023.106770 OpenAlex:W4366609076
- Added
- 2026-10-22
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