paper
2023
Hybrid physics-ML & parameterization
Sub-seasonal to seasonal New model or method
Other6 h–3 days3–15 daysLawrence Berkeley National Laboratory / NERSC Other
2023-08-22
022
Aug 2023
Zikang He, Julien Brajard, Yiguo Wang et al.
preprint
Lawrence Berkeley National Laboratory / NERSC
Hybrid model uses an ANN trained on analysis increments to correct errors in a coupled ocean-atmosphere model (MAOOAM), improving prediction skill across lead times.
Hybrid physics-ML & parameterization
Enhancing climate predictions with combination of dynamical model and artificial neural network
In one sentence. Hybrid model uses an ANN trained on analysis increments to correct errors in a coupled ocean-atmosphere model (MAOOAM), improving prediction skill across lead times.
Labels
- Topic
- Hybrid physics-ML & parameterization, Sub-seasonal to seasonal
- Type
- New model or method
- Method
- Other
- Time scale
- 6 h–3 days, 3–15 days
- Domain
- Global
- Data
- Other
- Status
- Research
- Identifiers
- DOI:10.22541/essoar.169272242.27053871/v1 OpenAlex:W4386070303
- Added
- 2026-10-22
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