paper
2018
Hybrid physics-ML & parameterization
Climate emulation Position or perspective paper
OtherClimate projections / centennial Journal
2018-03-21
008
Mar 2018
Sarah Stanley
Eos
Eos news piece proposing that climate models learn and adapt on the fly with machine learning to reduce prediction uncertainty.
Hybrid physics-ML & parameterization
Next-Generation Climate Models Could Learn, Improve on the Fly
In one sentence. Eos news piece proposing that climate models learn and adapt on the fly with machine learning to reduce prediction uncertainty.
Abstract
Scientists propose development of new models that use machine learning techniques to reduce uncertainties in climate predictions.
Labels
- Topic
- Hybrid physics-ML & parameterization, Climate emulation
- Type
- Position or perspective paper
- Method
- Other
- Time scale
- Climate projections / centennial
- Domain
- Global
- Status
- Research
- Identifiers
- DOI:10.1029/2018eo093857 OpenAlex:W2790419979
- Added
- 2026-10-22
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