paper
2021
Data assimilation
Foundation models Position or perspective paper
RNN / LSTM / ConvLSTMPhysics-informed / physics-constrainedECMWF Journal
2021-02-15
061
Feb 2021
A. J. Geer
Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences
ECMWF
Perspective framing data assimilation and machine learning as equivalent inverse methods in a Bayesian network, e.g. linking 4D-Var to recurrent neural networks, to learn earth system models from observations.
Learning earth system models from observations: machine learning or data assimilation?
In one sentence. Perspective framing data assimilation and machine learning as equivalent inverse methods in a Bayesian network, e.g. linking 4D-Var to recurrent neural networks, to learn earth system models from observations.
Labels
- Topic
- Data assimilation, Foundation models
- Type
- Position or perspective paper
- Method
- RNN / LSTM / ConvLSTM, Physics-informed / physics-constrained
- Domain
- Global
- Data
- Other
- Status
- Research
- Identifiers
- arXiv:2020.0089 DOI:10.1098/rsta.2020.0089 OpenAlex:W3131584643
- Added
- 2026-10-22
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