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Machine learning with data assimilation and uncertainty quantification for dynamical systems: a review
Data Assimilation (DA) and Uncertainty quantification (UQ) are extensively used in analysing and reducing error propagation in high-dimensional spatial-temporal dynamics.
Combining data assimilation and machine learning to estimate parameters of a convective-scale model
Errors in the representation of clouds in convection-permitting numerical weather prediction models can be introduced by different sources.
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