Combining Stochastic Parameterized Reduced‐Order Models With Machine Learning for Data Assimilation and Uncertainty Quantification With Partial Observations

Abstract A hybrid data assimilation algorithm is developed for complex dynamical systems with partial observations. The method starts with applying a spectral decomposition to the entire spatiotemporal fields, followed by creating a machine learning model that builds a nonlinear map between the coef...

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Xehetasun bibliografikoak

Egile Nagusiak:	Changhong Mou, Leslie M. Smith, Nan Chen
Formatua:	Artigo
Hizkuntza:	Inglês
Argitaratua:	American Geophysical Union (AGU) 2023-10-01
Saila:	Journal of Advances in Modeling Earth Systems
Gaiak:	stochastic parameterized reduced‐order model data assimilation machine learning uncertainty precipitating quasi‐geostrophic model
Sarrera elektronikoa:	https://doi.org/10.1029/2022MS003597
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