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On the Complementary Role of Data Assimilation and Machine Learning: An Example Derived from Air Quality Analysis
We present a new formulation of the error covariances that derives from ensembles of model simulations, which captures terrain-dependent error correlations, without the prohibitive cost of ensemble Kalman filtering. Error variances are obtained from innovation variances empirically related to concen...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
2020
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7304728/ http://dx.doi.org/10.1007/978-3-030-50433-5_17 |