Dynamic Bayesian Networks for Evaluation of Granger Causal Relationships in Climate Reanalyses
Abstract We apply a Bayesian structure learning approach to study interactions between global climate modes, so illustrating its use as a framework for developing process‐based diagnostics with which to evaluate climate models. Homogeneous dynamic Bayesian network models are constructed for time ser...
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| Auteurs principaux: | , |
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| Format: | article |
| Langue: | EN |
| Publié: |
American Geophysical Union (AGU)
2021
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| Sujets: | |
| Accès en ligne: | https://doaj.org/article/720c584245b34176b886e6888ef0141d |
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