Nonlinear Processes in Geophysics
Nonlinear Processes in Geophysics
NPG
Articles | Volume 29, issue 1
Articles | Volume 29, issue 1
https://doi.org/10.5194/npg-29-37-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/npg-29-37-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 29, issue 1
Research article
 | 
16 Feb 2022
Research article |  | 16 Feb 2022

Direct Bayesian model reduction of smaller scale convective activity conditioned on large-scale dynamics

Robert Polzin, Annette Müller, Henning Rust, Peter Névir, and Péter Koltai

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Latest update: 29 Jun 2024
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Short summary
In this study, a recent algorithmic framework called Direct Bayesian Model Reduction (DBMR) is applied which provides a scalable probability-preserving identification of reduced models directly from data. The stochastic method is tested in a meteorological application towards a model reduction to latent states of smaller scale convective activity conditioned on large-scale atmospheric flow.
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