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

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

doi:https://doi.org/10.5194/npg-29-37-2022

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

Data sets

Data repository for Polzin et al. (2022) "Direct Bayesian model reduction of smaller scale convective activity conditioned on large-scale dynamics" R. M. Polzin https://doi.org/10.17169/refubium-33435

Model code and software

Bayesian-Model-Reduction-Toolkit S. Gerber https://github.com/SusanneGerber/Bayesian-Model-Reduction-Toolkit

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.