Articles | Volume 29, issue 1
https://doi.org/10.5194/npg-29-37-2022
https://doi.org/10.5194/npg-29-37-2022
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

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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.