Articles | Volume 29, issue 2
Nonlin. Processes Geophys., 29, 171–181, 2022
https://doi.org/10.5194/npg-29-171-2022
Nonlin. Processes Geophys., 29, 171–181, 2022
https://doi.org/10.5194/npg-29-171-2022
Research article
 | Highlight paper
02 May 2022
Research article  | Highlight paper | 02 May 2022

Using neural networks to improve simulations in the gray zone

Raphael Kriegmair et al.

Model code and software

wavestoweather/NNforModelError: NN to improve simulations in the grey zone (v1.0.0) R. Kriegmair https://doi.org/10.5281/zenodo.4740252

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Short summary
Our regional numerical weather prediction models run at kilometer-scale resolutions. Processes that occur at smaller scales not yet resolved contribute significantly to the atmospheric flow. We use a neural network (NN) to represent the unresolved part of physical process such as cumulus clouds. We test this approach on a simplified, yet representative, 1D model and find that the NN corrections vastly improve the model forecast up to a couple of days.