Correcting for model changes in statistical postprocessing – an approach based on response theory

Demaeyer, Jonathan; Vannitsem, Stéphane

doi:https://doi.org/10.5194/npg-27-307-2020

Articles | Volume 27, issue 2

https://doi.org/10.5194/npg-27-307-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Special issue:

Advances in post-processing and blending of deterministic...

https://doi.org/10.5194/npg-27-307-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 27, issue 2

Research article

|

27 May 2020

Research article |

| 27 May 2020

Correcting for model changes in statistical postprocessing – an approach based on response theory

Jonathan Demaeyer and Stéphane Vannitsem

Supplement

https://doi.org/10.5194/npg-27-307-2020-supplement

Model code and software

Quasi-Geostrophic Spectral model - qgs: version 0.1.0 release (Version v0.1.0) J. Demaeyer and L. De Cruz https://doi.org/10.5281/zenodo.3716322

Postprocessing and response theory notebooks J. Demaeyer https://doi.org/10.5281/zenodo.3755313

Short summary

Postprocessing schemes used to correct weather forecasts are no longer efficient when the model generating the forecasts changes. An approach based on response theory to take the change into account without having to recompute the parameters based on past forecasts is presented. It is tested on an analytical model and a simple model of atmospheric variability. We show that this approach is effective and discuss its potential application for an operational environment.