Articles | Volume 18
https://doi.org/10.5194/asr-18-145-2021
https://doi.org/10.5194/asr-18-145-2021
17 Sep 2021
 | 17 Sep 2021

Addressing up-scaling methodologies for convection-permitting EPSs using statistical and machine learning tools

Tiziana Comito, Colm Clancy, Conor Daly, and Alan Hally

Model code and software

Convection-permitting-EPS-Up-scaling-1.0 T. Comito https://github.com/Phy-Flux/Convection-permitting-EPS-Up-scaling-.git

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Short summary
Convection-permitting models allow for prediction of rainfall events with increasing levels of detail. However, this increased resolution can create problems such as the so-called double penalty problem when attempting to verify model forecast accuracy. This problem is amplified when trying to maximise the value of a convection-permitting ensemble prediction system (EPS). Post-processing of the EPS can help to overcome these issues. In this spirit, two new up-scaling algorithms based on Machine