Articles | Volume 14, issue 10
https://doi.org/10.5194/gmd-14-6241-2021
https://doi.org/10.5194/gmd-14-6241-2021
Development and technical paper
 | 
18 Oct 2021
Development and technical paper |  | 18 Oct 2021

A micro-genetic algorithm (GA v1.7.1a) for combinatorial optimization of physics parameterizations in the Weather Research and Forecasting model (v4.0.3) for quantitative precipitation forecast in Korea

Sojung Park and Seon K. Park

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Cited articles

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Short summary
One of the biggest uncertainties in numerical weather predictions (NWPs) comes from treating subgrid-scale physical processes. Physical processes, such as cumulus, microphysics, and planetary boundary layer processes, are parameterized in NWP models by empirical and theoretical backgrounds. We developed an interface between a micro-genetic algorithm and the WRF model for a combinatorial optimization of physics for heavy rainfall events in Korea. The system improved precipitation forecasts.
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