Improvement of typhoon rainfall prediction based on optimization of the Kain-Fritsch convection parameterization scheme using a micro-genetic algorithm

doi:10.1007/s11707-019-0798-0

Front. Earth Sci.

2019, Vol. 13

Issue (4) : 721-732 https://doi.org/10.1007/s11707-019-0798-0

RESEARCH ARTICLE

Improvement of typhoon rainfall prediction based on optimization of the Kain-Fritsch convection parameterization scheme using a micro-genetic algorithm

Jia ZHU^1,², Jiong SHU^1,²(

), Xing YU³

¹. Key Laboratory of Geographic Information Science (Ministry of Education), East China Normal University, Shanghai 200241, China
². School of Geographic Sciences, East China Normal University, Shanghai 200241, China
³. Beijing Thematic Technology Co., Ltd., Beijing 100020, China

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Abstract

Inclusion of cloud processes is essential for precipitation prediction with a numerical weather prediction model. However, convective parameterization contains numerous parameters whose values are in large uncertainties. In particular, it is still not clear how the parameters of a sub-grid-scale convection scheme can be modified to improve high-resolution precipitation prediction. To address these issues, a micro-genetic (micro-GA) algorithm is coupled to the Kain-Fritsch (KF) convective parameterization scheme (CPS) in the WRF to improve the quantitative precipitation forecast (QPF). The optimization focuses on two parameters in the KF scheme: the convective time scale and the conversion rate. The optimizing process is controlled by the micro-GA using a QPF skill score as the fitness function. Two heavy rainfall events related to typhoons that made landfall over the south-east coastal region of China are selected, and for each case the parameter values are adjusted to achieve the best QPF skill. Significant improvements in QPF are evident with an increase in the average equitable threat score (ETS) by 5.8% for the first case, and by 18.4% for the second case. The results demonstrate that the micro-GA-KF coupling system is effective in optimizing the parameter values, which affect the applicability of CPS in a high-resolution model, and therefore improves the rainfall prediction in both ETS and spatial distribution.

Keywords quantitative precipitation forecast micro-GA Kain-Fritsch scheme typhoon

Corresponding Author(s): Jiong SHU

Just Accepted Date: 24 October 2019 Online First Date: 29 November 2019 Issue Date: 30 December 2019

Cite this article:

Jia ZHU,Jiong SHU,Xing YU. Improvement of typhoon rainfall prediction based on optimization of the Kain-Fritsch convection parameterization scheme using a micro-genetic algorithm[J]. Front. Earth Sci., 2019, 13(4): 721-732.

URL:

https://academic.hep.com.cn/fesci/EN/10.1007/s11707-019-0798-0
https://academic.hep.com.cn/fesci/EN/Y2019/V13/I4/721

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