Evaluations and Ensemble Approaches of Western-Pacific Subtropical High and South-Asian High Ensemble Forecasting in GRAPES-GEPS

  • Li Gao ,
  • Pengfei Ren ,
  • Fang Zhou ,
  • Jiawen Zheng ,
  • Hongli Ren
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  • 1.Numerical Weather Prediction Center of CMA, National Meteorological Center, Beijing 100081,China
    2.State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081,China
    3.Climate Change Research Center, Institute of Atmospheric Physics, and Nansen-Zhu International Research Centre, Chinese Academy of Sciences, Beijing 100029,China
    4.Guangzhou Meteorological Service, Guangdong Province Meteorological Bureau, Guangzhou 511430,China
Gao Li (1978-), female, Alashan Zuoqi, Inner Mongolia Autonomous Region, Senior engineer. Research areas include weather dynamics and ensemble forecast. E-mail: gaol@cma.gov.cn

Received date: 2020-05-31

  Revised date: 2020-06-30

  Online published: 2020-08-21

Supported by

the National Key Research and Development Program of China "Research and development of short-medium-range numerical weather forecasting techniques and their applications to the 2022 Olympic Winter Games"(2018YFF0300103);The National Natural Science Foundation of China "Medium-range weather predictability and ensemble-based probabilistic forecasting method of extreme temperature event in China"(41875138)

Abstract

Based on the operational standard indices, the prediction skills of the Western-Pacific Subtropical High (WPSH) and South-Asian High (SAH) using 2019 real-time forecasts derived from the Global Ensemble Prediction System of GRAPES (GRAPES-GEPS) in China Meteorological Administration (CMA) Numerical Prediction Center were evaluated and the effects of different ensemble approaches on the prediction skills of WPSH and SAH indices were further investigated in this study. The results show that for WPSH, the GRAPES-GEPS has its highest prediction skill for the ridge line index, considerably high skill for the intensity and area indices, but relatively low skill for the western boundary index, and for SAH, it has comparatively high skill for the intensity and center latitude indices, but relatively lower skill for the center longitude index. Prediction errors of the GRAPES-GEPS for the WPSH forecasts are featured by the weaker intensity and area and the more eastward center position, compared with the observation, which can be effectively reduced by employing the maximum/minimum approach from ensemble members, relative to the ensemble mean approach. By direct comparison, prediction errors of the GRAPES-GEPS for the SAH forecasts are featured by the weaker intensity and the more southward center position, which tends to be slightly reduced using the ensemble mean approach. Finally, for the extreme forecast, the maximum approach provides superior performance for both WPSH and SAH than the ensemble mean approach, which can be validated in terms of the two extreme cases. These results clearly indicate that the maximum approach could better improve the GRAPES-GEPS performance for the extreme forecasting of the two primary circulation patterns than the traditional ensemble mean approach.

Cite this article

Li Gao , Pengfei Ren , Fang Zhou , Jiawen Zheng , Hongli Ren . Evaluations and Ensemble Approaches of Western-Pacific Subtropical High and South-Asian High Ensemble Forecasting in GRAPES-GEPS[J]. Advances in Earth Science, 2020 , 35(7) : 715 -730 . DOI: 10.11867/j.issn.1001-8166.2020.060

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