ISSN 1000-0526
CN 11-2282/P
Severe Convective Wind and Hail Probabilistic Forecasting Method Based on Outputs of GRAPES_3 km Model
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National Meteorological Centre, Beijing 100081

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    Abstract:

    Based on the GRAPES_3 km model developed independently by China and calculating the hourly maximum updraft helicity (UH), we have developed the probabilistic forecast technology which exceeds a certain threshold of UH in different forecast time periods. Since the value of UH can represent the ascending motion and rotation intensity of convective storm, the UH probabilistic forecast product can be used as the probabilistic forecast guidance which characterizes severe convective wind and hail. We verified the probabilistic forecast products of daily tests and typical cases in North China, Northeast China and South China from 14 June to 31 July 2019, the results show that it has a good forecast performance. Compared to the subjective forecast, the threat score (TS) of the objective product for severe convective wind and hail is greatly increased in North China, Northeast China and South China, respectively. Especially for the weak large-scale forcing process in South China, the product can significantly reduce the missing alarm rate (MAR) and significantly increase the TS. In addition, the product can predict the shape distribution and moving propagation characteristics of convective storm, and the region of probabilistic forecast is similar to the observation of severe convective wind and hail. We verified the probabilistic forecast products with different UH thresholds and spatial Gaussian smoothing parameters, the results show that the TS of the products calculated by lower UH threshold is higher than that of higher threshold due to lower MAR. The products with Gaussian smoothing parameter of 20 km have the best forecast performance.

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History
  • Received:July 17,2020
  • Revised:April 23,2021
  • Adopted:
  • Online: September 29,2021
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