Weather and Climate

Environmental parameters and forecast models of hail events

  • Nana YI ,
  • Lijuan SU ,
  • Xucheng ZHENG ,
  • Yue XIN ,
  • Min CAI ,
  • Hui LI ,
  • Yuchen JIN
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  • 1. Weather Modification Center of Inner Mongolia, Hohhot 010051, Inner Mongolia, China
    2. Meteorological Science Institute of Inner Mongolia, Hohhot 010051, Inner Mongolia, China

Received date: 2023-08-25

  Revised date: 2023-10-13

  Online published: 2024-01-24

Abstract

Based on the hail observation records of 119 national stations in Inner Mongolia and ERA5 reanalysis data from 1959 to 2021, the differences in layer formation, water vapor, typical temperature layer height, vertical wind shear, and cloud microphysical quantities between hail and nonhail were analyzed. A hail prediction model was established to provide an objective and quantitative basis for potential hail forecasting. The results revealed that the K-index, pseudo-equivalent temperature difference, vertical wind shear, specific humidity, rain water mixing ratio, snow water mixing ratio, ice water mixing ratio, and liquid water mixing ratio were not well distinguished between hail and nonhail. The total index was >50 °C, temperature difference between 850 hPa and 500 hPa was ≥28.4 °C, precipitable water vapor was ≤24 mm, height of -20 °C was <7.05 km, and the height of -20 °C to 0 °C was ≤3.15 km. The above environmental parameter thresholds were able to identify >70% of hail samples, and the reverse condition can identify >70% of nonhail samples. Based on the analysis of the environmental parameters of hail and nonhail samples, the Fisher discriminant method was used to establish a hail prediction model using the total index, temperature difference between 850 hPa and 500 hPa, height of -20 °C to 0 °C, and precipitable water vapor. The accuracy of the model discrimination exceeded 80%.

Cite this article

Nana YI , Lijuan SU , Xucheng ZHENG , Yue XIN , Min CAI , Hui LI , Yuchen JIN . Environmental parameters and forecast models of hail events[J]. Arid Zone Research, 2024 , 41(1) : 13 -23 . DOI: 10.13866/j.azr.2024.01.02

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