Identification of mixed precipitation particles and analysis of scale spectrum characteristics of rainsnow and hail 

ZOU Shuping, KE Liping, XIONG Kai, LI Dezhang, Huang Yu, Chen Bailian

PDF(3753 KB)
Plateau Meteorology ›› 0 DOI: 10.7522/j.issn.1000-0534.2025.00025

Identification of mixed precipitation particles and analysis of scale spectrum characteristics of rainsnow and hail 

  • ZOU Shuping1KE Liping2XIONG Kai3LI DezhangHuang Yu1Chen Bailian1
Author information +
History +

Abstract

Based on the observation time series data of Guizhou DSG1 precipitation phenomenon instrument from 2018 to 2023the particle number distribution and scale spectrum characteristics of rainsnow and hail three types precipitation were compared and analyzedand an integrated determination algorithm for precipitation phenomenon type identification was established based on the particle numberparticle spectral widthand particle pluralityand the applicability of the algorithm was evaluated. The specific conclusions are:(1The diameter spectrum widths of rainsnowand hail droplets are concentrated in the ranges of 1~8 mm1~12 mmand 5~12 mmrespectively. The velocity spectra are concentrated in the ranges of 3~15 m∙s-13~5 m∙s-112~ 15 m∙s-1and the particle plurality velocities are 4. 4 m∙s-11. 1 m∙s-1 and 4. 4 m∙s-1. respectively. The rain and snow precipitation types can be effectively recognized by the particle falling velocities.2The percentages of rain particles in the raindrop and hail drop spectrum accounted for 50. 1% and 64. 3%and the number of snow particles in the snowdrop spectrum accounted for 70. 2%which exceeded half of the total number of particles. The percentage of hail particles in the hail droplet spectrum is 0. 19%which is significantly higher than the short-term heavy precipitation0. 005%.3Particles with particle diameters greater than 3 mm and particle velocities of less than 5 m∙s-1 mainly exist in the process of snowfall. Particles with particle diameters greater than 5 mm and particle velocities greater than 10 m∙s-1 mainly exist in the process of hailstorms and short-term heavy precipitation. Increasing the velocity limit can improve the accuracy of hail particle recognition.4By evaluating the integrated determination algorithm for precipitation phenomenon type recognitionthe accuracy of single precipitation type recognition reaches more than 95%and the false alarm rate of hail is only 1. 7%which can effectively reduce the cases of misrecognition as hail in short-term heavy precipitation.

Key words

Raindrop spectrum / precipitation type / particle identification / particle diameter / falling speed

Cite this article

Download Citations
ZOU Shuping, KE Liping, XIONG Kai, LI Dezhang, Huang Yu, Chen Bailian. Identification of mixed precipitation particles and analysis of scale spectrum characteristics of rainsnow and hail . Plateau Meteorology. 0 https://doi.org/10.7522/j.issn.1000-0534.2025.00025

References

PDF(3753 KB)

55

Accesses

0

Citation

Detail

Sections
Recommended

/