Page 142 - 《高原气象》2025年第5期

高 原 气 象 44 卷
1260

Identification of Mixed Precipitation Particles and Analysis of

Scale Spectrum Characteristics of Rain， Snow and Hail

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ZOU Shuping ， KE Liping ， XIONG Kai ， LI Dezhang ， HUANG Yu ， CHEN Bailian 1
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（1. Guizhou Mountainous Meteorological Science research Institute， Guiyang 5500081， Guizhou， China；
2. Weining County Meteorological Bureau of Guizhou Province， Weining 553100， Guizhou， China；
3. Wuchuan County Meteorological Bureau of Guizhou Province， Wuchuan 564300， Guizhou， China；
4. Bijie Meteorological Bureau， Bijie 551700， Guizhou， China）
Abstract： Based on the observation time series data of Guizhou DSG1 precipitation phenomenon instrument
from 2018 to 2023， the particle number distribution and scale spectrum characteristics of rain， snow and hail
three types precipitation were compared and analyzed， and an integrated determination algorithm for precipita‐
tion phenomenon type identification was established based on the particle number， particle spectral width， and
particle plurality， and the applicability of the algorithm was evaluated. The specific conclusions are： （1） The di‐
ameter spectrum widths of rain， snow， and hail droplets are concentrated in the ranges of 1~8 mm， 1~12 mm，
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and 5~12 mm， respectively. The velocity spectra are concentrated in the ranges of 3~15 m∙s ， 3~5 m∙s ， 12~
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15 m∙s ， and the particle plurality velocities are 4. 4 m∙s ， 1. 1 m∙s and 4. 4 m∙s . respectively. The rain and
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snow precipitation types can be effectively recognized by the particle falling velocities.（2） The 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 precipitation （0. 005%）.（3） Particles with particle diameters greater than 3 mm and particle ve‐
locities of less than 5 m∙s mainly exist in the process of snowfall. Particles with particle diameters greater than
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5 mm and particle velocities greater than 10 m∙s mainly exist in the process of hailstorms and short-term heavy
precipitation. Increasing the velocity limit can improve the accuracy of hail particle recognition.（4） By evaluat‐
ing the integrated determination algorithm for precipitation phenomenon type recognition， the 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