DSG5降水天气现象仪对一次雨雪转换天气过程的识别分析
作者:
作者单位:

作者简介:

通讯作者:

中图分类号:

基金项目:

山东省气象局面上项目(2022sdqxm14)、临沂市气象局自立课题(2022lyqx03)、山东省气象局引导类项目(2023SDYD31)资助


Particle Spectral Characterization of a Rain-to-Snow Event and Identification Process of DSG5 Precipitation Weather Phenomenometer
Author:
Affiliation:

Fund Project:

  • 摘要
  • |
  • 图/表
  • |
  • 访问统计
  • |
  • 参考文献
  • |
  • 相似文献
  • |
  • 引证文献
  • |
  • 资源附件
  • |
  • 文章评论
    摘要:

    本文分析了一次雨雪转换天气中DSG5降水天气现象仪形成的各级数据间的关系及其对天气现象的判识过程,研究了降水粒子谱及气温、地面温度和草面温度等气象要素的变化特征,利用ECMWF模式和双偏振多普勒雷达资料探讨了雨雪转换的天气背景及不同相态降水粒子的空间分布。主要结论如下:降水过程中,随着回流冷空气的增强,近地面冷气层变厚变冷,其上的暖气层逐渐变薄直至消失,测站先后经历了雨滴、雨滴加冰粒和冰粒加雪花3个主要的降水阶段。测站上空降水粒子相态的变化在双偏振多普勒雷达相关系数的空间分布上有明确的反映。在由雨转雪的过程中,地面降水粒子的尺度谱明显变宽,速度谱明显收窄;总体上DSG5的判识结果与双偏振多普勒雷达和其他观测资料的分析结果相吻合。DSG5判断的降水开始时间比实际降水滞后了5 min,降水结束时间提前了6 min,判断的过程总降水时长偏短。可以利用降水过程和雷达回波的连续性对DSG5的判识结果进行优化。

    Abstract:

    In this paper, the relationship between the data at all levels formed by DSG5 in a rain-snow transition weather process and its identification process of weather phenomena are analyzed. The variation characteristics of the precipitation particle spectrum and meteorological elements such as air temperature, ground temperature and grass surface temperature in the process of rain-snow transition are studied. The ECMWF model data and dual-polarization Doppler radar data are used to explore the weather background of rain-snow transition and the spatial distribution of precipitation particles in different phases. It is found that: Before the start of precipitation, a cold air layer formed at the bottom of the warm air layer below 2 km above the station due to the influence of the backflow cold air, and the snowflakes in the upper layer experienced different degrees of melting after falling into the warm air layer. With the enhancement of the backflow cold air, the cold air layer near the ground gradually became thicker, the temperature became colder, and the warm layer gradually became thinner. The station experienced three main precipitation stages: raindrops, raindrops plus ice particles, and ice particles plus snowflakes. The phase change of precipitation particles over the station was clearly reflected in the spatial distribution of the correlation coefficient of the dual-polarisation Doppler radar. In the process of changing from rain to snow, the scale spectrum of surface precipitation particles obviously widened, and the velocity spectrum obviously narrowed. The raindrop scale time spectrum and velocity time spectrum better reflected the changes in the phase state of precipitation particles. The distribution of parameters such as the correlation coefficient of dual-polarisation Doppler radar and the changes of air temperature, ground temperature, and grass surface temperature assisted DSG5 in judging the precipitation weather phenomenon. In general, the identification results of DSG5 precipitation weather phenomenon were consistent with the analysis results of dual-polarisation Doppler radar and other observation data. To avoid interference, the particle number threshold was adopted by DSG5, which made the start time of precipitation judged by DSG5 lag by 5 minutes, the end time of precipitation advance by 6 minutes, and the total duration of precipitation judged by DSG5 was obviously shorter. According to the continuity of the precipitation process and radar echo, the time periods before and after the precipitation process identified by DSG5 were included in the corresponding weather process, and the identification results of DSG5 were optimised to overcome the problem that the total precipitation time of DSG5 was too short.

    参考文献
    相似文献
    引证文献
引用本文

申高航,刘婷婷,王子悦,高安春,宋莹华. DSG5降水天气现象仪对一次雨雪转换天气过程的识别分析[J].气象科技,2024,52(6):787~796

复制
分享
文章指标
  • 点击次数:
  • 下载次数:
  • HTML阅读次数:
  • 引用次数:
历史
  • 收稿日期:2023-10-30
  • 定稿日期:2024-08-14
  • 录用日期:
  • 在线发布日期: 2024-12-25
  • 出版日期:
您是第位访问者
技术支持:北京勤云科技发展有限公司