HE Guanxing,SU Debin,LI Zhi,et al.Multi-source Detection Data Analysis and Ground Verification of Hail Probability[J].Journal of Chengdu University of Information Technology,2023,38(05):507-515.[doi:10.16836/j.cnki.jcuit.2023.05.003]
降雹概率的多源探测数据分析及地面验证
- Title:
- Multi-source Detection Data Analysis and Ground Verification of Hail Probability
- 文章编号:
- 2096-1618(2023)05-0507-09
- 分类号:
- TN959.4
- 文献标志码:
- A
- 摘要:
- 受特殊地理环境的影响，冰雹天气成为内蒙古巴彦淖尔地区夏季主要气象灾害之一，因此对巴彦淖尔进行降雹概率研究十分必要。基于巴彦淖尔地区雷达、探空、风云四号卫星TBB等气象探测数据和地面观测人员记录的降雹观测信息，研究雷达数据、探空资料对识别冰雹特征的相关算法。通过2020年7月4日发生在巴彦淖尔乌拉特中旗的一次典型降雹过程，运用测雹板和气象服务人员观测的地面降雹结果与冰雹识别算法结果进行对比分析，验证冰雹识别算法。结果表明冰雹识别算法在引入0 ℃层和-20 ℃层的高度信息后，能更加准确地预测出冰雹的发生概率和尺寸信息。
- Abstract:
- Influenced by its special geographical environment, hail weather has become one of the main meteorological disasters in summer in the Bayannur area of Inner Mongolia. Therefore, it is necessary to study the probability of hail in Bayannur. Based on the meteorological detection data such as radar, sounding, and the temperature of black body(TBB)data of Fengyun-4 satellite in Bayannur area, as well as the hailfall observation information recorded by ground observers, this paper studies the correlation algorithm of radar data and sounding data to identify hail characteristics. Through a typical hailfall process that occurred in Bayannur Urad Middle Banner on July 4, 2020, the comparative analysis of the ground hail results observed by hail measuring boards and meteorological service personnel with the results of the hail identification algorithm was used to verify the hail identification algorithm. The results show that the hail recognition algorithm can more accurately predict the hail occurrence probability and size information after introducing the height information of the0 ℃ layer and the -20 ℃ layer.
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备注/Memo
收稿日期:2022-09-15
基金项目:国家自然科学基金资助项目(42075001)