| 王小龙,王彤,李映春,李娟,邓卓雅,王秀花,谢蕊,安斌.基于“葵花8号”气象卫星的陇东南地区强对流识别跟踪技术研究[J].沙漠与绿洲气象,2022,16(5):56~61 |
| 基于“葵花8号”气象卫星的陇东南地区强对流识别跟踪技术研究 |
| Research on Identification and Tracking Technology of Severe Convection in Southeast Gansu Based on Himawari-8 Meteorological |
| 投稿时间：2021-03-12 修订日期：2021-08-30 |
| DOI：10.12057/j.issn.1002-0799.2022.05.008 |
| 中文关键词: 葵花8号气象卫星 强对流云团识别 强对流云团追踪 短时强降水 |
| 英文关键词:Himawari-8 meteorological satellite identification of severe convective clouds tracing of severe convective clouds falling area forecast |
| 基金项目:甘肃省气象局面上项目,基于“向日葵8号”气象卫星的陇东南强对流识别跟踪的技术研究(GSMAMs2018-08) |
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| 中文摘要: |
| 利用常规观测资料、区域自动站资料和“葵花8号”气象卫星资料，对2016年4—9月甘肃省陇东南地区出现的43次强对流天气过程展开分析，确立了强对流云团识别指标、追踪方法及预报指标，并对2018年部分个例进行了效果检验。结果表明：（1）利用卫星B13通道（10.4 μm）亮温值TBB≤238 K或B08通道（6.2 μm）与B13通道亮温差△TBB＜0 K双阈值作为强对流云团识别指标，可以准确识别出陇东南地区的强对流天气云团；（2）利用“逆向搜索法”、“面积重叠法”及对云团重心的计算，可以准确对强对流云团进行定位、追踪及移动路径外推预报；（3）建立的强对流天气落区判别指标对该地区短时强降水及冰雹落区具有一定的预报能力。 |
| 英文摘要: |
| Based on the data of routine observations, regional automatic stations and Himawari-8 meteorological satellite, the 43 severe convection weather processes that occurred in Southeast Gansu between April 2016 and September 2016 were analyzed. The indicator of severe convective cloud recognition, tracking method and forecast indicator were established, and some individual cases of 2018 were tested to validate the effectiveness. The results showed that : (1) Using double threshold values of TBB≤238 K of the B13 channel (10.4 μm) or the TBB difference △TBB＜0 K of the B08 channel (6.2 μm) and the B13 channel as the indicator of severe convective cloud recognition helps accurately identify severe convection weather clouds in Southeast Gansu. (2) Approaches like “reverse searching” and “area overlap” could be used to calculate the center of gravity of clouds, thereby accurately locating and tracking severe convective clouds and extrapolatively forecasting their paths of movement. (3) The indicator to discriminate the fallout zone of convective weather has a certain forecast capacity for the fallout zones of short-time strong rainfall and hail within the region. |
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