| 低空急流识别及急流轴自动绘制方法研究 |
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| 引用本文： | 王萍,王琮,王迪.低空急流识别及急流轴自动绘制方法研究[J].气象,2018,44(7):952-960. |
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| 作者姓名： | 王萍 王琮 王迪 |
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| 作者单位： | 天津大学电气自动化与信息工程学院 |
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| 基金项目： | 公益性行业(气象)科研专项(GYHY201406004)资助 |
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| 摘 要： | 低空急流对强对流天气的预报有重要意义。针对目前低空急流主要由手工绘制,存在效率低、易受主观因素影响的问题,本文基于MICAPS高空全要素填图数据中的探空站风场信息,提出了一种低空急流自动识别及急流轴自动绘制算法。算法从急流轴定义出发,依次从风速、风向、探空站分布、中轴线位置等多个角度对低空急流轴进行检测。经过传递闭包聚类、急流轴关键点提取、不同风向急流轴关键点归并、急流轴平滑等步骤,实现了低空急流自动识别及急流轴的自动绘制。测试表明,在识别的基础上自动绘制的急流轴具有位置准确、形态自然、能完整反映急流水汽输送路径、适应复杂环境低空急流等特点。在291组测试数据中未发现空报,准确击中率达到94.96%。
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| 关 键 词： | 低空急流，自动识别，传递闭包聚类 |
| 收稿时间： | 2017/7/7 0:00:00 |
| 修稿时间： | 2017/9/3 0:00:00 |
Research on Low Level Jet Identification and Automatic Drawing Method |
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| WANG Ping,WANG Cong and WANG Di.Research on Low Level Jet Identification and Automatic Drawing Method[J].Meteorological Monthly,2018,44(7):952-960. |
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| Authors: | WANG Ping WANG Cong and WANG Di |
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| Institution: | School of Electrical and Information Engineering, Tianjin University, Tianjin 300072,School of Electrical and Information Engineering, Tianjin University, Tianjin 300072 and School of Electrical and Information Engineering, Tianjin University, Tianjin 300072 |
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| Abstract: | Low level jet is important for predicting severe convective weather. At present, the identification of low level jet is conducted mainly by handwork, which brings the problem of low efficiency, easily influenced by subjective factors. So, based on the wind field data of the sounding stations in MICAPS, we propose an automatic low level jet identification and drawing algorithm in this paper. The algorithm is based on the definition of the low level jet axis, and detects the low level jet axis from several aspects in terms of wind speed, wind direction, sounding station distribution, and the central axis position. Then after the steps of transitive closure clustering, key points extracting, low level jet axis merging and the axis smooth ing, the automatic identification and drawing of low level jet are achieved. The test result shows that the jet axis, which is automatically drawn, has the characteristics of accurate position and natural shape. Besides, it could reflect the transport path of water vapor in jet, and adapt to the complex environment of low level jet. In the 291 test data, the identification rate reaches 94.96% and false alarm is not found. |
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| Keywords: | low level jet automatic identification transitive closure clustering |
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