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基于骨架的线状对流系统客观量化识别算法研究

盛杰 郑永光 沈新勇 张小雯

盛杰, 郑永光, 沈新勇, 等. 2020. 基于骨架的线状对流系统客观量化识别算法研究[J]. 大气科学, 44(6): 1291−1304 doi:  10.3878/j.issn.1006-9895.2004.19210
引用本文: 盛杰, 郑永光, 沈新勇, 等. 2020. 基于骨架的线状对流系统客观量化识别算法研究[J]. 大气科学, 44(6): 1291−1304 doi:  10.3878/j.issn.1006-9895.2004.19210
SHENG Jie, ZHENG Yongguang, SHEN Xinyong, et al. 2020. Research on Skeleton-Based Objective Quantization and Identification Algorithm for Quasi-linear Convective Systems [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 44(6): 1291−1304 doi:  10.3878/j.issn.1006-9895.2004.19210
Citation: SHENG Jie, ZHENG Yongguang, SHEN Xinyong, et al. 2020. Research on Skeleton-Based Objective Quantization and Identification Algorithm for Quasi-linear Convective Systems [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 44(6): 1291−1304 doi:  10.3878/j.issn.1006-9895.2004.19210

基于骨架的线状对流系统客观量化识别算法研究

doi: 10.3878/j.issn.1006-9895.2004.19210
基金项目: 国家重点研发计划项目2018YFC1506104、2018YFC1507506、2017YFC1502003,国家自然科学基金项目41790471、41530427、41975054、41930967,中国科学院战略性先导科技专项XDA20100304
详细信息
    作者简介:

    盛杰,男,1984年出生,硕士研究生,高级工程师,主要从事强对流预报方法研究。E-mail: shengjie@cma.gov.cn

    通讯作者:

    沈新勇,E-mail: shenxy@nuist.edu.cn

  • 中图分类号: P409

Research on Skeleton-Based Objective Quantization and Identification Algorithm for Quasi-linear Convective Systems

Funds: National Key Research and Development Program of China (Grants 2018YFC1506104, 2018YFC1507506, 2017YFC1502003), National Natural Science Foundation of China (Grants 41790471, 41530427, 41975054, 41930967), Strategic Priority Research Program of the Chinese Academy of Sciences (Grant XDA20100304)
  • 摘要: 本文将计算机图形学骨架概念应用到气象学领域,发展了回波图像预处理、骨架修剪处理以及长宽比量化处理技术,该方法能自动识别出雷达回波拼图中符合气象学标准的线状对流系统(quasi-linear convective systems,QLCSs)。首先结合2016年黄淮地区一次双QLCSs过程给出了基于骨架的QLCSs客观量化算法的具体技术流程,然后利用该方法对2016年6月安徽地区的QLCSs进行客观筛选,并进一步量化识别QLCSs的移动特征,结合灾害天气实况与主观识别进行对比评估,结果表明:结合气象学标准改造的骨架图像识别算法,较好保留了气象回波形状信息,在准确量化对流系统长短轴的基础上,实现QLCSs的有效识别。而获得的量化移动矢量等特征,一方面可应用于致灾QLCSs的分类研究,为开展长序列统计及致灾机理分析提供个例识别方法和量化特征,另一方面也为QLCSs的短临监测预警业务提供新的思路。
  • 图  1  基于骨架的线状对流系统(QLCSs)识别算法流程示意图

    Figure  1.  Flow diagram of skeleton-based identification algorithm for the quasi-linear convection systems (QLCSs)

    图  2  2016年6月13日QLCSs组合反射率(单位:dBZ):(a)初始阶段(10:50,协调世界时,下同);(b)成熟阶段(14:30);(c)合并阶段(17:40);(d)消亡阶段(21:30)

    Figure  2.  Composite reflectivity (units: dBZ) of QLCSs at (a) initiation stage (1050 UTC), (b) mature stage (1430 UTC), (c) merging stage (1740 UTC), and (d) dissipation stage (2130 UTC) on June 13, 2016

    图  3  图2,但为不小于40 dBZ回波二值化图像(白色为不小于40 dBZ的区域,赋值为255;黑色为小于40 dBZ的区域,赋值为0)

    Figure  3.  Same as Fig. 2, but for binarized images of radar echoes not less than 40 dBZ (Radar echo value assigned 255 is not less than 40 dBZ, and radar echo value assigned 0 is less than 40 dBZ)

    图  4  图2,但为回波二值化图像闭运算结果

    Figure  4.  Same as Fig. 2, but for the closed operation of echo binarized images

    图  5  图2,但为回波二值化图像骨架

    Figure  5.  Same as Fig. 2, but for the skeletons of echo binarized images

    图  6  图2,但为回波二值化图像骨干和几何距离转换(EDT)结果分布。图中阴影表示图4中白色区域内的点到黑色边界的最短距离,单位:km

    Figure  6.  Same as Fig. 2, but for the backbones of echo binarized image and distributions of Euclidean Distance Transform (EDT) results. Shadings represent the shortest distance from the point in the white area to the black boundary in Fig, 4, units: km

    图  7  图2,单时次QLCSs识别结果

    Figure  7.  Same as Fig. 2, but for single-time identification results of QLCSs

    图  8  2016年6月13日双QLCSs过程骨干图(1 h间隔,颜色越深代表时间越早)

    Figure  8.  Backbone map of double QLCSs on 13 June, 2016 (1-hour intervals, the darker the color, the earlier the time)

    图  9  2016年6月安徽地区QLCSs识别结果(轨迹线间隔均为1 h,颜色越深代表时间越早,红色轨迹线表示QLCSs移动方向与伸展方向平均夹角大于45°、移动速度快于10 m s−1。绿色点为QLCSs发生时段内累积雨量>100 mm站点,蓝色点为瞬时风速>17.2 m s−1雷暴大风站点)

    Figure  9.  Maps of QLCSs in June 2016 in Anhui Province (1-hour intervals, the darker the color, the earlier the time. The red lines indicate QLCSs with velocities greater than 10 m s−1, and an angle between the moving vector and the direction of QLCS greater than 45°. The green dots indicate stations with accumulated rainfall > 100 mm and the blue dots stations with wind speeds > 17.2 m s−1)

    图  10  QLCSs移动方向和伸展方向平均夹角与QLCSs移速散点图。绿点代表大暴雨过程;红点代表8级以上大风过程;黑点表征无上述两类天气发生的过程。持续时间(单位:min)用数字标在点的下方,并与点的面积成正相关

    Figure  10.  Scatter diagrams of AMS (the angle between the moving vector and the extension direction of the QLCSs) and moving speed of the QLCSs, with green dots representing a large heavy rain process, red dots a gale process greater than force 8, and black dots a process without the above two kinds of weather; duration (units: min) is indicated as a number below the point and has a positive correspondence with the size of the dot

    表  1  相关文献中线状对流系统(QLCSs)标准

    Table  1.   Criteria used in the literature to define the quasi-linear convection systems (QLCSs)

    Geerts(1998)Parker and Johnson(2000)俞小鼎等(2006)Meng et al.(2013)
    大于20 dBZ回波带超过100 km,持续时间4 h,大于40 dBZ长宽比5∶1,超过2 h。大于40 dBZ回波带连续或者准连续大于100 km,时间超过3 h,并共有一个回波前缘。线性多单体风暴中35 dBZ部分的长宽比超过5∶1,长度至少在50 km 之上。大于40 dBZ回波带呈现线性且大于100 km的时间超过3 h,并有共同移动前缘。
    下载: 导出CSV

    表  2  2016年6月安徽地区的QLCSs主、客观识别结果对比

    Table  2.   Comparison of subjective and objective identifications of QLCSs in June 2016 in Anhui Province

    QLCSs主观筛选结果QLCSs客观识别及量化结果
    序号发生时段持续时间/min发生区域识别时段持续时间/minQLCSs整体移速/m s−1QLCSs移动方向和
    伸展方向平均夹角/(°)
    12日02:20~09:00400安徽南部02:50~08:503601314
    25日01:20~09:40500安徽西北部01:30~09:204701068
    311日16:10~12日01:10540安徽中南部16:20~01:40560650
    419日19:10~23:40270安徽中南部19:30~23:24234125
    520日03:48~07:30220安徽中东部03:12~07:30256312
    620日22:36至21日07:30534安徽中北部22:48~07:125041215
    722日06:30~09:30180安徽西南部06:12~09:301981249
    824日10:18~19:00/522安徽中西部10:24~19:24540465
    926日14:12~18:00228安徽中东部14:30~18:122221765
    1030日17:30至1日00:24714安徽中南部17:36~01:00744247
    下载: 导出CSV
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出版历程
  • 收稿日期:  2019-09-10
  • 网络出版日期:  2020-05-09
  • 刊出日期:  2020-11-15

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