Fei Zengping, Wang Hongqing, Zhang Yan, et al. MCS identification and tracking based on geo-satellite IR images. J Appl Meteor Sci, 2011, 22(1): 115-122.
Citation: Fei Zengping, Wang Hongqing, Zhang Yan, et al. MCS identification and tracking based on geo-satellite IR images. J Appl Meteor Sci, 2011, 22(1): 115-122.

MCS Identification and Tracking Based on Geo-satellite IR Images

  • Received Date: 2010-01-10
  • Rev Recd Date: 2010-10-19
  • Publish Date: 2011-02-28
  • MCS (mesoscale convection systems) are significant weather systems causing heavy rain, hail and other severe weather events. Many disastrous weathers are usually caused by strong convection systems of 10—200 kilometers, but they are very difficult to forecast in operation. Geostationary satellite infrared imagery with higher spatial and temporal resolution provides much practical information for identifying and tracking MCS automatically from a broader perspective. Many researches are implemented on MCS based on geostationary satellite infrared imagery, amending the MCS judgment standard according to the actual condition of the weather. However, the lack of mature auto-tracking software has limited the extensive surveying of MCS using geostationary satellite. Artificial method is too onerous and error prone.An automatic method of identifying, saving, tracking and characteristics recording has been established based on imagery processing and time series analyzing. First, smooth sharp noise of the satellite image with mean filtering method and median filtering method. Then binary convert the preprocessed images, identify a MCS cloud regiment by marking and extracting the characteristic quantity, and get each target cloud regiment of time sequence. By computing the possible position, the target MCS, is checked if its characteristic matches with the stored information in area, strength, etc. Thus, the time sequence of the MCS cloud regiment is tracked automatically. The method is applied in MCS identifying, tracking automatically with characteristic statistics during the flood over Huaihe River in 2003, and the validation results show that this method has the ability of identifying MCS quickly each time, as well as tracking MCS of multi-time effectively.
  • Fig. 1  The identifier of MCS

    (a) the figure after pretreatment, (b) the binary figure gotten by TBB≤-52℃, (c) the figure gotten by MCS criterion based on the binary figure

    Fig. 2  The 4-D storage configuration of MCS

    Fig. 3  The track of MCS cloud clusters from 21 July to 22 July in 2003

    Fig. 4  The track of MCS cloud cluster A from 21 July to 22 July in 2003

    Fig. 5  The track of MCS cloud cluster B from 21 July to 22 July in 2003

    Table  1  Definition of MCCs by Maddox[2]

    项目 物理特征
    尺度 TBB≤-32℃的连续冷云区面积>100000 km2
    TBB≤-52℃的连续冷云区面积>50000 km2
    生成 第1次满足尺度定义① 和② 的时刻
    生命期 满足尺度定义① 和② 的时间>6 h
    最大的空间范围 连续冷云罩 (TBB≤-32℃) 的最大面积
    形状 在最大空间范围时椭圆率 (短轴/长轴)≥0.7
    消亡 尺度定义① 和② 不再满足的时刻
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    • Received : 2010-01-10
    • Accepted : 2010-10-19
    • Published : 2011-02-28

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