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MCS Identification and Tracking Based on Geo-satellite IR Images
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摘要: 由于缺乏成熟的中尺度对流系统 (MCS) 自动追踪工具，使基于静止卫星红外云图的MCS研究的深度和广度受到制约。手工目测法识别追踪MCS，工作量大且容易造成误差，无法用于长时间序列卫星云图的MCS普查。该文结合我国中尺度对流天气的特点，在重新定义MCS云团识别标准的基础上，给出了一种基于图像处理和时间序列分析技术的MCS自动识别、存储、追踪和时间序列特征统计方法。通过对2003年淮河大水期间连续时次卫星云图的MCS自动识别、追踪和特征统计，对该方法的应用效果进行了检验，结果表明:该方法不仅能对每个时次的MCS进行快速识别，同时也能对多时次的MCS进行有效追踪。Abstract: 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.
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Key words:
- satellite image;
- MCS;
- image processing;
- time sequence analysis
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图 1 MCS的识别
(a) 预处理后的图像，(b) 按照TBB≤-52℃得到的二值图像，(c) 在二值图像的基础上，按照MCS判据提取的目标
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
图 3 2003年7月21—22日MCS云团的追踪
Fig. 3 The track of MCS cloud clusters from 21 July to 22 July in 2003
图 4 2003年7月21—22日MCS云团A的追踪结果
Fig. 4 The track of MCS cloud cluster A from 21 July to 22 July in 2003
图 5 2003年7月21—22日MCS云团B的追踪结果
Fig. 5 The track of MCS cloud cluster B from 21 July to 22 July in 2003
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[1] Orlanski L A. A rational subdivision of scales for atmospheric processes. Bull Amer Meteor Soc, 1975, 56: 527-530. http://geomorphometry.org/content/rational-subdivision-scales-atmospheric-processes [2] Maddox R A. Mesoscale convective complexes. Bull Amer Meteor Soc, 1980, 61: 1374-1387. doi: 10.1175/1520-0477(1980)061<1374:MCC>2.0.CO;2 [3] Shibagaki Y, Yabanaka M D, Shimizu S, et al. Meso-β to meso-γ-scale wind circulations associated with precipitating clouds near Beiu front observed by the MU and meteorological radars. Meteor Soc Jappan, 2000, 78 : 69-91. doi: 10.2151/jmsj1965.78.1_69 [4] 江吉喜.一次特大沙尘暴成因的卫星云图分析.应用气象学报, 1995, 6(2): 177-184. http://qikan.camscma.cn/jams/ch/reader/view_abstract.aspx?file_no=19950229&flag=1 [5] 何立富, 陈涛, 谌芸, 等.大气探测资料在中尺度暴雨中的分析和应用.应用气象学报, 2006, 17(增刊): 88-97. http://www.cnki.com.cn/Article/CJFDTOTAL-KJCB201216086.htm [6] 国家气象中心, 国家卫星气象中心. 98中国大洪水与天气预报.北京:气象出版社, 1999. [7] 费增坪, 郑永光, 张焱, 等.基于静止卫星红外云图的MCS普查研究进展及标准修订.应用气象学报, 2008, 19(1):82-90. http://qikan.camscma.cn/jams/ch/reader/view_abstract.aspx?file_no=20080113&flag=1 [8] Anderson C J, Arritt R W. Mesoscale convective complexes and persistent elongated convective systems over the United States during 1992 and 1993. Mon Wea Rev, 1998, 126: 578-599. doi: 10.1175/1520-0493(1998)126<0578:MCCAPE>2.0.CO;2 [9] 马禹, 王旭, 陶祖钰.中国及其邻近地区中尺度对流系统的普查和时空分布特征.自然科学进展, 1997, 7:701-706. doi: 10.3321/j.issn:1002-008X.1997.06.010 [10] 费增坪, 郑永光, 王洪庆. 2003年淮河大水期间MCS的普查分析.气象, 2005, 31(13):18-22. http://www.cnki.com.cn/Article/CJFDTOTAL-QXXX200512003.htm [11] Fujita T, Bradbnry D L, Murino C, et al. A Study of Mesoscale Cloud Motions Computed from ATS2 Ⅰand Terrestrial Photographs. SMRP Res Pap 71, University of Chicago, 1968: 25. [12] Smith E A. The McIDAS System. IEEE Trans Geosci Electron GE-13, 1975: 123-136. [13] Endlish R M, Wolf D E, Hall D J, et al. Use of a pattern recognition technique for determining cloud motions from sequences of satellite photographs. J Appl Meteor, 1971, 10: 105-117. doi: 10.1175/1520-0450(1971)010<0105:UOAPRT>2.0.CO;2 [14] Hall D J, Endlish R M, Wolf D E, et al. Experiments in automatic cloud tracking using SMSGOES Data. J Appl Meteor, 1977, 16: 1219-1230. doi: 10.1175/1520-0450(1977)016<1219:EIACTU>2.0.CO;2 [15] Arking A, Robert C L, Rosenfield A. A furrier approach to cloud motion estimation. J Appl Meteor, 1978, 17: 735-744. doi: 10.1175/1520-0450(1978)017<0735:AFATCM>2.0.CO;2 [16] 王登炎. MCS的形态特征和外推预报.气象, 2000, 26(8): 22-24. doi: 10.7519/j.issn.1000-0526.2000.08.006 [17] 肖稳安, 褚昭利, 徐辉.中尺度对流复合体的降水特征和预报.南京气象学院学报, 1995, 18(1): 107-112. http://www.cnki.com.cn/Article/CJFDTOTAL-NJQX501.015.htm [18] 白洁, 王洪庆, 陶祖钰. GMS卫星红外云图强对流云团的识别与追踪.热带气象学报, 1997, 13(2): 158-167. http://www.cnki.com.cn/Article/CJFDTOTAL-RDQX702.007.htm [19] Zheng Yongguang, Tao Zuyu, Wang Hongqing, et al. Enviroment of meso-α-scale convective system development in yellow Sea region. Progress in Natural Science, 1999, 9(7): 842-848. http://kns.cnki.net/KCMS/detail/detail.aspx?filename=zkjy199911005&dbname=CJFD&dbcode=CJFQ -
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