基于多普勒雷达的边界层辐合线的识别
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摘要
边界层辐合线具有很强的气象风暴灾害的预示能力,它在多普勒雷达图像上表现为一条蜿蜒的、可能有岔路的、宽度不定的、取值变化的、若隐若现的带状区域。
本文对“探测窗”协同加深“印象”算法进行改进,并对辐合线相关潜势特征进行具体提取、统计与分析,用于识别这种具有复杂背景的非规则带状区域,获得了更好的处理结果。本文主要完成了以下两部分工作:
一、改进辐合线的识别算法并对辐合线区域提取骨架。本文针对“探测窗”协同加深“印象”算法原理,对识别问题进行总结,根据大量样本实验,对阈值与相关参数进行调整,再通过细化得到辐合线骨架。
二、利用剖面图知识,对辐合线区域及其附近区域的水汽分布特征进行分析总结;利用对辐合线骨架两侧的风场速度信息提取,分析辐合线的形成特征、运动特征,以及与未来出现的风暴天气的联系,给出一定的结论。
综上所述,本文为边界层辐合线的识别与风暴预测提供了新的思路,所涉及算法均已编程实现,并在样本测试过程中表现出较强的稳定性和令人满意的测试效果。
Boundary convergent lines have strong ability to predict weather storms, which are shown as some winding, possibly to have the branch road and looming belt-shaped regions with uncertain width and change value in the Doppler radar images.
This paper makes improvements to the algorithm including "detection window" and deepen "impression", and identifies potential features of the boundary convergent lines and casts statistical analysis, applies the above algorithm to the complex the irregular belt-shaped region and achieves satisfactory results. This paper has mainly completed the following two tasks:
First, improves the algorithm of identifying boundary convergent lines and extracts skeleton of region of boundary convergent lines. This paper studies the principle of the algorithm including "detection window" and deepen "impression", summarizes problem identification methodology, based on large size of sample survey modifies related threshold value and parameters, and gets skeleton of boundary convergent lines through specification.
Second, applies sectional drawing theory to analyze and summarize water and steam distribution characteristics within and near region of boundary convergent lines; uses wind field speed on both sides of skeleton of boundary convergent lines to extract information, analyze characteristics of boundary convergent lines convergence and movements as well as the relationship between these characteristics and potential stormy weather and provide related conclusions.
In sum, it has developed a new method for boundary convergent lines identification and storm prediction, realized related algorithms and its coding, and achieved strong robustness during sample tests and other satisfactory testing results.
本文对“探测窗”协同加深“印象”算法进行改进,并对辐合线相关潜势特征进行具体提取、统计与分析,用于识别这种具有复杂背景的非规则带状区域,获得了更好的处理结果。本文主要完成了以下两部分工作:
一、改进辐合线的识别算法并对辐合线区域提取骨架。本文针对“探测窗”协同加深“印象”算法原理,对识别问题进行总结,根据大量样本实验,对阈值与相关参数进行调整,再通过细化得到辐合线骨架。
二、利用剖面图知识,对辐合线区域及其附近区域的水汽分布特征进行分析总结;利用对辐合线骨架两侧的风场速度信息提取,分析辐合线的形成特征、运动特征,以及与未来出现的风暴天气的联系,给出一定的结论。
综上所述,本文为边界层辐合线的识别与风暴预测提供了新的思路,所涉及算法均已编程实现,并在样本测试过程中表现出较强的稳定性和令人满意的测试效果。
Boundary convergent lines have strong ability to predict weather storms, which are shown as some winding, possibly to have the branch road and looming belt-shaped regions with uncertain width and change value in the Doppler radar images.
This paper makes improvements to the algorithm including "detection window" and deepen "impression", and identifies potential features of the boundary convergent lines and casts statistical analysis, applies the above algorithm to the complex the irregular belt-shaped region and achieves satisfactory results. This paper has mainly completed the following two tasks:
First, improves the algorithm of identifying boundary convergent lines and extracts skeleton of region of boundary convergent lines. This paper studies the principle of the algorithm including "detection window" and deepen "impression", summarizes problem identification methodology, based on large size of sample survey modifies related threshold value and parameters, and gets skeleton of boundary convergent lines through specification.
Second, applies sectional drawing theory to analyze and summarize water and steam distribution characteristics within and near region of boundary convergent lines; uses wind field speed on both sides of skeleton of boundary convergent lines to extract information, analyze characteristics of boundary convergent lines convergence and movements as well as the relationship between these characteristics and potential stormy weather and provide related conclusions.
In sum, it has developed a new method for boundary convergent lines identification and storm prediction, realized related algorithms and its coding, and achieved strong robustness during sample tests and other satisfactory testing results.
引文
[1]俞小鼎、姚秀萍、熊廷南等,多普勒天气雷达原理与业务应用,北京:气象出版社,2006,90-95
[2]陶诗言等,暴雨和强对流天气研究,大气科学,1979,3(3):227-238
[3] Belkasim S O,Shridhar M,Ahmadi M,Pattern Recognition with Moment Invariant :A Comparative Study and New Results,Pattern Recognition,1991,24 :1172-1381
[4]黄勇,王崇骏,王亮,杭燕等,基于形状不变矩的图像检索算法的研究,计算机应用研究,2004,(7):256-260
[5] Orlanski,Isidoro,A rational subdivision of scales for atmospheric processes,Bulletin of the American Meteorological Society,1975,56(5),527-530
[6] Rinehart R E,Garvey E T,Three- dimensional storm motion detection by conventional weather radar,Nature,1978, 273: 287- 289
[7] Michael Dixon,Gerry wiener,Thunder storm identification,tracking,analysis and nowcasting-A radar_base methodology,J AtmosOceanic Technic,1993,10:785-797
[8] Johnson J T,Pamela L,Mackeen,The Storm Cell Identification and Tracking Algorithm:An Enhanced WSR-88D Algorithm,Weather and Forecasting,1997,13:263-276
[9] Pierce E,Hardaker P J,Collier C G,GANDOLF: a system for generating automated nowcasts of convective precipitation,Meteorol. Appl,2000,7:341-360
[10] Muller C,Saxen T,Roberts R,et al,NCAR Auto-Nowcast System,Weather and Forecasting,2003,18:545-561
[11]张沛源,多普勒雷达资料在强天气短时预报中的应用,第十一届亚运会气象保障研究论文集,北京:气象出版社,1991: 68-73
[12]万玉发,张家国,杨洪平等,联合雷达网和卫星定量监测与预报长江流域大范围降水应用,气象学报,1998, 9(1): 94-103
[13]杜秉玉,姚祖庆,上海地区强对流天气短时预报系统,南京气象学院学报,2000,23(2):242-250
[14] Shi-Lin Wang, Wing-Hong Lau, Alan Wee-Chung Liew, Shu-Hung Leung, Robust lip region segmentation for lip images with complex background[J]: Pattern Recognition, 2007, 40(12): 3481-3491
[15] Kass M, Witkin A, Terzopoulos D, Snakes: Active Contour Models[J]: Internation Journal of Computer Vision. 1988: 321-331
[16] Lilian Ji, Hong Yan, Loop-free snakes for highly irregular object shapes[J]: Pattern Recognition Letters, 2002, 23(5): 579-591
[17] Zoller,T, Buhmann, J.M, Shape Constrained Image Segmentation by ParametricDistributional Clustering: Computer Vision and Pattern Recognition, 2004: 386-393
[18] Fang M,Doviak R J,Melnikov V,Spectrum Width Measured by WSR -88D:Error Sources and Statistics of Various Weather Phenomena,J.Atmos,Oceanic Technol,2004,21:888-904
[19]许录平,数字图像处理,北京:科学出版社,2007
[20] Scassellati,Alexopoulos S,Flickner M,Retrieving images by 2D shape:a comparison of computation methods with human perceptual judgments ,In:Proceedings of the SPIE:Storage and Retrieval for Image and Video DatabasesⅡ,1994,2185:2~14
[21]刘恒,强对流天气潜势信息提取及其演变预测,[硕士学位论文],天津大学,2007
[22]丁险峰,孔维新,杨青,卢汉清,马颂德基于许瓦兹表示的形状检索计算机工程与科学,1998,20(A1):121~123
[23] Kliot M , Rivlin E , Invariant - Based Shape Retrieval in Pictorial DatabasesComputer Vision and Image Understanding,1998,71(2):182~197
[24] Mokhtarian F,Abbasi S,Retrieval of similar shapes under affine transform,In:Lecture Notes in Computer Science 1614:566~574
[25] Shen D G,Wong W H,Horace H S,Affine-invariant image retrieval by correspondence matching of shapes,Image and Vision Computing,1999,17(7):489~499
[26] Persoon E,Fu K,Shape discrimination using Fourier descriptors,IEEE Transactions on Systems,Man,and Cybernetics,1977,7:170-179
[27] Hu M K,Visual Pattern Recognition by Moment Invariants,IRE Transactions on Information Theory,1962,IT-8 (2) :179-187
[28] Belkasim S O,Shridhar M,Ahmadi M,Pattern Recognition with Moment Invariant :A Comparative Study and New Results,Pattern Recognition,1991,24 :1172-1381
[29] Wilson,J.W,and W.E.Schreiler,Initiation of convective storms by radar-observed boundary layer convergent lines,Mon.Wea.Rev,1986,114,2516-2536
[30] Ogura Y,On the Formation of organized convective systems observed over the Atlantic,Mon.Wea.Rev,1979,107(4):411~426
[31]强兆庆,基于突变理论的冰雹云预测研究[硕士学位论文],天津大学,2009
[32]贾永红,计算机图像处理与分析,武汉:武汉大学出版社,2001, 116-120
[33]屈展,形成期风暴预测与潜势特征提取[硕士学位论文],天津大学,2009
[34]盛德君,细化处理和算法实现,云南师范大学学报,2005,20(6): 21-23
[35]张群,张维桓,姜勇强,边界层辐合线发展成飑线的数值试验,气象科学,2001,21 (3): 308-315
[36]丁青兰,刘武,朱晓虎,李靖,一次飑线天气过程多普勒雷达产品分析及临近预报,气象科技,2008,36(2): 160-164
[37]卢焕珍,赵玉洁,俞小鼎,冯金湖,雷达观测的渤海湾海陆风辐合线与自动站资料的对比分析,气象,2008,34(9): 57-64
[38]卢焕珍,赵玉洁,俞小鼎,冯金湖,雷达观测的渤海湾海陆风辐合线与自动站资料的对比分析,气象,2008,34(9): 57-64
[39]丁青兰,王令,卞素芬,北京局地降水中地形和边界层辐合线的作用,气象科技,2009,37(2): 152-155
[40]周治黔,罗文芳,一次锋面与地面辐合线相互作用的对流天气落区预报及分析,贵州气象,2006,30(3): 6-9
[2]陶诗言等,暴雨和强对流天气研究,大气科学,1979,3(3):227-238
[3] Belkasim S O,Shridhar M,Ahmadi M,Pattern Recognition with Moment Invariant :A Comparative Study and New Results,Pattern Recognition,1991,24 :1172-1381
[4]黄勇,王崇骏,王亮,杭燕等,基于形状不变矩的图像检索算法的研究,计算机应用研究,2004,(7):256-260
[5] Orlanski,Isidoro,A rational subdivision of scales for atmospheric processes,Bulletin of the American Meteorological Society,1975,56(5),527-530
[6] Rinehart R E,Garvey E T,Three- dimensional storm motion detection by conventional weather radar,Nature,1978, 273: 287- 289
[7] Michael Dixon,Gerry wiener,Thunder storm identification,tracking,analysis and nowcasting-A radar_base methodology,J AtmosOceanic Technic,1993,10:785-797
[8] Johnson J T,Pamela L,Mackeen,The Storm Cell Identification and Tracking Algorithm:An Enhanced WSR-88D Algorithm,Weather and Forecasting,1997,13:263-276
[9] Pierce E,Hardaker P J,Collier C G,GANDOLF: a system for generating automated nowcasts of convective precipitation,Meteorol. Appl,2000,7:341-360
[10] Muller C,Saxen T,Roberts R,et al,NCAR Auto-Nowcast System,Weather and Forecasting,2003,18:545-561
[11]张沛源,多普勒雷达资料在强天气短时预报中的应用,第十一届亚运会气象保障研究论文集,北京:气象出版社,1991: 68-73
[12]万玉发,张家国,杨洪平等,联合雷达网和卫星定量监测与预报长江流域大范围降水应用,气象学报,1998, 9(1): 94-103
[13]杜秉玉,姚祖庆,上海地区强对流天气短时预报系统,南京气象学院学报,2000,23(2):242-250
[14] Shi-Lin Wang, Wing-Hong Lau, Alan Wee-Chung Liew, Shu-Hung Leung, Robust lip region segmentation for lip images with complex background[J]: Pattern Recognition, 2007, 40(12): 3481-3491
[15] Kass M, Witkin A, Terzopoulos D, Snakes: Active Contour Models[J]: Internation Journal of Computer Vision. 1988: 321-331
[16] Lilian Ji, Hong Yan, Loop-free snakes for highly irregular object shapes[J]: Pattern Recognition Letters, 2002, 23(5): 579-591
[17] Zoller,T, Buhmann, J.M, Shape Constrained Image Segmentation by ParametricDistributional Clustering: Computer Vision and Pattern Recognition, 2004: 386-393
[18] Fang M,Doviak R J,Melnikov V,Spectrum Width Measured by WSR -88D:Error Sources and Statistics of Various Weather Phenomena,J.Atmos,Oceanic Technol,2004,21:888-904
[19]许录平,数字图像处理,北京:科学出版社,2007
[20] Scassellati,Alexopoulos S,Flickner M,Retrieving images by 2D shape:a comparison of computation methods with human perceptual judgments ,In:Proceedings of the SPIE:Storage and Retrieval for Image and Video DatabasesⅡ,1994,2185:2~14
[21]刘恒,强对流天气潜势信息提取及其演变预测,[硕士学位论文],天津大学,2007
[22]丁险峰,孔维新,杨青,卢汉清,马颂德基于许瓦兹表示的形状检索计算机工程与科学,1998,20(A1):121~123
[23] Kliot M , Rivlin E , Invariant - Based Shape Retrieval in Pictorial DatabasesComputer Vision and Image Understanding,1998,71(2):182~197
[24] Mokhtarian F,Abbasi S,Retrieval of similar shapes under affine transform,In:Lecture Notes in Computer Science 1614:566~574
[25] Shen D G,Wong W H,Horace H S,Affine-invariant image retrieval by correspondence matching of shapes,Image and Vision Computing,1999,17(7):489~499
[26] Persoon E,Fu K,Shape discrimination using Fourier descriptors,IEEE Transactions on Systems,Man,and Cybernetics,1977,7:170-179
[27] Hu M K,Visual Pattern Recognition by Moment Invariants,IRE Transactions on Information Theory,1962,IT-8 (2) :179-187
[28] Belkasim S O,Shridhar M,Ahmadi M,Pattern Recognition with Moment Invariant :A Comparative Study and New Results,Pattern Recognition,1991,24 :1172-1381
[29] Wilson,J.W,and W.E.Schreiler,Initiation of convective storms by radar-observed boundary layer convergent lines,Mon.Wea.Rev,1986,114,2516-2536
[30] Ogura Y,On the Formation of organized convective systems observed over the Atlantic,Mon.Wea.Rev,1979,107(4):411~426
[31]强兆庆,基于突变理论的冰雹云预测研究[硕士学位论文],天津大学,2009
[32]贾永红,计算机图像处理与分析,武汉:武汉大学出版社,2001, 116-120
[33]屈展,形成期风暴预测与潜势特征提取[硕士学位论文],天津大学,2009
[34]盛德君,细化处理和算法实现,云南师范大学学报,2005,20(6): 21-23
[35]张群,张维桓,姜勇强,边界层辐合线发展成飑线的数值试验,气象科学,2001,21 (3): 308-315
[36]丁青兰,刘武,朱晓虎,李靖,一次飑线天气过程多普勒雷达产品分析及临近预报,气象科技,2008,36(2): 160-164
[37]卢焕珍,赵玉洁,俞小鼎,冯金湖,雷达观测的渤海湾海陆风辐合线与自动站资料的对比分析,气象,2008,34(9): 57-64
[38]卢焕珍,赵玉洁,俞小鼎,冯金湖,雷达观测的渤海湾海陆风辐合线与自动站资料的对比分析,气象,2008,34(9): 57-64
[39]丁青兰,王令,卞素芬,北京局地降水中地形和边界层辐合线的作用,气象科技,2009,37(2): 152-155
[40]周治黔,罗文芳,一次锋面与地面辐合线相互作用的对流天气落区预报及分析,贵州气象,2006,30(3): 6-9