MTSAT卫星云图中对流初生的自动预报算法研究
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摘要
目前对降雨事件的短时预测,获得了广泛关注,特别是对中尺度系统,当然也包括了雷暴情况。因为雷暴天气通常会伴随着天气在空间和时间范围内的迅速改变,并且会带来天气灾害,其影响包括从农民到飞行员等各种职业。所以对雷暴的发展、演变和运动情况的精确预报是至关重要的。
本文在小波融合理论的基础上,首次在小波融合算法中考虑图像数据的物理意义,将可见光图像高的空间分辨率和丰富的纹理细节信息融合到红外图像中,提高了红外图像的空间分辨率,增加了红外图像数据的物理信息量。本文所提出的方法,充分考虑了红外和可见光图像本身数据的物理意义,用小波变换得到待融合数据的多分辨结构,在数据多分辨结构相应各级上采取不同的融合规则,得到融合数据的多分辨结构,利用小波逆变换重构融合数据。此方法得到的高分辨率红外图像不仅在视觉上得到了改善,而且丰富了红外通道数据的物理信息,取得了非常好的效果。结果表明：该融合方法简便易行,精度较高,为快速获取高分辨率红外图像提供了一条新途径。
再对高分辨率的红外数据进行分析处理,预报出潜在对流初生(Convective initiation, CI)区域,使CI的预报时间更加提前。通过对我国京津地区一些时段的MTSAT卫星云图资料进行实验分析,预报CI。同时使用相同区域、同一时间段的雷达回波数据作为降水资料,对CI的预报结果进行检验,并根据检验结果对八分法系统参数进行调整,开发出一套适合中国地域的CI预报方法,最后取得了比较好的预报结果。
One aspect that has received widespread attention is the short-term prediction of rainfall events, especially those that evolve on meso-time scales, which certainly include thunderstorm convection. Because thunderstorms are often accompanied by rapidly changing weather in spatial and temporal scales, and thunderstorms will bring weather hazards and phenomena that often adversely impact on professionals ranging from farmers to pilots. So there is a critical need to accurately predict their develop-ment, evolution, and movement.
Based on the theory of wavelet fusion, this paper consideres the physical meaning of image data in wavelet fusion algorithm for the first time. This algorithm fuses the visible light images with high spatial resolution and rich texture detail to the infrared image, which can improve the saptial resolution of the infrared images, and increase the physical information. The method presented in this paper consider the physical meaning of the infrared and visible images. This paper uses multiwavelet to get the multi-resolution structure of the original data, and uses different fusion rules at every data multi-resolution structure level to get the multi-resolution stucture of the fusion data, which can be rebuild. This method not only get high-resolution infrared images, but also make the infrared channel data rich in physical information. The results show that:the fusion method is simple and has high precision, which is a new way of getting high-resolution infrared images.
Then high-resolution infrared data were processed and analysed for the purpose of forecasting the potential CI region and a more earlier forecasting time. After fore-casting CI through the analysis of MTSAT image data of Beijing-Tianjin region, using radar data of the same time and the same area to test the CI forecasting result and adjusting the system parameters, a CI forecasting method was developed, which is suitable for China's geographical and obtained good prediction results.
本文在小波融合理论的基础上,首次在小波融合算法中考虑图像数据的物理意义,将可见光图像高的空间分辨率和丰富的纹理细节信息融合到红外图像中,提高了红外图像的空间分辨率,增加了红外图像数据的物理信息量。本文所提出的方法,充分考虑了红外和可见光图像本身数据的物理意义,用小波变换得到待融合数据的多分辨结构,在数据多分辨结构相应各级上采取不同的融合规则,得到融合数据的多分辨结构,利用小波逆变换重构融合数据。此方法得到的高分辨率红外图像不仅在视觉上得到了改善,而且丰富了红外通道数据的物理信息,取得了非常好的效果。结果表明：该融合方法简便易行,精度较高,为快速获取高分辨率红外图像提供了一条新途径。
再对高分辨率的红外数据进行分析处理,预报出潜在对流初生(Convective initiation, CI)区域,使CI的预报时间更加提前。通过对我国京津地区一些时段的MTSAT卫星云图资料进行实验分析,预报CI。同时使用相同区域、同一时间段的雷达回波数据作为降水资料,对CI的预报结果进行检验,并根据检验结果对八分法系统参数进行调整,开发出一套适合中国地域的CI预报方法,最后取得了比较好的预报结果。
One aspect that has received widespread attention is the short-term prediction of rainfall events, especially those that evolve on meso-time scales, which certainly include thunderstorm convection. Because thunderstorms are often accompanied by rapidly changing weather in spatial and temporal scales, and thunderstorms will bring weather hazards and phenomena that often adversely impact on professionals ranging from farmers to pilots. So there is a critical need to accurately predict their develop-ment, evolution, and movement.
Based on the theory of wavelet fusion, this paper consideres the physical meaning of image data in wavelet fusion algorithm for the first time. This algorithm fuses the visible light images with high spatial resolution and rich texture detail to the infrared image, which can improve the saptial resolution of the infrared images, and increase the physical information. The method presented in this paper consider the physical meaning of the infrared and visible images. This paper uses multiwavelet to get the multi-resolution structure of the original data, and uses different fusion rules at every data multi-resolution structure level to get the multi-resolution stucture of the fusion data, which can be rebuild. This method not only get high-resolution infrared images, but also make the infrared channel data rich in physical information. The results show that:the fusion method is simple and has high precision, which is a new way of getting high-resolution infrared images.
Then high-resolution infrared data were processed and analysed for the purpose of forecasting the potential CI region and a more earlier forecasting time. After fore-casting CI through the analysis of MTSAT image data of Beijing-Tianjin region, using radar data of the same time and the same area to test the CI forecasting result and adjusting the system parameters, a CI forecasting method was developed, which is suitable for China's geographical and obtained good prediction results.
引文
[1]王丕诰,刘宗义,张开斗.应用卫星气象学.青岛：中国海洋大学出版社,2004
[2]余远东.气象卫星遥感云图和水汽图的图像处理及强云团识别：[博士学位论文]。武汉：武汉理工大学,2007
[3]陆汉城等.中尺度天气原理和预报.北京：气象出版社,2004
[4]Bedka, J. R. Mecikalski, et al.2007:Statistical comparisons between satellite-derived atmospheric motion vectors,rawinsondes, and NOAA Wind Profiler observations. Accepted. J. Appl. Meteor
[5]Mecikalski, J. R., K. M. Bedka, S. J. Paech, and L. A. Litten,2008:A statistical evaluation of GOES cloud-top properties for nowcasting convective initiation. Mon.Wea. Rev., Accepted
[6]Roberts, R. D., and S. Rutledge,2003:Nowcasting storm Initiation and growth using GOES-8 and WSR-88D data. Wea. Forecasting,18,562-584
[7]王改利,刘黎平,阮征.多普勒雷达资料在暴雨临近预报中的应用.应用气象学报,2007,18(3)：388～395
[8]倪允琪,周秀骥.“我国贡大天气灾害形成机理与预测理沦研究”取得的土要研究成果.地球科学进展,2006,9：881～894
[9]帅春香,谢正辉.基于静止气象卫星观测的降水时间降尺度研究.地理科学进展,2008,4：15～22
[10]魏建苏,严明良,樊永富,尹东平,沈树勤.卫星云图和数值产品结合的汛期强降水预警系统.气象科学,2001,9：355～362
[11]Mecikalski, J. R., and K. M. Bedka,2006:Forecasting convective initiation by monitoring the evolution of moving convection in daytime GOES imagery. Mon. Wea. Rev.,134, 49-78.
[12]Bedka, K. M., and J. R. Mecikalski,2005:Application of satellitederived atmospheric vectors for estimating mesoscale flows. J. Appl. Meteor.,44,1761～1772.
[13]孟执中,李卿.气象卫星的发展.上海航天,2003,2：1-6.
[14]张鹏锐,王荣华.日本新一代多功能卫星MTSAT中国航天,2005,4：10～11.
[15]黄建明,李金宗,李冬冬.利用二位插值核的高分辨力图像重构.光电工程,2005,5：80～84
[16]陈宝平,赵俊岚,尹志凌.双线性插值算法的一种快速实现方式.北京电子科技学院学报.2004,12(4)：21～23
[17]段汕,秦前清.基于形态插值的图像重建方法.计算机工程及应用,2004,18：26～28
[18]杨云峰,苏志勋,胡金燕.一种保持边缘特征的图像插值方法.中国图像图形学报,2005,10：1249～1251
[19]韩崇昭,朱洪艳,段战胜.多源信息融合[M].北京：清华大学出版社,2006.
[20]洪日昌.多源图像融合算法及应用研究,中国科学技术大学博士论文,2007.
[21]Hand, W. H.,1996:An object-oriented technique for nowcasting heavy showers and thunderstorms. Meteor. Appl.,3,31～41
[22]Ranehin.T,Wald.L.The Wavelet Transform for the Analysis of Remotely Sensed Images. Int. J. Remote Sensing.1993.14(3):615～620
[23]Li.H, Manjunath. B. S, Mitra.S.K. Multisensor Image Fusion Using the Wavelet Transform. Graphical models and Image Proeessing.1995.57:235～245
[24]Xu. Y. S. et al. Wavelet Transform Domain Filters:a Spatially Selective Noise Filtration Technique. IEEE Trans. On Image Proeessing.1994.3(6):747～758
[25]Nikolov. S. G. et al.2-D Image Fusion by Multiseale Edge Graph Combination. Proceedings of the 3rd International Conference on Information Fusion(Fusion 2000). Paris. Franee.2000.7:10～13
[26]Nikolov. S. G.. et al. Fusion of 2-D Images Using Their Multiscale Edges. IEEE International Conference on Pattern Recognition(ICPR). Barcelona. Spain.2000.3:41～44.
[27]Seheunders. P. Multiscale Edge Representation Applied to Image Fusion. Proc. Wavelet Applications in Signal and Image Proeessing VIII, SPIE's Annual Meeting. San Diego. USA. July 30～August 4.2000. 1:MoD3-16～22
[28]Qu. G..H, Zhang. D. L, Yan. P. F. Medical Image Fusion by Wavelet Transform Modulus Maxima. Optics Express.2001.9(4):184～190
[29]Koren. I, Laine. A. A Discrete Dyadic Wavelet Transform for Multidimensional Feature. M. Akay(Editor), Time-Frequency and Wavelets in Biomedical Signal Engineering. New York. NY:IEEE Press.1998.425～449
[30]Mallat. S. A Theory for Multiresolution Signal Decomposition:the Wavelet Representation. IEEE Trans. On Pattern Anal. MachineIntell.1989.11(7):674～692.
[31]Weckwerth, T. M., and D. B. Parsons,2006:A review of convective initiation and motivation for IHOP_2002. Mon. Wea. Rev.,134,5-22
[32]Setvak, M., and C. A. Doswell Ⅲ,1991:The AVHRR channel 3 cloud top reflectivity of convective storms. Mon. Wea. Rev.,119,841～847
[33]Strabala, K. I., S. A. Ackerman, and W. P. Menzel,1994:Cloud properties inferred from 8-12_m data. J. Appl. Meteor.,33,212～229
[34]Schmetz, J., S. A. Tjemkes, M. Gube, and L. van de Berg,1997:Monitoring deep convection and convective overshooting with METEOSAT. Adv. Space Res.,19,433-441.
[35]Hand, W. H.,1996:An object-oriented technique for nowcasting heavy showers and thunderstorms. Meteor. Appl,3,31～41
[36]Menzel, W. P., and J. F. W. Purdom,1994:Introducing GOES-Ⅰ:The first of a new generation of geostationary operational environmental satellites. Bull. Amer. Meteor. Soc., 75,757～781
[37]Beckman, S. K.,1986:Relationship between cloud bands in satellite imagery and severe weather. Satellite Imagery Interpretation for Forecasters, Vol.2, Precipitation Convection, P. S. Parke, Ed., National Weather Association. [Available from the NWA,4400 Stamp Road, No.404, Temple Hills, MD 20748.] Bedka, K. M
[38]章毓晋.图像理解与计算机视觉.北京：清华大学出版社,2000
[39]Lovejoy, S., and G. L. Austin. The delineation of rain areas from visible and IR satellite data for GATE and mid-latitudes. Atmos.-Ocean,1979,17:77～92
[40]兰红平,张儒林,江崟.用红外云图估测小区域雨强及其在短时预报中的应用.热带气象学报,2000,11：366～373
[41]黄战,姜宇鹰,张镭.基于表格查询学习算法的自适应模糊分类器.计算机应用,2005,4：750～753
[42]Kuo, K. S., R. M. Welch, and R. C. Weger,1993:The threedimensional structure of cumulus clouds over the ocean.1. Structural analysis. J. Geophys. Res.,98,20685～20711
[43]Markowski, P., C. Hannon, and E. Rasmussen,2006:Observations of convection initiation "failure" from the 12 June 2002 IHOP deployment. Mon. Wea. Rev.,134,375～405
[44]李智勇,沈振康等.动态图像分析.北京：国防工业出版社,1999
[2]余远东.气象卫星遥感云图和水汽图的图像处理及强云团识别：[博士学位论文]。武汉：武汉理工大学,2007
[3]陆汉城等.中尺度天气原理和预报.北京：气象出版社,2004
[4]Bedka, J. R. Mecikalski, et al.2007:Statistical comparisons between satellite-derived atmospheric motion vectors,rawinsondes, and NOAA Wind Profiler observations. Accepted. J. Appl. Meteor
[5]Mecikalski, J. R., K. M. Bedka, S. J. Paech, and L. A. Litten,2008:A statistical evaluation of GOES cloud-top properties for nowcasting convective initiation. Mon.Wea. Rev., Accepted
[6]Roberts, R. D., and S. Rutledge,2003:Nowcasting storm Initiation and growth using GOES-8 and WSR-88D data. Wea. Forecasting,18,562-584
[7]王改利,刘黎平,阮征.多普勒雷达资料在暴雨临近预报中的应用.应用气象学报,2007,18(3)：388～395
[8]倪允琪,周秀骥.“我国贡大天气灾害形成机理与预测理沦研究”取得的土要研究成果.地球科学进展,2006,9：881～894
[9]帅春香,谢正辉.基于静止气象卫星观测的降水时间降尺度研究.地理科学进展,2008,4：15～22
[10]魏建苏,严明良,樊永富,尹东平,沈树勤.卫星云图和数值产品结合的汛期强降水预警系统.气象科学,2001,9：355～362
[11]Mecikalski, J. R., and K. M. Bedka,2006:Forecasting convective initiation by monitoring the evolution of moving convection in daytime GOES imagery. Mon. Wea. Rev.,134, 49-78.
[12]Bedka, K. M., and J. R. Mecikalski,2005:Application of satellitederived atmospheric vectors for estimating mesoscale flows. J. Appl. Meteor.,44,1761～1772.
[13]孟执中,李卿.气象卫星的发展.上海航天,2003,2：1-6.
[14]张鹏锐,王荣华.日本新一代多功能卫星MTSAT中国航天,2005,4：10～11.
[15]黄建明,李金宗,李冬冬.利用二位插值核的高分辨力图像重构.光电工程,2005,5：80～84
[16]陈宝平,赵俊岚,尹志凌.双线性插值算法的一种快速实现方式.北京电子科技学院学报.2004,12(4)：21～23
[17]段汕,秦前清.基于形态插值的图像重建方法.计算机工程及应用,2004,18：26～28
[18]杨云峰,苏志勋,胡金燕.一种保持边缘特征的图像插值方法.中国图像图形学报,2005,10：1249～1251
[19]韩崇昭,朱洪艳,段战胜.多源信息融合[M].北京：清华大学出版社,2006.
[20]洪日昌.多源图像融合算法及应用研究,中国科学技术大学博士论文,2007.
[21]Hand, W. H.,1996:An object-oriented technique for nowcasting heavy showers and thunderstorms. Meteor. Appl.,3,31～41
[22]Ranehin.T,Wald.L.The Wavelet Transform for the Analysis of Remotely Sensed Images. Int. J. Remote Sensing.1993.14(3):615～620
[23]Li.H, Manjunath. B. S, Mitra.S.K. Multisensor Image Fusion Using the Wavelet Transform. Graphical models and Image Proeessing.1995.57:235～245
[24]Xu. Y. S. et al. Wavelet Transform Domain Filters:a Spatially Selective Noise Filtration Technique. IEEE Trans. On Image Proeessing.1994.3(6):747～758
[25]Nikolov. S. G. et al.2-D Image Fusion by Multiseale Edge Graph Combination. Proceedings of the 3rd International Conference on Information Fusion(Fusion 2000). Paris. Franee.2000.7:10～13
[26]Nikolov. S. G.. et al. Fusion of 2-D Images Using Their Multiscale Edges. IEEE International Conference on Pattern Recognition(ICPR). Barcelona. Spain.2000.3:41～44.
[27]Seheunders. P. Multiscale Edge Representation Applied to Image Fusion. Proc. Wavelet Applications in Signal and Image Proeessing VIII, SPIE's Annual Meeting. San Diego. USA. July 30～August 4.2000. 1:MoD3-16～22
[28]Qu. G..H, Zhang. D. L, Yan. P. F. Medical Image Fusion by Wavelet Transform Modulus Maxima. Optics Express.2001.9(4):184～190
[29]Koren. I, Laine. A. A Discrete Dyadic Wavelet Transform for Multidimensional Feature. M. Akay(Editor), Time-Frequency and Wavelets in Biomedical Signal Engineering. New York. NY:IEEE Press.1998.425～449
[30]Mallat. S. A Theory for Multiresolution Signal Decomposition:the Wavelet Representation. IEEE Trans. On Pattern Anal. MachineIntell.1989.11(7):674～692.
[31]Weckwerth, T. M., and D. B. Parsons,2006:A review of convective initiation and motivation for IHOP_2002. Mon. Wea. Rev.,134,5-22
[32]Setvak, M., and C. A. Doswell Ⅲ,1991:The AVHRR channel 3 cloud top reflectivity of convective storms. Mon. Wea. Rev.,119,841～847
[33]Strabala, K. I., S. A. Ackerman, and W. P. Menzel,1994:Cloud properties inferred from 8-12_m data. J. Appl. Meteor.,33,212～229
[34]Schmetz, J., S. A. Tjemkes, M. Gube, and L. van de Berg,1997:Monitoring deep convection and convective overshooting with METEOSAT. Adv. Space Res.,19,433-441.
[35]Hand, W. H.,1996:An object-oriented technique for nowcasting heavy showers and thunderstorms. Meteor. Appl,3,31～41
[36]Menzel, W. P., and J. F. W. Purdom,1994:Introducing GOES-Ⅰ:The first of a new generation of geostationary operational environmental satellites. Bull. Amer. Meteor. Soc., 75,757～781
[37]Beckman, S. K.,1986:Relationship between cloud bands in satellite imagery and severe weather. Satellite Imagery Interpretation for Forecasters, Vol.2, Precipitation Convection, P. S. Parke, Ed., National Weather Association. [Available from the NWA,4400 Stamp Road, No.404, Temple Hills, MD 20748.] Bedka, K. M
[38]章毓晋.图像理解与计算机视觉.北京：清华大学出版社,2000
[39]Lovejoy, S., and G. L. Austin. The delineation of rain areas from visible and IR satellite data for GATE and mid-latitudes. Atmos.-Ocean,1979,17:77～92
[40]兰红平,张儒林,江崟.用红外云图估测小区域雨强及其在短时预报中的应用.热带气象学报,2000,11：366～373
[41]黄战,姜宇鹰,张镭.基于表格查询学习算法的自适应模糊分类器.计算机应用,2005,4：750～753
[42]Kuo, K. S., R. M. Welch, and R. C. Weger,1993:The threedimensional structure of cumulus clouds over the ocean.1. Structural analysis. J. Geophys. Res.,98,20685～20711
[43]Markowski, P., C. Hannon, and E. Rasmussen,2006:Observations of convection initiation "failure" from the 12 June 2002 IHOP deployment. Mon. Wea. Rev.,134,375～405
[44]李智勇,沈振康等.动态图像分析.北京：国防工业出版社,1999