多普勒雷达基数据质量控制方法研究
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摘要
随着电子计算机技术的快速发展,对计算能力要求较高的数值天气预报模式也得到了较大的进步,目前已经可以将具有高分辨率的雷达资料应用到数值预报模式,用以改善数值天气预报的质量。不过,多普勒天气雷达的基数据常常是不准确的,从而影响雷达资料在实际气象业务中的应用。因此,雷达基数据的质量控制就具有了重要意义。目前,多普勒雷达基数据主要存在三个问题：(1)速度模糊；(2)地物杂波；(3)距离折叠。本文主要是进行速度退模糊和去除地物杂波这两方面的工作。
多普勒雷达径向速度退模糊方法的基本思路都是首先确定可靠观测,然后在可靠观测的基础上进行速度扩展。确定可靠观测的基本方式有两种：一种是借助其它气象观测数据或非观测气象数据；另一种是通过雷达径向风资料自身的特点来发掘可靠观测。通过雷达径向风资料自身的特点发掘可靠观测又可以通过两种方式：径向和切向。本文使用fortran语言实现了一种基于切向获取参考场的退模糊方案和一种基于径向获取参考场的退模糊方案；并且设计制作了多种模拟的雷达径向风资料；利用模拟资料对这两种方案进行了对比。对比结果表明,这两种方案对风场的特性都较为敏感,基于切向获取参考场的退模糊方案在实际风场的非线性较强时表现较差；而基于径向获取参考场的退模糊方案在雷达径向风场的零风速线不与雷达观测场的径向匹配时表现也较差。然后针对其中的通过径向方式获取参考场的退模糊方案做出改进。模拟资料测试结果和实际资料的测试结果表明,该方案更加有效。
目前去除地物杂波的重点是去除超折射回波(AP回波)。本文对Kessinger的回波分类技术使用实际资料进行了测试。测试结果表明,仅仅使用原方案,即只通过APDA算法的判断进行去除超折射回波的工作存在两个问题,一个是会将部分气象回波当作地物去除掉,另一个是在缺少多普勒信息的观测点很难识别出地物回波。这对这些不足,本文有效结合两种回波分类算法(APDA、PDA),这可以在很大程度上保证气象回波不会被误认为地物被去除；同时引入了经验型方案作为补充,在缺少多普勒场的情况下,依然能够表现良好。
With the development of computer technology and the advances in numerical weather forecast model, it is possible to have high resolution data of radar applied to numerical forecast model to improve the numerical forecast. But the base data of the Doppler radar is not always correct, affecting the application of radar data in business. Therefore, the quality control of radar base data would have great significance. Nowadays, the radar base data is influenced by three problems:(1)distance folding;(2)velocity aliasing;(3)clutter. Dealiasing and removing clutter is the main work in this paper.
The basic idea of the dealiasing algorithm for the Doppler radar radial velocity can be divided into two steps:the first step is to determine the reliable observations; the second step is the continuity check based on the reliable observations. Generally, we have two methods to determine the reliable observations, one is to contrast radar radial velocity with another observational or non observational meteorological data; the other is obtain them from the radar radial velocity observations themselves. We can obtain reliable observations from the radar data by means of tangential method and radial method. I fulfilled two dealiasing algorithms with fortran computer language, one obtains reliable observations by means of tangential method and the other is by means of radial method. Additionally, this paper designs and made makes simulated Doppler radar radial velocity data, which is used to test two typical automated dealiasing method. According to the result, the two methods are both very sensitive to the characters of the wind. The dealiasing algorithm which obtains reliable observations based on tangential method performances very bad when nonlinearity of the wind is strong. The other dealiasing algorithm do not performance well when the isanemone of the radial velocity data is not match to radar radial line. Then, a new dealiasing method obtains reliable observations based on radial method has being designed based on the two methods. The new method is more robust according to the testing result.
The other main work of this paper is to remove AP clutter. This paper tested the method offered by Kessinger with real Doppler radar observations. According to the result, there are two defects in the original method which just uses the result from APDA to remove AP clutter. One is that it would remove meteorology echo falsely and the other is that it almost do anything when there are no Doppler information. So, this paper combines two echo identification algorithms (APDA, PDA) based on the method offered by Kessinger, which would ensure that the meteorology echo would not be removed falsely; and a kind of experienced method to be supplemented when there is no Doppler information.
多普勒雷达径向速度退模糊方法的基本思路都是首先确定可靠观测,然后在可靠观测的基础上进行速度扩展。确定可靠观测的基本方式有两种：一种是借助其它气象观测数据或非观测气象数据；另一种是通过雷达径向风资料自身的特点来发掘可靠观测。通过雷达径向风资料自身的特点发掘可靠观测又可以通过两种方式：径向和切向。本文使用fortran语言实现了一种基于切向获取参考场的退模糊方案和一种基于径向获取参考场的退模糊方案；并且设计制作了多种模拟的雷达径向风资料；利用模拟资料对这两种方案进行了对比。对比结果表明,这两种方案对风场的特性都较为敏感,基于切向获取参考场的退模糊方案在实际风场的非线性较强时表现较差；而基于径向获取参考场的退模糊方案在雷达径向风场的零风速线不与雷达观测场的径向匹配时表现也较差。然后针对其中的通过径向方式获取参考场的退模糊方案做出改进。模拟资料测试结果和实际资料的测试结果表明,该方案更加有效。
目前去除地物杂波的重点是去除超折射回波(AP回波)。本文对Kessinger的回波分类技术使用实际资料进行了测试。测试结果表明,仅仅使用原方案,即只通过APDA算法的判断进行去除超折射回波的工作存在两个问题,一个是会将部分气象回波当作地物去除掉,另一个是在缺少多普勒信息的观测点很难识别出地物回波。这对这些不足,本文有效结合两种回波分类算法(APDA、PDA),这可以在很大程度上保证气象回波不会被误认为地物被去除；同时引入了经验型方案作为补充,在缺少多普勒场的情况下,依然能够表现良好。
With the development of computer technology and the advances in numerical weather forecast model, it is possible to have high resolution data of radar applied to numerical forecast model to improve the numerical forecast. But the base data of the Doppler radar is not always correct, affecting the application of radar data in business. Therefore, the quality control of radar base data would have great significance. Nowadays, the radar base data is influenced by three problems:(1)distance folding;(2)velocity aliasing;(3)clutter. Dealiasing and removing clutter is the main work in this paper.
The basic idea of the dealiasing algorithm for the Doppler radar radial velocity can be divided into two steps:the first step is to determine the reliable observations; the second step is the continuity check based on the reliable observations. Generally, we have two methods to determine the reliable observations, one is to contrast radar radial velocity with another observational or non observational meteorological data; the other is obtain them from the radar radial velocity observations themselves. We can obtain reliable observations from the radar data by means of tangential method and radial method. I fulfilled two dealiasing algorithms with fortran computer language, one obtains reliable observations by means of tangential method and the other is by means of radial method. Additionally, this paper designs and made makes simulated Doppler radar radial velocity data, which is used to test two typical automated dealiasing method. According to the result, the two methods are both very sensitive to the characters of the wind. The dealiasing algorithm which obtains reliable observations based on tangential method performances very bad when nonlinearity of the wind is strong. The other dealiasing algorithm do not performance well when the isanemone of the radial velocity data is not match to radar radial line. Then, a new dealiasing method obtains reliable observations based on radial method has being designed based on the two methods. The new method is more robust according to the testing result.
The other main work of this paper is to remove AP clutter. This paper tested the method offered by Kessinger with real Doppler radar observations. According to the result, there are two defects in the original method which just uses the result from APDA to remove AP clutter. One is that it would remove meteorology echo falsely and the other is that it almost do anything when there are no Doppler information. So, this paper combines two echo identification algorithms (APDA, PDA) based on the method offered by Kessinger, which would ensure that the meteorology echo would not be removed falsely; and a kind of experienced method to be supplemented when there is no Doppler information.
引文
[1]高丽杰,张军英.新一代天气雷达数据分析中基本产品的研究和开发[D].2008.
[2]中国气象局网站：http://english.cma.gov.cn/qxxdh/leida/index.php
[3]张培昌,杜秉玉.戴铁丕.雷达气象学[M].北京：气象出版社,2001.
[4]Alberoni, P. P., Andersson, T., Mezzasalma, P., Michelson, D. B., and Nanni, S., 2001. Use of the vertical reflectivity profile for identification of anomalous propagation. Meteorol. Appl.8(3),257-266.
[5]赵恒轩.90年代天气雷达监测网建设与发展[J].成都气象学院学报.1999(3)：252-260.
[6]许柏魁,朱晓华.脉冲多普勒气象雷达信号处理系统研究[D].2002.
[6]张华,朱晓华.脉冲多普勒气象雷达信号处理系统研究[D].2003.
[7]肖艳娇,刘黎平.新一代天气雷达三维组网技术及其应用研究[D].2007.
[8]R.L.Alborty and T.D.Crum. NEXRAD and the operational Doppler weather radar for the 1990s and beyond, International Simposium on Geoscience and Remote Sensing. Vol-1, Jan.1990:725-728.
[9]P. Hildebrand, C. A. Walther, C. Frush, J. Testud, F. Baudin. "The ELDORA/ ASTRAIA airborne Doppler weather radar:goals, design and first field tests". Preceeding of the IEEE. Vol-82,NO.12, Dec.1994:1873-1890.
[10]杨尚军,邹逢兴.雷达模拟器气象杂波的建模与仿真[D].2006.
[1]Ray P, C Ziegler. De-aliasing first-moment Doppler estimates[J]. J. Appl. Meteor., 1977,16(5):563-564.
[2]Bargen D W, R. C Brown. Interactive radar velocity unfolding[C]. Preprints, Conf. On Radar Meteorology, Miami, FL, Amer. Meteor. Soc.,1980:278-283.
[3]Hennington L, Reducing the effects of Doppler radar ambiguities [J]. J. Appl. Meteor.,1981,20(12):1543-1546.
[4]Eilts M D, S D Smith. Efficient dealiasing of Doppler velocities using local environment constraints [J]. J. Atmos. Oceanic Technol.,1990,7(1):118-128.
[5]Merritt M W. Automatic velocity dealiasing for real-time applications[C]. Proc. 22nd Conf. on Radar Meteorology. Zurich, Amer. Meteor. Soc.,1984:528-533.
[6]Bergen W R, S C Albers. Two and three-dimensional dealiasing of Doppler radar velocities[J]. J. Atmos. Oceanic Technol.,1988,5(2):305-319.
[7]Gong J, L Wang, Xu Q.. A three-step dealiasing method for Doppler velocity data quality control[J]. J. Atmos. Oceanic Technol.,2003,20(12):1738-1748.
[8]Tabary P, G Scialom, U Germann. Real-time retrieval of the wind from aliased velocities measured by Doppler radars[J]. J. Atmos. Oceanic Technol..2001,18(6): 875-882.
[9]Xu Q., K. Nai, and L. Wei,2010:Fitting VAD wind to aliased radial-velocity observations-A minimization problem with multiple minima. Quart. J. Roy. Meteor. Soc.,136,451-461.
[10]Xu Q., K. Nai, and L. Wei, et al. A VAD-Based Dealiasing Method for Radar Velocity Data Quality Control. J. Atmos. Oceanic Technol,2010,28,50-62.
[11]James C. N., R. A. Houze. A real-time four dimensional Doppler dealiasing scheme[J]. J. Atmos. Oceanic Technol.,2001,18(10):1674-1683.
[12]Zhang J, S Wang. An automated 2-D multi-pass velocity dealiasing scheme[C]. Preprints,11th Conf. on Aviation, Range, and Aerospace, Hyannis, MA, Amer. Meteor. Soc.,2004, paper 5.5.
[13]蔡亲波,颜琼丹.二维多路多普勒雷达风场自动退模糊算法应用研究[J].气象科学,2000,29(5)：625-632.
[14]Lim E, J Sun. A Velocity Dealiasing Technique Using Rapidly Updated Analysis from a Four-dimensional Variational Doppler Radar Data Assimilation System[J]. J. Atmos. Oceanic Technol.,2010,27(7):1140-1152.
[15]雷小途,陈联寿.热带气旋风场模型构造及特征参数估算[J].地球物理学报,2005,48(1)：25～31.
[1]Zhang J, S Wang. An automated 2-D multi-pass velocity dealiasing scheme[C]. Preprints,11th Conf. on Aviation, Range, and Aerospace, Hyannis, MA, Amer. Meteor. Soc.,2004, paper 5.5.
[2]Eilts M D, S D Smith. Efficient dealiasing of Doppler velocities using local environment constraints [J]. J. Atmos. Oceanic Technol.,1990,7(1):118-128.
[1]Steiner, M., and J. A. Smith,2002 Use of three-dimensional reflectivity structure for automated detection and removal of nonprecipitating echoes in radar data. J. Atmos. Oceanic Technol.,19,673-686.
[2]Kessinger, C., S. Ellis, and J. vanAndel,1999:A fuzzy logic, radar echo classification scheme for the WSR-88D. Preprints,29th Int. Conf. on Radar Meteorology, Montreal, QC, Canada, Amer. Meteor. Soc.,576-579.
[3]Zhang J, Wang S, Clarke B. Wsr-88d reflectivity quality control using horizontal and vertical reflectivity structure[C].11th Conference on aviation, range and aerospace meteorology. Hyannis,2004:54.
[4]Lakshmanan, V, A. Fritz, T. Smith, K. Hondl, and G. Stumpf,2007:An automated technique to quality control radar reflectivity data. J. Appl. Meteor. Climatol.,46,288-305.
[5]Kosko, B.,1992:Neural Networks and Fuzzy Systems:A Dynamical Systems Approach to Machine Intelligence. Prentice Hall,449 pp.
[6]刘黎平,吴林林,杨引明.基于模糊逻辑的分步式超折射地物回波识别方法的建立和效果分析[J].气象学报,2007,65(2)：252-260.
[7]毛紫阳,段崇雯,成礼智等.模糊特征在天气雷达反射率基数据质量控制中的应用[J].模糊系统与数学,2006,20(6)：136-142
[8]唐飞,李刚,马旭林.一种基于FCM算法的雷达反射率基数据的质量控制方案[J].大气科学学报,2012,35(2)：214-220.
[2]中国气象局网站：http://english.cma.gov.cn/qxxdh/leida/index.php
[3]张培昌,杜秉玉.戴铁丕.雷达气象学[M].北京：气象出版社,2001.
[4]Alberoni, P. P., Andersson, T., Mezzasalma, P., Michelson, D. B., and Nanni, S., 2001. Use of the vertical reflectivity profile for identification of anomalous propagation. Meteorol. Appl.8(3),257-266.
[5]赵恒轩.90年代天气雷达监测网建设与发展[J].成都气象学院学报.1999(3)：252-260.
[6]许柏魁,朱晓华.脉冲多普勒气象雷达信号处理系统研究[D].2002.
[6]张华,朱晓华.脉冲多普勒气象雷达信号处理系统研究[D].2003.
[7]肖艳娇,刘黎平.新一代天气雷达三维组网技术及其应用研究[D].2007.
[8]R.L.Alborty and T.D.Crum. NEXRAD and the operational Doppler weather radar for the 1990s and beyond, International Simposium on Geoscience and Remote Sensing. Vol-1, Jan.1990:725-728.
[9]P. Hildebrand, C. A. Walther, C. Frush, J. Testud, F. Baudin. "The ELDORA/ ASTRAIA airborne Doppler weather radar:goals, design and first field tests". Preceeding of the IEEE. Vol-82,NO.12, Dec.1994:1873-1890.
[10]杨尚军,邹逢兴.雷达模拟器气象杂波的建模与仿真[D].2006.
[1]Ray P, C Ziegler. De-aliasing first-moment Doppler estimates[J]. J. Appl. Meteor., 1977,16(5):563-564.
[2]Bargen D W, R. C Brown. Interactive radar velocity unfolding[C]. Preprints, Conf. On Radar Meteorology, Miami, FL, Amer. Meteor. Soc.,1980:278-283.
[3]Hennington L, Reducing the effects of Doppler radar ambiguities [J]. J. Appl. Meteor.,1981,20(12):1543-1546.
[4]Eilts M D, S D Smith. Efficient dealiasing of Doppler velocities using local environment constraints [J]. J. Atmos. Oceanic Technol.,1990,7(1):118-128.
[5]Merritt M W. Automatic velocity dealiasing for real-time applications[C]. Proc. 22nd Conf. on Radar Meteorology. Zurich, Amer. Meteor. Soc.,1984:528-533.
[6]Bergen W R, S C Albers. Two and three-dimensional dealiasing of Doppler radar velocities[J]. J. Atmos. Oceanic Technol.,1988,5(2):305-319.
[7]Gong J, L Wang, Xu Q.. A three-step dealiasing method for Doppler velocity data quality control[J]. J. Atmos. Oceanic Technol.,2003,20(12):1738-1748.
[8]Tabary P, G Scialom, U Germann. Real-time retrieval of the wind from aliased velocities measured by Doppler radars[J]. J. Atmos. Oceanic Technol..2001,18(6): 875-882.
[9]Xu Q., K. Nai, and L. Wei,2010:Fitting VAD wind to aliased radial-velocity observations-A minimization problem with multiple minima. Quart. J. Roy. Meteor. Soc.,136,451-461.
[10]Xu Q., K. Nai, and L. Wei, et al. A VAD-Based Dealiasing Method for Radar Velocity Data Quality Control. J. Atmos. Oceanic Technol,2010,28,50-62.
[11]James C. N., R. A. Houze. A real-time four dimensional Doppler dealiasing scheme[J]. J. Atmos. Oceanic Technol.,2001,18(10):1674-1683.
[12]Zhang J, S Wang. An automated 2-D multi-pass velocity dealiasing scheme[C]. Preprints,11th Conf. on Aviation, Range, and Aerospace, Hyannis, MA, Amer. Meteor. Soc.,2004, paper 5.5.
[13]蔡亲波,颜琼丹.二维多路多普勒雷达风场自动退模糊算法应用研究[J].气象科学,2000,29(5)：625-632.
[14]Lim E, J Sun. A Velocity Dealiasing Technique Using Rapidly Updated Analysis from a Four-dimensional Variational Doppler Radar Data Assimilation System[J]. J. Atmos. Oceanic Technol.,2010,27(7):1140-1152.
[15]雷小途,陈联寿.热带气旋风场模型构造及特征参数估算[J].地球物理学报,2005,48(1)：25～31.
[1]Zhang J, S Wang. An automated 2-D multi-pass velocity dealiasing scheme[C]. Preprints,11th Conf. on Aviation, Range, and Aerospace, Hyannis, MA, Amer. Meteor. Soc.,2004, paper 5.5.
[2]Eilts M D, S D Smith. Efficient dealiasing of Doppler velocities using local environment constraints [J]. J. Atmos. Oceanic Technol.,1990,7(1):118-128.
[1]Steiner, M., and J. A. Smith,2002 Use of three-dimensional reflectivity structure for automated detection and removal of nonprecipitating echoes in radar data. J. Atmos. Oceanic Technol.,19,673-686.
[2]Kessinger, C., S. Ellis, and J. vanAndel,1999:A fuzzy logic, radar echo classification scheme for the WSR-88D. Preprints,29th Int. Conf. on Radar Meteorology, Montreal, QC, Canada, Amer. Meteor. Soc.,576-579.
[3]Zhang J, Wang S, Clarke B. Wsr-88d reflectivity quality control using horizontal and vertical reflectivity structure[C].11th Conference on aviation, range and aerospace meteorology. Hyannis,2004:54.
[4]Lakshmanan, V, A. Fritz, T. Smith, K. Hondl, and G. Stumpf,2007:An automated technique to quality control radar reflectivity data. J. Appl. Meteor. Climatol.,46,288-305.
[5]Kosko, B.,1992:Neural Networks and Fuzzy Systems:A Dynamical Systems Approach to Machine Intelligence. Prentice Hall,449 pp.
[6]刘黎平,吴林林,杨引明.基于模糊逻辑的分步式超折射地物回波识别方法的建立和效果分析[J].气象学报,2007,65(2)：252-260.
[7]毛紫阳,段崇雯,成礼智等.模糊特征在天气雷达反射率基数据质量控制中的应用[J].模糊系统与数学,2006,20(6)：136-142
[8]唐飞,李刚,马旭林.一种基于FCM算法的雷达反射率基数据的质量控制方案[J].大气科学学报,2012,35(2)：214-220.