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基于支持向量机的微波链路雨强反演方法

宋堃 高太长 刘西川 印敏 薛杨

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基于支持向量机的微波链路雨强反演方法

宋堃, 高太长, 刘西川, 印敏, 薛杨

Method and experiment of rainfall intensity inversion using a microwave link based on support vector machine

Song Kun, Gao Tai-Chang, Liu Xi-Chuan, Yin Min, Xue Yang
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  • 为提高微波链路雨致衰减反演雨强精度, 在Mie散射理论、气体吸收衰减模型以及Gamma雨滴谱分布的基础上, 将支持向量机引入到微波链路测量降水中, 提出了基于支持向量机的微波链路雨强反演方法, 并开展了15–20 GHz频段的视距微波链路与地面雨滴谱仪的同步观测降雨实验. 实验结果表明, 基于支持向量机的微波链路雨强反演模型的反演雨强与实测雨强的相关系数全部高于0.6, 最高达到0.9674; 雨强的均方根误差最小值为0.5780 mm/h, 累积降雨量的绝对最小误差仅为0.0080 mm; 相对偏差大部分在10%以内, 最小偏差为0.7425%. 实验结果验证了基于支持向量机的微波链路雨强反演方法的有效性、准确性和适用性, 对于进一步提高微波链路反演降雨精度、改善降水监测效果具有重要意义.
    The precipitation is an important physical phenomenon. The real-time, accurate measurement of rainfall intensity has important significance in meteorological support, agriculture, weather forecasting, transportation industry and military mission. However, current methods, such as the rain gauge, the weather radar and meteorological satellite, are unable to meet the needs in all the areas above at present. The network of rain gauge is costly. Meanwhile, rain gauge has low spatial and temporal resolution. And the weather radar has a big deviation because of the ground clutter. Besides, the meteorological satellite is unable to measure the surface rainfall. Thus, a method of using the measurement of microwave rain-induced attenuation for rainfall estimation has been presented in meteorological field recently by meteorological experts and it has made some progress. The method based on microwave link has low cost because of using preexisting microwave device. There are also many preexisting microwave transmission networks, which can be used by rainfall field inversion in the future research. The method measures rainfall intensity more accurately because the propagation path of microwave is close to the surface. Many models for inversing rainfall intensity by rain-induced microwave attenuation have been put forward on account of the method advantages. The commonly used model for inversion of rain rate is given by International Telecommunication Union (ITU). However, the model presented by ITU ignores a number of meteorological factors such as temperature, humidity and air pressure, which to some degree reduces the accuracy of the rainfall inversion based on microwave link. Thus, based on the theory of support vector machine (SVM), an inversion method of the path rainfall intensity by using a microwave link is proposed. Starting from the theory of Mie scattering and the atmospheric gas absorption attenuation model, a model of rainfall intensity inversion of line-of-sight microwave links is proposed, which is based on support vector machine, the microwave rain attenuation characteristics and the Gamma drop-size distribution. One line-of-sight microwave link is designed and used to measure the microwave rain-induced attenuation and inverse rainfall. Compared with actual rainfall intensity measured by a disdrometer, inversion rainfall intensity shows a satisfactory result. The correlation coefficient of rain rate is inversed by microwave link based on SVM and that of disdrometer is higher than 0.6 mostly, and the maximum value is 0.9674; the minimum value of the root-mean-square error of the rain rate is 0.5780 mm/h; the minimum value of the error of accumulated rain amount is 0.0080 mm; the relative error of accumulated rain amount is less than 10% and its minimum value is 0.7425%. All these parameters above are superior to ITU's. Therefore, the inversion result demonstrates the validity, feasibility and accuracy of rainfall inversion model using a microwave link based on SVM. The model we present is of great significance for further improving the accuracy of inversion of rain rate based on microwave link and rainfall monitoring.
      通信作者: 高太长, 2009gaotc@gmail.com
    • 基金项目: 国家自然科学基金(批准号: 41475020, 41405024, 41327003)资助的课题.
      Corresponding author: Gao Tai-Chang, 2009gaotc@gmail.com
    • Funds: Project supported by the National Natural Science Foundation of China (Grant Nos. 41475020, 41405024, 41327003).
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  • [1]

    Gao T C 2012 Meteorol. Hydrol. Eq. 23 1 (in Chinese) [高太长 2012 气象水文装备 23 1]

    [2]

    L D R, Wang P C, Qiu J H, Tao S Y 2003 Chin. J. Atmos. Sci. 27 552 (in Chinese) [吕达仁, 王普才, 邱金恒, 陶诗言 2003 大气科学 27 552]

    [3]

    Liang H H, Xu B X, Liu L P, Ge R S 2005 Adv. Earth Sci. 20 541 (in Chinese) [梁海河, 徐宝祥, 刘黎平, 葛润生 2005 地球科学进展 20 541]

    [4]

    Qie X S, L D R, Chen H B, Wang P C, Duan S, Zhang W X 2008 Chin. J. Atmos. Sci. 32 867 (in Chinese) [郄秀书, 吕达仁, 陈洪滨, 王普才, 段树, 章文星 2008 大气科学 32 867]

    [5]

    Messer H, Zinevich A, Alpert P 2006 Science 312 713

    [6]

    Goldshtein O, Messer H, Zinevich A 2009 IEEE Trans. Signal Proces. 57 1616

    [7]

    Messer H, Zinevich A, Alpert P 2012 IEEE Trans. Instrum. Meas. 15 32

    [8]

    David N, Alpert P, Messer H 2013 Atmos. Res. 131 13

    [9]

    Overeem A, Leijnse H, Uijlenhoet R 2013 Proc. Natl. Acad. Sci. USA 110 2741

    [10]

    Liu X C, Liu L, Gao T C, Ren J P 2013 J. Infrared Millim. Waves 32 379 (in Chinese) [刘西川, 刘磊, 高太长, 任景鹏 2013 红外与毫米波学报 32 379]

    [11]

    Liu X C, Gao T C, Liu L, Zhai D L 2014 Acta Phys. Sin. 63 199201 (in Chinese) [刘西川, 高太长, 刘磊, 翟东力 2014 物理学报 63 199201]

    [12]

    Jiang S T, Gao T C, Liu X C, Liu L, Liu Z T 2013 Acta Phys. Sin. 62 154303 (in Chinese) [姜世泰, 高太长, 刘西川, 刘磊, 刘志田 2013 物理学报 62 154303]

    [13]

    Yin M, Jiang S T, Gao T C, Liu X C, Liang M Y, Ge S R, Cao C K 2015 Meteorol. Sci. Technol. 43 1 (in Chinese) [印敏, 姜世泰, 高太长, 刘西川, 梁妙元, 戈书睿, 曹承堃 2015 气象科技 43 1]

    [14]

    Gao T C, Song K, Liu X C, Yin M, Liu L, Jiang S T 2015 Acta Phys. Sin. 64 174301 (in Chinese) [高太长, 宋堃, 刘西川, 印敏, 刘磊, 姜世泰 2015 物理学报 64 174301]

    [15]

    International Telecommunication Union 2005 Rec. ITU-R p838-3

    [16]

    Zhao H G, Wen J H, Liu Y Z, Yu D L, Wang G, Wen X S 2008 Chin. Phys. B 17 1305

    [17]

    Liu X C, Gao T C, Han X D 2010 J. Meteorol. Sci. 30 42 (in Chinese) [刘西川, 高太长, 韩小冬 2010 气象科学 30 42]

    [18]

    David N, Alpert P, Messer H 2009 Atmos. Chem. Phys. 9 2413

    [19]

    Chen B J, Li Z H, Liu J C, Gong F J 1998 Acta Meteorol. Sin. 56 123 (in Chinese) [陈宝君, 李子华, 刘吉成, 宫福久 1998 气象学报 56 123]

    [20]

    Yuan C, Fan L, Li Y B 2001 J. Nanjing I. Meteorol. 24 250 (in Chinese) [袁成, 樊玲, 李亚滨 2001 南京气象学院学报 24 250]

    [21]

    Zheng J H, Chen B J 2007 J. Meteorol. Sci. 27 17 (in Chinese) [郑娇恒, 陈宝君 2007 气象科学 27 17]

    [22]

    Freeman R 1991 Telecommunications Transmission Handbook (3rd Ed.) (Canda: John Wiley & Sons Inc.) p279

    [23]

    Liu X C, Gao T C, Liu L 2013 Infrared Laser Eng. 42 167 (in Chinese) [刘西川, 高太长, 刘磊 2013 红外与激光工程 42 167]

    [24]

    Liu H H, Liu Y H 2012 Chin Phys. B 21 026102

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基于支持向量机的微波链路雨强反演方法

  • 1. 解放军理工大学气象海洋学院, 南京 211101
  • 通信作者: 高太长, 2009gaotc@gmail.com
    基金项目: 国家自然科学基金(批准号: 41475020, 41405024, 41327003)资助的课题.

摘要: 为提高微波链路雨致衰减反演雨强精度, 在Mie散射理论、气体吸收衰减模型以及Gamma雨滴谱分布的基础上, 将支持向量机引入到微波链路测量降水中, 提出了基于支持向量机的微波链路雨强反演方法, 并开展了15–20 GHz频段的视距微波链路与地面雨滴谱仪的同步观测降雨实验. 实验结果表明, 基于支持向量机的微波链路雨强反演模型的反演雨强与实测雨强的相关系数全部高于0.6, 最高达到0.9674; 雨强的均方根误差最小值为0.5780 mm/h, 累积降雨量的绝对最小误差仅为0.0080 mm; 相对偏差大部分在10%以内, 最小偏差为0.7425%. 实验结果验证了基于支持向量机的微波链路雨强反演方法的有效性、准确性和适用性, 对于进一步提高微波链路反演降雨精度、改善降水监测效果具有重要意义.

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