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北京MST雷达功率谱密度处理算法改进

陈泽 田玉芳 吕达仁

陈泽, 田玉芳, 吕达仁. 北京MST雷达功率谱密度处理算法改进. 应用气象学报, 2020, 31(6): 694-705. DOI: 10.11898/1001-7313.20200605.
引用本文: 陈泽, 田玉芳, 吕达仁. 北京MST雷达功率谱密度处理算法改进. 应用气象学报, 2020, 31(6): 694-705. DOI: 10.11898/1001-7313.20200605.
Chen Ze, Tian Yufang, Lü Daren. Improving the processing algorithm of Beijing MST radar power spectral density data. J Appl Meteor Sci, 2020, 31(6): 694-705. DOI:  10.11898/1001-7313.20200605
Citation: Chen Ze, Tian Yufang, Lü Daren. Improving the processing algorithm of Beijing MST radar power spectral density data. J Appl Meteor Sci, 2020, 31(6): 694-705. DOI:  10.11898/1001-7313.20200605

北京MST雷达功率谱密度处理算法改进

DOI: 10.11898/1001-7313.20200605
资助项目: 

国家自然科学基金项目 41905042

电波环境特性及模化技术重点实验室基金 6142403180204

临近空间探测实验与科学研究 XDA17010103

中国科学院前沿科学重点研究项目 QYZDY-SSW-DQC027

详细信息
    通信作者:

    田玉芳, tianyufang@mail.iap.ac.cn

Improving the Processing Algorithm of Beijing MST Radar Power Spectral Density Data

  • 摘要: 北京MST(mesosphere-stratosphere-troposphere,中间层-平流层-对流层)雷达是我国“子午工程”一期中探测大气动力结构的独特大型设备。雷达自2011年建成以来,已获取较好的大气风场数据,但在其他要素提取方面仍有改进需求。从噪声电平估算与目标回波识别这两个关键步骤改进雷达原始功率谱密度处理算法,以期得到更准确的大气要素信息。在噪声电平估算方面,提出应用对数-线性拟合方案快速实现客观分析法,与二分法方案差值的标准差为0.43 dB,表明对数-线性拟合方案能兼顾时效性与准确性。改进后的数据处理算法能够精确识别目标回波。利用改进算法处理2012年1—12月数据结果与雷达、探空以及ERA5再分析数据进行比较,各高度纬向风与探空测值的均方根误差均为2~3 m·s-1,优于雷达产品和探空测值均方根误差(3~4 m·s-1),信噪比、谱宽和垂直速度质量也有明显提高,表明改进算法可靠、有效且相对易于实现。
  • 图  1  2012年1月4日00:10北京MST雷达原始功率谱密度及数据预处理叠加经客观分析法和八段平均法处理的噪声电平(15 km高度东波束)

    Fig. 1  Beijing MST radar raw and preprocessed power spectral density and averaged noise value estimated by objective method and segment method at 0010 UTC 4 Jan 2012(eastern beam at height of 15 km)

    图  2  2012年3月16日15:10北京MST雷达观测数据的R2及lgR2随dP变化

    Fig. 2  R2 and lgR2 varying with dP using Beijing MST radar at 1510 UTC 16 Mar 2012

    图  3  2012年5月北京MST雷达7.8~12 km高度内(1715个距离库)功率谱数据应用对数-线性拟合方案与二分法方案估算噪声电平对比

    Fig. 3  The comparison of noise level estimated by log-linear scheme and dichotomy scheme using power spectral density at 7.8-12 km height of Beijing MST radar in May 2012

    图  4  2012年1月4日00:10北京MST雷达东波束与西波束经改进算法处理后5个距离库高度功率谱密度(加粗曲线表示识别出的目标回波信号)

    Fig. 4  Power spectral density of eastern and western beams at 5 heights of Beijing MST radar data processed by improved algorithm at 0010 UTC 4 Jan 2012(bold curve denotes recognized target echo)

    图  5  2012年3月16日11:40北京MST雷达原算法与改进算法得到的水平风速、水平风向与探空(11:15)对比

    Fig. 5  Comparison of the horizontal wind speed and wind direction between radiosonde(1115 UTC) and Beijing MST radar products before and after improved algorithm processed(1140 UTC) on 16 Mar 2012

    图  6  2012年1月1日—12月31日信噪比(a)和谱宽(b)的年平均值(曲线)和标准差(阴影)廓线

    Fig. 6  Comparison of annual mean(the curve) and standard deviation(the shaded) of SNR(a) and spectral width(b) between Beijing MST radar data(from 1 Jan to 31 Dec in 2012) obtained using original and improved algorithms

    图  7  2012年1月1日—12月31日北京MST雷达原算法与改进算法得到的经向风、纬向风与探空对比

    Fig. 7  Comparison of the zonal and meridional wind between radiosonde and Beijing MST radar data obtained using original and improved algorithms from 1 Jan to 31 Dec in 2012

    图  8  2012年1月1日—12月31日北京MST雷达原算法与改进算法得到的垂直速度与ERA5再分析数据对比

    Fig. 8  Comparison of the vertical velocity between ERA5 reanalysis and Beijing MST radar data obtained using original and improved algorithms from 1 Jan to 31 Dec in 2012

    图  9  2012年16组降水天气条件下北京MST雷达原算法与改进算法得到的经向风、纬向风与探空测值平均差值和均方根误差廓线

    Fig. 9  Comparison of mean values and root mean square error of zonal and meridional wind between radiosonde and Beijing MST radar data obtained using original and improved algorithms under 16-group precipitation weather conditions in 2012

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  • 收稿日期:  2020-04-17
  • 修回日期:  2020-08-10
  • 刊出日期:  2020-10-27

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