综合识别法去除风廓线雷达地物杂波的可行性研究
|
摘要
以杂波谱极小值连线的思想为基础,针对强风天气条件下的风廓线雷达地物杂波信号,提出一种综合识别杂波的去除方法,并与常规的地物杂波抑制方法相比较。结果表明:利用该方法对强风天气下的地物杂波有更好的抑制效果,水平风速得到了明显增强,与地面观测数据相比,雷达产品更趋于真实风速。
Based on the idea of the minimum connection of clutter spectrum,a comprehensive recognition method of removing ground clutter which was directed against wind profiler radar ground clutter signals under strong wind conditions was proposed in this paper.Compared with the conventional ground clutter suppression method,the results show that this method had better inhibitory effect on ground clutter under strong wind weather condition,the horizontal wind speed was obviously enhanced,compared with ground observation data,radar products tended to true wind speed. Thus,the accuracy and reliability of extracting atmospheric profile data from wind profiler radar were improved,and a good data quality control foundation for the follow-up product development was built.
Based on the idea of the minimum connection of clutter spectrum,a comprehensive recognition method of removing ground clutter which was directed against wind profiler radar ground clutter signals under strong wind conditions was proposed in this paper.Compared with the conventional ground clutter suppression method,the results show that this method had better inhibitory effect on ground clutter under strong wind weather condition,the horizontal wind speed was obviously enhanced,compared with ground observation data,radar products tended to true wind speed. Thus,the accuracy and reliability of extracting atmospheric profile data from wind profiler radar were improved,and a good data quality control foundation for the follow-up product development was built.
引文
[1]张小雯,郑永光,吴蕾,等.风廓线雷达资料在天气业务中的应用现状与展望[J].气象科技,2017,45(2):285-297.
[2]胡明宝,郑国光,肖文建.风廓线雷达数据获取率的统计分析[J].现代雷达,2008,30(10):14-15.
[3]BARTH M F,CHADWICK R B,VAN DE KAMP D W. Data pro-cessing algorithms used by NOAA’s wind profiler demonstration net-work[J]. Ann Geophys,1994,12:518-528.
[4]王莎,阮征,葛润生.风廓线雷达探测大气返回信号谱的仿真模拟[J].应用气象学报,2012,23(1):21-22.
[5]阮征,高祝宇,李丰,等.风廓线雷达与天气雷达风廓线数据的融合及应用[J].气象,2017,43(10):1213-1223.
[6]刘成,车达生,柯宗建.风廓线雷达在高空风场分析中的应用[J].沙漠与绿洲气象,2013,7(2):56-60.
[7]王天义,朱克云,张杰,等.风廓线雷达与多普勒天气雷达风矢产品对比及相关分析[J].气象科技,2014,42(2):231-239.
[8]曹俊武,胡志群.多普勒天气雷达与风廓线雷达测风比较[J].雷达科学与技术,2013(6):605-610.
[9]李喆,何平,潘新民,等.风廓线雷达回波强度和速度标定问题研究[J].气象,2015,41(8):1023-1027.
[10]胡明宝.风廓线雷达数据处理与应用研究[D].南京:南京信息工程大学,2012.
[11]马秀梅,李文兆,赵坤,等.非线性VAD反演低层风廓线拟合阶数优化方法[J].应用气象学报,2014,25(3):321-329.
[12]王令,王国荣,古月,等.风廓线雷达垂直径向速度应用初探[J].气象,2014,40(3):290-296.
[13]刘梦娟,刘舜.上海组网风廓线雷达数据质量评估[J].气象,2016,42(8):962-970.
[14]胡明宝,张鹏.风廓线雷达测量性能分析[J].气象科技,2011,39(3):315-319.
[2]胡明宝,郑国光,肖文建.风廓线雷达数据获取率的统计分析[J].现代雷达,2008,30(10):14-15.
[3]BARTH M F,CHADWICK R B,VAN DE KAMP D W. Data pro-cessing algorithms used by NOAA’s wind profiler demonstration net-work[J]. Ann Geophys,1994,12:518-528.
[4]王莎,阮征,葛润生.风廓线雷达探测大气返回信号谱的仿真模拟[J].应用气象学报,2012,23(1):21-22.
[5]阮征,高祝宇,李丰,等.风廓线雷达与天气雷达风廓线数据的融合及应用[J].气象,2017,43(10):1213-1223.
[6]刘成,车达生,柯宗建.风廓线雷达在高空风场分析中的应用[J].沙漠与绿洲气象,2013,7(2):56-60.
[7]王天义,朱克云,张杰,等.风廓线雷达与多普勒天气雷达风矢产品对比及相关分析[J].气象科技,2014,42(2):231-239.
[8]曹俊武,胡志群.多普勒天气雷达与风廓线雷达测风比较[J].雷达科学与技术,2013(6):605-610.
[9]李喆,何平,潘新民,等.风廓线雷达回波强度和速度标定问题研究[J].气象,2015,41(8):1023-1027.
[10]胡明宝.风廓线雷达数据处理与应用研究[D].南京:南京信息工程大学,2012.
[11]马秀梅,李文兆,赵坤,等.非线性VAD反演低层风廓线拟合阶数优化方法[J].应用气象学报,2014,25(3):321-329.
[12]王令,王国荣,古月,等.风廓线雷达垂直径向速度应用初探[J].气象,2014,40(3):290-296.
[13]刘梦娟,刘舜.上海组网风廓线雷达数据质量评估[J].气象,2016,42(8):962-970.
[14]胡明宝,张鹏.风廓线雷达测量性能分析[J].气象科技,2011,39(3):315-319.