doi:  10.3878/j.issn.1006-9895.1805.17289
X波段双线偏振多普勒雷达共极化差分相移资料的滤波方法研究

The Study of Method for Filtering Copolar Differential Phase of X-Band Dual-Polarimetric Doppler Weather Radar
摘要点击 106  全文点击 34  投稿时间:2017-11-22  修订日期:2018-02-04
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基金:  北京市自然科学基金重点项目8141002,国家重点基础研究发展计划(973计划)2014CB441401、 2014CB441403,成都信息工程大学气象科普基地示范项目2017KZ0015,成都市科技惠民项目2016-HM01-00038-SF,四川省教育厅项目16CZ0021、17ZB0087,国家科技支撑计划2015BAC03B00,国家自然科学基金资助项目41575037
中文关键词:  共极化差分相移 滤波 X波段双线偏振多普勒雷达 粒子识别
英文关键词:  copolar differential phase, filter, X-band dual-polarimetric Doppler radar, hydrometeors classification
                 
作者中文名作者英文名单位
赵川鸿Zhao Chuanhong成都信息工程大学大气科学学院
周筠珺Zhou Yunjun成都信息工程大学大气科学学院
肖辉Xiao Hui中国科学院大学
赵鹏国Zhao Pengguo成都信息工程大学大气科学学院
张晓玲Zhang Xiaoling北京市气象信息中心
胡天洁Hu Tianjie北京市气象信息中心
引用:赵川鸿,周筠珺,肖辉,赵鹏国,张晓玲,胡天洁.2018.X波段双线偏振多普勒雷达共极化差分相移资料的滤波方法研究[J].大气科学
Citation:Zhao Chuanhong,Zhou Yunjun,Xiao Hui,Zhao Pengguo,Zhang Xiaoling,Hu Tianjie.2018.The Study of Method for Filtering Copolar Differential Phase of X-Band Dual-Polarimetric Doppler Weather Radar[J].Chinese Journal of Atmospheric Sciences (in Chinese)
中文摘要:
      为了提高X波段双线偏振多普勒雷达的共极化差分相移ΨC质量,利用714XDP-A型车载X波段双线偏振多普勒雷达在北京顺义的探测资料,构造了一个综合滤波方法。将其应用于滤波处理,得到结果:1)综合小波去噪滤波方法在滤波处理及KDP的估算方面相较于中值滤波、综合滑动平均、综合卡尔曼滤波及综合FIR都是最优秀的,其能较好地保留原始ΨC平均趋势及细节特征(偏差基本在±2°可信范围内,部分区域由于对原始ΨC细节特征的保留会略有超出),避免探测误差零值对滤波产生的影响(误差零值订正值回归平均趋势水平,偏差在±2°可信范围内),对原始ΨC距离廓线的平滑程度达到了94~97%(平滑了超出±1.5°/Gate的波动,对±1.5°/Gate内波动保留);2)估算的KDP整体在±5°/km边界阈值内,避免了探测误差零值、环境噪声和δ对KDP估算产生的误差影响,KDP对较强降水指示明显(在回波强度30dBZ≤ZH<37dBZ的层积云降水中KDP普遍大于0.25°/km,峰值可达到4.3°/km;在回波强度30dBZ≤ZH<50dBZ的积雨云降水中KDP普遍大于0.1°/km,峰值可达到1.95°/km);3)结合粒子识别研究,统计了水成物粒子与KDP对应关系,层积云中DR(-1.5~1.0°/km)、RA(-0.6~2.5°/km)、DC(-3~4.5°/km)、DS(-1.1~2.4°/km)、WS(-0.3~0.8°/km)、DG(-3.8~1.9°/km)和积雨云中RH(-0.2~1.2°/km)、DG(-0.44~1.31°/km)、WG(0.46~1.35°/km)、RA(-0.19~1.95°/km)。本文工作对于降水估测和水成物粒子识别有着改善效果,这对雷暴天气预警预报具备重要意义。
Abstract:
      Utilizing the measurements of the 714XDP-A X-band dual-polarimetric Doppler radar located at Shunyi Beijing to produce an integrated filter method for improving the quality of the copolar differential phase ΨC what is measured by X-band dual-polarimetric Doppler radar. Using the integrated filter method for filtering, the result is that 1) the integrated wavelet de-noising method is the best than median, integrated mean, integrated Kalman and integrated FIR filters, it retains the mean trend of raw ΨC range profiles and details(deviations inside ±2° which is regarded as credible, some details will exceed the range slightly), furthermore, avoiding the zero value what is error by measurement to interfere the filtered results(the corrected value for zero error returned the level of mean trend, deviations inside ±2° which is regarded as credible), in addition, the fluctuation index of filtered ΨC range profiles by integrated wavelet de-noising reduced 94%~97% than raw ΨC range profiles, smoothing effect is remarkable(smoothing the fluctuations what exceed ±1.5°/Gate, retaining the fluctuations what are inside ±1.5°/Gate). 2) The KDP after integrated wavelet de-noising are inside the boundary which is ±5°/km, avoiding the interferences which are induced by zero error, δ and environment noises, what’s more, it can indicate the strong precipitation (if the precipitation system is stratocumulus and 30dBZ≤ZH<37dBZ, generally KDP will greater than 0.25°/km, the maximum is 4.3°/km, if the precipitation system is cumulonimbus and 30dBZ≤ZH<50dBZ, generally KDP will greater than 0.1°/km, the maximum is 1.95°/km). 3) Counting the corresponding feature relationship between the types of hydrometeors and KDP with the research of hydrometeors classification. If the system is stratocumulus, DR(-1.5~1.0°/km), RA(-0.6~2.5°/km), DC(-3~4.5°/km), DS(-1.1~2.4°/km), WS(-0.3~0.8°/km), DG(-3.8~1.9°/km), if the system is cumulonimbus, RA(-0.19~1.95°/km), DG(-0.44~1.31°/km), WG(0.46~1.35°/km) and RH(-0.2~1.2°/km). This study is beneficial to the rainfall estimation and the hydrometeors classification, that is important for forecasting of thunderstorm weather.
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