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高原气象  2018, Vol. 37 Issue (4): 1033-1041    DOI: 10.7522/j.issn.1000-0534.2017.00084
论文     
机载微波辐射计亮温数据中RFI识别方法研究
王婉1,2, 雷恒池3, 王兆宇1, 郭晓军1, 聂皓浩1
1. 天津市人工影响天气办公室, 天津 300074;
2. 中国气象局云雾物理环境重点实验室, 北京 100081;
3. 中国科学院大气物理研究所云降水物理与强风暴重点实验室, 北京 100029
Method Study on Identification of Radio-Frequency Interference Signal from Airborne Microwave Radiometer
WANG Wan1,2, LEI Hengchi3, WANG Zhaoyu1, GUO Xiaojun1, NIE Haohao1
1. TianJin Weather Modification Office, TianJin 300074, China;
2. Key Laboratory for Cloud Physics of China Meteorological Administration, Beijing 100081, China;
3. Key Laboratory of Cloud-Precipitation Physics and Severe Storms, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
 全文: PDF 
摘要: 机载微波辐射计(G-band water Vapor Radiometer,GVR)在使用过程中发现存在无线电频率干扰信号(Radio-Frequency Interference,RFI),为准确使用数据,需对干扰信号进行识别和订正。在分析多种RFI识别方法在GVR数据中的适用性基础上,根据GVR探测及定标原理提出适用于GVR的RFI识别和订正方案。采用该方案对天津市2016年11月20日一次GVR亮温数据进行识别和订正,结果表明,该方法能较好的识别出各通道亮温数据中的RFI信号;RFI存在于多个通道中,时空分布无规律,具有随机性,为干扰源确定带来较大困难;RFI在亮温数据中除少数以孤立点形式存在,多数为连续干扰点,连续干扰点越多,订正效果越差,当连续干扰点较多时建议剔除该部分数据。RFI订正前后的反演结果对比分析表明,多数情况下,RFI的存在使得垂直累积水汽和垂直累积液态水含量值被高估,少数值被低估,单个通道做订正对反演结果的影响不同。
关键词: GVR无线电频率干扰识别    
Abstract: Radio-frequency interference (RFI) signals were found in the brightness temperature datas of G-band water Vapor Radiometer (GVR). It is necessary to identify and correct the interference datas for better use. Based on the analysis of the applicability of various RFI identification methods of GVR data, the RFI recognition and correction method for GVR was proposed according to the principle of GVR detection and calibration. This method is used to identify the RFI from GVR brightness temperature datas on November 20, 2016 and the results show that:(1)The method works well for identifying the RFI from the brightness temperature datas of GVR different channels; (2) RFI signals exist in multiple channels and have no regular distribution in spatial and temporal that brings great difficulties to determine the source of RFI; (3) In addition to a few signals exist in the form of isolated points, majority of RFI signals in the brightness temperature datas exist in the form of continuity points. The more the continuity interference points are, the worse the correction results are. The datas are recommended to be eliminated when there are many continuity interference points. The retrival results analysis of before and after correction of RFI from GVR datas show that most of the PWV (Precipitable Water Vapor) and LWP (Liquid Water Path) values are overestimated because of the RFI and the correction of individual channels, which has different effects on the retrival results.
Key words: GVR    radio-frequency interference    identification
收稿日期: 2017-07-06 出版日期: 2018-08-22
:  P407.7  
基金资助: 中国气象局云雾物理环境重点实验室开放科研课题(2017Z01609);天津市气象局科研课题(201707ybxm07);国家自然科学基金项目(41675046,41675078)
作者简介: 王婉(1981-),女,江苏沛县人,高级工程师,主要从事云降水物理方面的研究.E-mail:vvan1981@126.com
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引用本文:

王婉, 雷恒池, 王兆宇, 郭晓军, 聂皓浩. 机载微波辐射计亮温数据中RFI识别方法研究[J]. 高原气象, 2018, 37(4): 1033-1041.

WANG Wan, LEI Hengchi, WANG Zhaoyu, GUO Xiaojun, NIE Haohao. Method Study on Identification of Radio-Frequency Interference Signal from Airborne Microwave Radiometer. Plateau Meteorology, 2018, 37(4): 1033-1041.

链接本文:

http://www.gyqx.ac.cn/CN/10.7522/j.issn.1000-0534.2017.00084        http://www.gyqx.ac.cn/CN/Y2018/V37/I4/1033

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