Jan.  2014

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# A Test Pattern Identification Algorithm and Its Application to CINRAD/SA(B) Data

• A variety of faulty radar echoes may cause serious problems with radar data applications, especially radar data assimilation and quantitative precipitation estimates. In this study, ''test pattern'' caused by test signal or radar hardware failures in CINRAD (China New Generation Weather Radar) SA and SB radar operational observations are investigated. In order to distinguish the test pattern from other types of radar echoes, such as precipitation, clear air and other non-meteorological echoes, five feature parameters including the effective reflectivity data percentage (RZ), velocity RF (range folding) data percentage (RRF), missing velocity data percentage (RM), averaged along-azimuth reflectivity fluctuation (RNr,Z) and averaged along-beam reflectivity fluctuation (RNa,Z) are proposed. Based on the fuzzy logic method, a test pattern identification algorithm is developed, and the statistical results from all the different kinds of radar echoes indicate the performance of the algorithm. Analysis of two typical cases with heavy precipitation echoes located inside the test pattern are performed. The statistical results show that the test pattern identification algorithm performs well, since the test pattern is recognized in most cases. Besides, the algorithm can effectively remove the test pattern signal and retain strong precipitation echoes in heavy rainfall events.
摘要: A variety of faulty radar echoes may cause serious problems with radar data applications, especially radar data assimilation and quantitative precipitation estimates. In this study, test pattern'' caused by test signal or radar hardware failures in CINRAD (China New Generation Weather Radar) SA and SB radar operational observations are investigated. In order to distinguish the test pattern from other types of radar echoes, such as precipitation, clear air and other non-meteorological echoes, five feature parameters including the effective reflectivity data percentage (RZ), velocity RF (range folding) data percentage (R RF), missing velocity data percentage (R M), averaged along-azimuth reflectivity fluctuation (RN_ r,Z) and averaged along-beam reflectivity fluctuation (RN_ a,Z) are proposed. Based on the fuzzy logic method, a test pattern identification algorithm is developed, and the statistical results from all the different kinds of radar echoes indicate the performance of the algorithm. Analysis of two typical cases with heavy precipitation echoes located inside the test pattern are performed. The statistical results show that the test pattern identification algorithm performs well, since the test pattern is recognized in most cases. Besides, the algorithm can effectively remove the test pattern signal and retain strong precipitation echoes in heavy rainfall events.

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## Manuscript History

Manuscript revised: 09 April 2013
###### 通讯作者: 陈斌, bchen63@163.com
• 1.

沈阳化工大学材料科学与工程学院 沈阳 110142

## A Test Pattern Identification Algorithm and Its Application to CINRAD/SA(B) Data

###### Corresponding author: LIU Liping
• 1. State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081;
• 2. Nanjing University of Information Science and Technology, Nanjing 210044;
• 3. National Meteorological Center, Beijing 100081
Fund Project:  The authors are thankful to Pengfei ZHANG of NSSL and the anonymous reviewers for their comments and suggestions, which helped improve the presentation of the paper. Also, thanks are extended to CAO Jie of IAP in Beijing for assistance with the English. This paper is supported by the National Key Program for Developing Basic Sciences under Grant 2012CB417202, the National Natural Science Foundation of China under Grant No. 41175038, No. 41305088 and No. 41075023, the Meteorological Special Project Radar network observation technology and QC, the CMA Key project Radar Operational Software Engineering and the Chinese Academy of Meteorological Sciences Basic Scientific and Operational Projects Observation and retrieval methods of micro-physics and dynamic parameters of cloud and precipitation with multi-wavelength Remote Sensing, and also by Project of the State Key Laboratory of Severe Weather grant 2012LASW-B04.

Abstract: A variety of faulty radar echoes may cause serious problems with radar data applications, especially radar data assimilation and quantitative precipitation estimates. In this study, ''test pattern'' caused by test signal or radar hardware failures in CINRAD (China New Generation Weather Radar) SA and SB radar operational observations are investigated. In order to distinguish the test pattern from other types of radar echoes, such as precipitation, clear air and other non-meteorological echoes, five feature parameters including the effective reflectivity data percentage (RZ), velocity RF (range folding) data percentage (RRF), missing velocity data percentage (RM), averaged along-azimuth reflectivity fluctuation (RNr,Z) and averaged along-beam reflectivity fluctuation (RNa,Z) are proposed. Based on the fuzzy logic method, a test pattern identification algorithm is developed, and the statistical results from all the different kinds of radar echoes indicate the performance of the algorithm. Analysis of two typical cases with heavy precipitation echoes located inside the test pattern are performed. The statistical results show that the test pattern identification algorithm performs well, since the test pattern is recognized in most cases. Besides, the algorithm can effectively remove the test pattern signal and retain strong precipitation echoes in heavy rainfall events.

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