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Raindrop Size Distribution Retrieval from Wind Profiler Radar Based on Double-Gaussian Fitting
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摘要: 在降水条件下，风廓线雷达返回信号是湍流信号和降水信号的叠加，其功率谱数据中通常会出现双峰结构。该文通过双高斯拟合方法区分大气湍流信号功率谱和降水信号功率谱，去除大气湍流对降水信号谱的影响，反演得到较为精确的雨滴谱分布。研究表明:在风廓线雷达估算雨滴谱的过程中，双高斯拟合可将两峰有效分离，利用处理后的降水谱反演得到的雨滴谱均呈指数分布。选取北京延庆地区2006年和2012年具有代表性的降水资料，对比反演得到的不同强度和不同类型降雨的雨滴谱资料显示，这种估算雨滴谱的方法可行且可靠，利用双高斯拟合将双峰分离，可以达到风廓线雷达数据质量控制的目的，对于风廓线雷达在更为复杂的天气条件下应用具有借鉴意义。Abstract: The raindrop size distribution is extremely important for understanding the physical process of cloud and fog formation, and the generation of natural rainfall. It is a major tool that can be used to assess the cloud conditions for weather modification and verify associated results, in addition to being an important scientific evidence for numerical modeling.The weather radar often uses the method of PPP (Pulse Pair Processing) to process the signal, so it cannot get the raindrop size data directly. However, wind profiler radar is invented to detect the turbulence of clear air and it can obtain the distribution of Doppler velocity of precipitation particles, hence data can be used to retrieve raindrop spectral of precipitation effectively. Under the condition of precipitation, the return information of wind profiler radar is superimposed by turbulent signal and precipitation signal, and the power spectrum would often appear an obvious bimodal structure. Some representative precipitation data of Yanqing, Beijing in 2006 and 2012 are analyzed, by the method of removing noise and calibration curve, the power spectrum of antenna array is retrieved and then a more accurate signal power spectrum is obtained. The method of double-Gaussian fitting is used to distinguish the power spectrum of atmospheric turbulence signal and the power spectrum of precipitation signal. The signal is used to estimate a better raindrop size distribution after removing effects of air turbulence. According to relations between precipitation particles and diameters, the raindrop spectrum can be obtained easily. Through analyses and comparisons of different intensity and types of retrieved raindrop size distribution data, it can be concluded that in the process of estimating the raindrop size distribution from wind profiler radar, the method of double-Gaussian fitting could separate two peaks effectively, and the precision is more accurate and the structure emerges an exponential form basically. The result shows that using the double-Gaussian fitting to separate the bimodal structure of power spectral data is feasible and reliable, and it can achieve better quality control of wind profile radar data. Also, the method provides reference for applying wind profiler radars under more complex weather conditions.
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Key words:
- wind profile radar;
- raindrop size;
- double-Gaussian fitting
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图 3 风廓线雷达垂直波束在2006年8月25日20:45 (a) 和2012年7月21日11:05 (b) 探测的25个距离库的功率谱密度分布
Fig. 3 The density of return signal power at 25 different heights detected by the wind profile radar vertical sounding at 2045 BT 25 Aug 2006 (a) and 1105 BT 21 Jul 2012 (b)
图 4 2006年8月25日20:45 2670 m高度 (a) 和2012年7月21日11:05 1590 m高度 (b) 雨滴谱分布
Fig. 4 The raindrop size distribution from wind profile radar at the height of 2670 m
图 5 2006年8月25日21:42 (a) 和2012年4月24日03:00 (b) 北京地区雷达回波图
Fig. 5 The radar echoes of Beijing Region at 2142 BT 25 Aug 2006 (a) and 0300 BT 24 Apr 2012 (b)
图 6 风廓线雷达垂直波束在2006年8月25日21:42 (a) 和2012年4月24日03:00 (b) 探测的25个距离库的功率谱密度分布
Fig. 6 The density of return signal power at 25 different heights detected by the wind profile radar vertical sounding at 2142 BT 25 Aug 2006 (a) and 0300 BT 24 Apr 2012 (b)
图 7 2006年8月25日1350 m高度功率谱分布和双高斯拟合结果 (a) 以及雨滴谱分布 (b)
Fig. 7 The density of return signal power and the result of double-Gauss fitting (a) and raindrop size distribution (b) at the height of 1350 m on 25 Aug 2006
图 8 2012年4月24日1230 m高度功率谱分布和双高斯拟合结果 (a) 以及雨滴谱分布 (b)
Fig. 8 The density of return signal power and the result of double-Gauss fitting (a) and raindrop size distribution (b) at the height of 1230 m on 24 Apr 2012
图 9 2006年8月25日21：00 25个库双高斯拟合相关系数分布
Fig. 9 The distribution of 25 coefficients of determination at 2100 BT 25 Aug 2006
图 10 各个高度上λ (a) 和N0 (b) 的分布
Fig. 10 Distributions of λ (a) and N0 (b) at different heights
表 1 雷达参数
Table 1 Parameters of radar
参数 探测模式 低 高 波长/mm 674 674 采样频率/MHz 40 40 脉冲宽度/μs 0.8 4 噪声系数/dB 2 2 谱变换数 256 512 谱平均数 6 12 相干积分次数 200 50 距离库长/m 120 240 Nyquist速度/(m·s-1) ±16.7 ±33.3 最小速度间隔/(m·s-1) 0.13 0.13 天线增益/dB 29 29 发射功率/kW 7.7 7.7 
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