Raindrop Size Distribution Retrieval from Wind Profiler Radar Based on Double-Gaussian Fitting

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.