| 摘要: | 本次研究是利用中壢特高頻(VHF)52MHz雷達以及地面二維雨滴譜儀(Disdrometer)來研究空中降水的情形，可分別得到空中降水粒子的終端速度、回波功率、頻譜寬、大氣回波功率、大氣垂直速度、大氣頻譜寬以及地面降雨率、雨滴粒徑分佈參數。由於降水粒子會對電磁波在大氣中的傳播造成衰減，因此研究空中降水粒子特性便為之重要，尤其是降水粒子在空中的粒徑分佈情形。
過去幾年內，許多研究皆說明了伽瑪雨滴粒徑分佈較符合真實雨滴粒子的分佈狀況，此文透過反捲積(Deconvolution)的方法反演出空中伽瑪雨滴粒徑分佈參數N_0 、μ、Λ，進而得到重要降水參數，如質量均值粒徑(D_m)、質量中值粒徑(D_0)、降雨率(R)等等…。為了驗證反捲積過程能有效地運用在雷達觀測資料上，藉由理論推導來模擬雷達降水回波頻譜及其對應的雨滴粒徑分佈情形，並考慮在不同大小雜訊影響下，反捲積過程的結果與理論值的誤差，可以發現隨著訊雜比的提升，所得到的誤差將隨之減少。
本次觀測的降水事件為2019年6月22日22:10LT至6月23日18:00LT這兩天的降水資料，分別利用傳統的反演方式以及反捲積方法反演空中降水參數D_m 、R並與地面雨滴譜儀量測結果做比較，顯示相對於傳統方式，反捲積過程的結果較趨近於地面雨滴譜儀觀測之結果。接著，依據不同的降水型態來分析所反演的降水參數並與特定時間下雨滴譜儀的資料做比對，計算兩者間的相關係數、方均根差、互相關函數，顯示無論是層狀降水或是對流降水，在時間平移後所得到的結果皆有改善的現象且受到不同大氣垂直速度的影響，使得兩種不同降水型態的時間延遲也有不同的結果。最後，探討降水終端速度與頻譜寬之間的關係，由散佈圖可看出隨著雷達回波的訊雜比提升，所觀測到的散佈型態較類似地面雨滴譜儀量測的結果，故訊雜比的大小為反演結果好壞的重要指標。
;The study uses Chung-Li 52MHz VHF radar and two dimensional video disdrometer (2DVD or disdrometer) to investigate precipitation phenomenon in the air. We can obtain precipitation terminal velocity, echo power, spectral width, air velocity, air echo power, air spectral width, rainfall rate and drop size distribution (DSD) from each apparatus. The precipitation particles will attenuate electromagnetic wave propagation in the air, so the study of their characteristic is very important, especially for DSD in the air.
In the past few years, many researches suggested that Gamma DSD was the closest to real DSD. The study through the deconvolution method to retrieve Gamma DSD parameters N_0 、μ、Λ and further important parameters such as mass-weighted averaged diameter (D_m), median volume diameter (D_0) and rainfall rate (R) etc. in the air. We simulate radar precipitation spectrums and corresponding DSDs through the theoretical formula in order to confirm the deconvolution method can efficiently be used in radar observed data, and then consider the errors between deconvolution results and theoretical values with different signal-to-noise ratio (SNR). The results show the errors reduce while SNR increase.
The data in this study is the precipitation events from June 22th 22:10LT to June 23th 18:00LT, 2019. We compare precipitation parameters D_m and R retrieved by traditional method and deconvolution process with ground-based 2DVD and find that deconvolution method is more closer to the 2DVD observation then tradition does. Next, according to precipitation characteristics, we separate the precipitation events into two categories, stratiform and convective precipitations. The statistical parameters, i.e., correlation coefficient, root-mean-square error and cross correlation function are calculated to compare radar retrieved parameters with 2DVD. Finally, both categories improve their results after the time shift. However, due to the different air velocity, the time delay will also be different. Last, we investigate the relationship between precipitation terminal velocity and its spectral width. The scatter diagrams show that the performances become closer to the pattern of disdrometer’s results when SNR increase, so the level of SNR be an important index when retrieving precipitation parameters in the air. |
