| 摘要: | 歷年來臺灣所經歷的天然災害，許多都和劇烈降水所帶來之豪大雨息息相關，然而現行「定量降雨」預報仍存在諸多不確定之變數及誤差，因此，若能利用遙測技術針對強降水系統進行密集連續地觀測，瞭解其垂直結構與雲物理過程，便能提供氣象數值模式在參數設定上更真實的參考依據，進而改善降水預報準確度。本研究利用中壢特高頻雷達及國防大學理工學院微波輻射儀，於2013年8月20至23日潭美颱風侵臺期間之觀測資料，並應用多頻率雷達成像技術(RIM)進行降水回波訊號分析；此技術是利用多個頻率之回波訊號，經反演後得到高徑向解析度的亮度函數分布，並可透過傅立葉轉換獲得高徑向解析度頻譜。分析結果發現，當降水現象發生時，須採用逐點校正法進行回波訊號之時間延遲及距離權重函數校正，以提升回波於取樣層數間之連續性；而針對校正後之回波利用Capon法進行時間域訊號反演後轉換為頻率域，可獲得比原始回波徑向解析度更高之頻譜資訊。此外，本研究利用條件平均法進行回波功率、都卜勒速度及頻譜寬等頻譜參數比對，結果發現應用RIM技術於頻譜參數分析，確實可解析出更細微之大氣及降水頻譜參數結構，尤其是在層狀降水的情況下效果更佳，且其所獲得之融解層都卜勒速度隨高度之變化亦較合理。而在降水回波與大氣回波分離部分，本研究另提出Contour法及Peak-Finding法，來進行大氣及降水回波中心之自動辨識及頻譜參數分析，並發現兩種方法的結果相當一致，惟在有降水發生的情況下，FFT取樣點數的不同會造成頻譜寬的些微差異(FFT取樣點數越小，頻譜寬越寬)。本研究亦首次利用雙偏極化微波輻射儀及中壢特高頻雷達進行降水聯合觀測，分析結果發現地面降雨率和輻射儀極化差值在對流降水情況下呈現不錯之正相關，且極化差值資料可用來做為判斷當時環境是否為對流降水之型態；此外，分析結果亦發現對流降水伴隨之強上升氣流，可能造成過冷水滴和冰晶碰撞並附著於其之上，導致雷達回波功率及頻譜寬之降低。研究結果顯示，聯合觀測對於瞭解劇烈降水系統形成之雲物理機制，有極大之潛力。;In recent years, many of the natural disasters that Taiwan has experienced have been closely related to the heavy rain brought by severe precipitation. However, there are still many uncertain variables and errors in the "quantitative rainfall" forecast. Therefore, if telemetry can be used for dense and continuous observation of heavy precipitation systems, to understand its vertical structure and cloud physics process, it can provide a more realistic reference for parameter setting in meteorological numerical model and improve the accuracy of precipitation forecasting. The present study employed the data collected between 20 and 23 August 2013 by Chung-Li VHF radar and CCIT microwave radiometer, when the typhoon Trami passed through Taiwan, and use multi-frequency range imaging (RIM) technology for precipitation echo analysis. RIM processes the echo signals with a group of closely spaced transmitting frequencies through appropriate inversion methods to obtain high-resolution distribution of echo power in the range direction, and can obtain the high-range resolution Doppler spectra using Fourier transform. Point-by-point correction of range delay combined with compensation of range-weighting function effect has been performed during the retrieval of temporal signals to improve the continuity of power spectra at gate boundaries, making the small-scale structures in the power spectra more natural and reasonable. Using the Capon methods, the radar echoes were synthesized to retrieve the temporal signals at a smaller range step than the original range resolution, and such retrieved temporal signals were then processed in the Doppler frequency domain to identify the atmosphere and precipitation echoes. An analysis called conditional averaging was further executed for echo power, Doppler velocity, and spectral width to verify the potential capabilities of the retrieval processing in resolving small-scale precipitation and atmosphere structures. The performance is better especially in the case of stratiform precipitation, and the Doppler velocity of melting layer change with height is more reasonable. This study also proposes the Contour-Based and Peak-Finding method for automatic localization and spectral parameter analysis of atmospheric and precipitation echo centers, and we found the results of the two methods were in good agreement. However, it also shows that different numbers of data points in FFT could produce slightly different spectra widths, especially in rainy condition: the smaller the FFT number was, the broader the spectral width could be. In this study, it is the first time to use the ground-based double-polarized microwave radiometer and the Chung-Li VHF radar for combined precipitation observation, and the rain rate and the polarization difference shows a good positive correlation in the case of convective precipitation. Also, the polarization difference data can be used to judge whether the environment is convective precipitation at that time. In addition, the analysis results also found that the strong updraft associated with convective precipitation may cause supercooled water droplets collide with ice crystals and adhere to it, which could lead to radar echo power and spectrum width reduction. The results show that joint observation has great potential for understanding the cloud-physical mechanism of the formation of severe precipitation systems. |
