台灣位於歐亞大陸與西太平洋之交界，四面環海，地形複雜，對於定量降水估計與數值天氣預報無疑是一大挑戰，廣大洋面上觀測資料的不足，造成模式初始資料的誤差，再加上物理過程的不確定性及複雜地形可能引發的中、小尺度天氣現象等，都造成數值模式在進行定量降水預報時產生較大的誤差。本計畫一方面利用地面雨滴譜儀與垂直相剖風雷達，結合移動式雙偏極化雷達來改進易受災地區梅雨季與颱風季定量降水估計與預報技術，另一方面將以WRF 3DVAR 之三維變分同化方法，進行梅雨季傳統的地面、探空以及非傳統資料如雷達，特別是移動式雷達和福衛三號GPS RO 等資料同化的預報系統，來評估設計不同資料的同化程序與組合，對易受災地區定量降水預報之影響。其次搭配SOWMEX / TIMREX 等梅雨季西南氣流實驗之規劃與執行，本計畫也將進行「西南氣流觀測實驗」觀測資料之分析與即時同化預報模擬，以改進易受災地區的定量降水預報。本研究的第一年將持續以TIMREX/SOWMEX以及2009-2010 梅雨實驗期間佈置在台灣西南部地區的四部撞擊式雨滴譜儀以及一部光學式的二維視訊雨滴譜長期觀測資料，搭配雷達，特別是NCAR S-pol 與移動式X-band 之TEAM-R 雙偏極化雷達與垂直剖風儀雷達的觀測來統計分析台灣地區梅雨季節不同降水型態下的雨滴粒徑分布與變化特性。統計分析各種降雨參數之間的關係，特別是降雨率與回波，降雨率與雨滴粒徑分布關係之變化特性，據此改進易受災地區的定量降水估計，同時在每年梅雨季進行 WRF 中尺度模式的三維變分同化探空與雷達資料的模式模擬與預報。本研究計畫的第二年除了延續第一年的研究項目之外，擬藉由雨滴譜的觀測，配合雙偏極化都卜勒雷達資料，解析降水凝結物之下降速度以及雨滴粒徑分布，並以定點地面雨滴譜儀結合UHF 雷達對雨滴粒徑分布的觀測計算之降水參數R、Z，作為雷達觀測資料之Z-R 關係的驗證，以期建立雷達雨量估計Z-R 關係式，計算gamma- fitted parameter，尋求參數分布型態與雨雲間之關聯性，以改進梅雨期之定量降水估計技術，並針對不同降雨型態進行分類探討。同時持續進行梅雨期WRF 模式的三維變分資料同化的即時天氣預報，檢驗結合模式與觀測資料同化的定量降水預報的能力。由於S-pol 與TEAM-R 兩部雙偏極化雷達，均可以提供除了回波與徑向速度之外的雙偏極化雷達參數，本計劃將用這些雙偏極化參數來反演降雨率，反演之方法包括先反演雨滴粒徑分布再反推降雨率，和直接使用經驗公式由雙偏極化參數直接反求降雨率並以地面雨量站網進行驗證和比較。並提供模式預報與模擬驗證之用。 Taiwan is located in the borderline between the Asia continent and the Pacific Ocean. Its unique complex terrain and island characteristics present a great challenge to numerical weather prediction. The lack of observation over the surrounding ocean, the uncertainties on the model physics, and the mesoscale and microscale weather phenomena that result from the modification of synoptic scale flow by complex terrain could significantly downgrade the accuracy of a numerical simulation. Therefore, we will use ensemble forecast, by running many ensemble members with different settings, in an attempt to reduce the aforementioned uncertainties of the model. In the past several years, we already established a mesoscale numerical weather prediction network for Taiwan area. It will consist of several ensemble members that are individually maintained by universities. The universities have the responsibility to produce daily weather forecasts and send them to the Central Weather Bureau (CWB). These products will provide more guidance for forecasters in the CWB and set up an ensemble system for the short-range weather forecast. In this project we will develop WRF 3DVAR procedure to assimilate the traditional surface and sounding data and the non-traditional radar, satellite and GPS data to access the impact of those data assimilation on the quantity precipitation forecasting. Measurements of the drop size distribution (DSD) have a broad range of applications in meteorology, hydrology and related sciences. In particular accurate estimate of a real rainfall through radar measurements. Benefit from the knowledge of the drop size distribution. The use of radar to make quantity precipitation estimate (QPE) requires a rela tionship between its measured reflectivity Z and the estimated rainfall. Such a relationship, Known as Z-R, can be derived from long term observations of DSD using disdrometers. In this project, the drop size distribution will be observed by a disdrometer network (four impact disdrometers and one 2-D Video disdrometers) during TIMREX/SOWMEX period in south-western Taiwan will be classified and analyzed. The distribution of DSDs in time and space in Mei-yu season will be discussed. The DSD data will be used directly to derive the Z-R relation through the Gamma distribution fit of DSD. The radar reflectivity field will be used to compared to the reflectivity calculated from the observed distribution of DSD will also be discussed in this project. S-pol radar and TEAM dual-polarization radar can be used to retrieve the DSD from the polarimetric variables, it also can provide more correct rainfall estimate than the Doppler weather radar. The main goal of this project is to develop the optimum rainfall algorithm by using the disdrometers and polarimetric radar observation from TIMREX/SOWMEX field campaign. 研究期間：9908 ~ 10007
