四維變分都卜勒雷達分析系統於複雜地形之定量降雨預報研究

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Title:	四維變分都卜勒雷達分析系統於複雜地形之定量降雨預報研究
Authors:	廖宇慶
Contributors:	國立中央大學大氣科學學系
Keywords:	大氣科學;氣象雷達;資料同化;四維變分;沉浸邊界法(IBM);都卜勒雷達變分分析系統(VDRAS);Variational Doppler Radar Analysis System;Immersed Boundary Method;4DVAR
Date:	2013-05-01
Issue Date:	2013-05-07 15:53:22 (UTC+8)
Publisher:	交通部中央氣象局
Abstract:	台灣因為其特殊的地理位置與地形條件，使得針對劇烈天氣的定量降雨預報十分具有挑戰性。目前全台有九部陸基式氣象雷達，以及一部研究用的移動式雙偏極化都卜勒雷達，在未來的3年內還會再建置4部雷達，如何能最佳化利用這些大量的雷達資料，以提升數值模式對降雨預報的精確度，是一兼具學術研究與作業應用價值的課題。本研究以四維變分同化技術為研究方法，即使用Variational Doppler Radar Analysis System (VDRAS) 為主要的運算平臺。VDRAS近來已有多個成功的應用案例，如:2000年澳洲雪梨奧運(Crook and Sun 2002)、在STEPS實驗預報雷暴的應用(Sun 2005)、IHOP實驗預報颮線的應用(Sun and Zhang 2008)、污染物擴散的研究(Warner et al. 2007)及2008年北京奧運會即時預報作業的應用(Sun et.al. 2010)等。由此可知，VDRAS已是一個發展相當成熟的雷達資料同化、分析與預報系統。但目前VDRAS使用笛卡爾(Cartesian)直角座標系統，無法處理台灣複雜的地形。為了使VDRAS能應用於台灣地區之定量降水預報，Tai et al.(2011)發現如將VDRAS的分析場與WRF模式結合，利用後者處理地形的能力，可提升單獨使用VDRAS或WRF的預報能力。然而，最根本的解決方法是讓VDRAS具有直接在地形上進行運算的能力。因此，本研究擬利用沉浸邊界法(Immersed Boundary Method)，在不修改座標系統的條件下，加入地形效應的影響。未來VDRAS將可以直接在地形上進行同化雷達資料與預報的運算，建立一套適合於台灣與鄰近區域地理、氣象、與觀測條件的短期(0~3小時)定量降水預報方案。 ; Due to the particular geography and topography, the quantitative precipitation forecast (QPF) of severe weather in Taiwan becomes much more challenging. Currently, there are nine ground based weather radars around the island and also one mobile dual-polarimetric doppler radar in service. Therefore, it will be a significant issue related with both research and operation that how to optimally use those numerous radar data to further improve the performance of precipitation forecast in Taiwan. The tool used in this project is Variational Doppler Radar Analysis System (VDRAS), which assimilates radar data by four-dimensional variational data assimilation（4DVAR）technique. Many successful applications done by VDRAS were already shown including nowcasting in Sydney Olympic Games (Crook and Sun, 2002), forecast of thunderstorm in STEPS field experiment (Sun, 2005), Squall line forecasting in IHOP experiment (Sun and Zhang, 2008), the Pentagon shield field program (Warner et al., 2007) and nowcasting for Beijing Olympic Games (Sun et.al., 2010). From the above, VDRAS has become a mature and robust system. However, it couldn’t resolve terrain effect by its cloud model even now. In order to apply VDRAS to QPF in Taiwan, Tai et. al (2011) found reinitialize the WRF by VDRAS analysis and then forecast by WRF model could improve the performance of short-term QPF. But it would be better VDRAS can analyze with terrain effect. In this case, we try to apply immersed boundary method to construct the ability of resolving terrain effects without modifying coordinates. In the future, VDRAS can assimilate radar data and forecast in complex terrain areas like Taiwan to provide a more suitable plan for short-term QPF (0 to 3 hours). ; 研究期間 10203 ~ 10212
Relation:	財團法人國家實驗研究院科技政策研究與資訊中心
Appears in Collections:	[Department of Atmospheric Sciences] Research Project

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