| DC 欄位 |
值 |
語言 |
| DC.contributor | 大氣物理研究所 | zh_TW |
| DC.creator | 郭閔超 | zh_TW |
| DC.creator | Min-Chao Kuo | en_US |
| dc.date.accessioned | 2011-7-6T07:39:07Z | |
| dc.date.available | 2011-7-6T07:39:07Z | |
| dc.date.issued | 2011 | |
| dc.identifier.uri | http://ir.lib.ncu.edu.tw:88/thesis/view_etd.asp?URN=986201003 | |
| dc.contributor.department | 大氣物理研究所 | zh_TW |
| DC.description | 國立中央大學 | zh_TW |
| DC.description | National Central University | en_US |
| dc.description.abstract | 本研究使用都卜勒雷達變分分析系統(Variational Doppler Radar Analysis System；VDRAS)進行雷達資料同化，VDRAS具有預報能力，但不能解析地形，因此以VDRAS透過4DVAR同化雷達資料後的分析場作為模式初始場，再結合有地形解析能力的WRF ，進行預報。本研究同化七股、墾丁、花蓮及SPOL雷達，且設計多組不同的同化策略，以檢視VDRAS結合WRF後對改進降水預報的程度。
本研究選取的個案為2008年SoWMEX(Southwest Monsoon Experiment；西南氣流實驗)期間IOP4(Intensive Observation Period 4；第四次密集觀測期)的6月2日。主要的實驗結果，發現同化四個雷達(同化SPOL雷達)比同化三個雷達(未同化SPOL雷達)的降水預報結果還要好。在降水預報上，同化雷達資料比純粹WRF的模擬結果有明顯改進，而再同化0600~0700UTC雷達資料並置換第二次VDRAS分析場，其結果較好。但是若同化0500~0600UTC雷達資料(天氣系統仍在海上)比同化0700~0800UTC雷達資料(天氣系統已登陸)，結果則較好，因此吾人認為0750~0800UTC，強度30dBZ以上的雷達觀測回波在複雜地形上的資料量比0550~0600和0650~0700來的多，而VDRAS無地形解析能力，同化天氣系統已登陸的雷達資料相較於同化天氣系統在海上時的VDRAS分析場，較無法掌握複雜地形上對流結構的特徵。
綜合以上各種同化策略，說明了VDRAS在台灣或類似其地理及觀測環境的可行性，以供日後研究參考。
| zh_TW |
| dc.description.abstract | In this research, the Variational Doppler Radar Analysis System (VDRAS) is used to assimilate radar data. The VDRAS has the capability to conduct forecast, but only over flat surface. Thus, it is attempted to merge the VDRAS analysis field with WRF, so that one can use the latter to resolve the terrain. In this study, we will use RCCG, RCKT, RCHL and S-POL radars to perform a series of assimilation experiments with different strategies.
A real case of a shallow surface front occurred from 0500UTC to 0900UTC on 02 June 2008 during Southwest Monsoon Experiment IOP4 is selected. Experimental results reveal that assimilating more radar data leads to a better performance of the rainfall forecast. It is also shown that assimilating radar data is better than using WRF alone. Further improvements can be achieved when WRF is merged with VDRAS analysis field twice. By assimilating radar data on 0500~0600UTC, when convective system is still over the ocean, results in a more accurate forecast of the rainfall than performing the radar data assimilation on 0700~0800UTC, when convective system already reaches the complex terrain. This difference can be explained in the following. Since a large portion of the convection system is over the terrain on 0700UTC~0800UTC, therefore even with radar data assimilation, the VDRAS is not able to capture the major features of the convective structure due to its inability to resolve the complex terrain.
The above-mentioned experimental results can be used as a guideline for applying VDRAS in Taiwan or other places with similar geographic environment and observational limitations.
| en_US |
| DC.subject | 天氣研究預報模式 | zh_TW |
| DC.subject | 四維變分 | zh_TW |
| DC.subject | 定量降水預報 | zh_TW |
| DC.subject | 都卜勒雷達 | zh_TW |
| DC.subject | WRF | en_US |
| DC.subject | 4DVAR | en_US |
| DC.subject | Quantitative Precipitation Forecast | en_US |
| DC.subject | VDRAS | en_US |
| DC.title | 結合VDRAS、WRF與雷達網聯資料，以檢視對台灣地區短期降水預報改善之成效 | zh_TW |
| dc.language.iso | zh-TW | zh-TW |
| DC.title | Improving short-range QPF in Taiwan by VDRAS and WRF using data from multiple weather radars. | en_US |
| DC.type | 博碩士論文 | zh_TW |
| DC.type | thesis | en_US |
| DC.publisher | National Central University | en_US |