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姓名 陳立昕(Li-Hsin Chen)  查詢紙本館藏   畢業系所 大氣科學學系
論文名稱 利用系集法估計與檢驗對流尺度之預報誤差:SoWMEX IOP8 個案分析
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摘要(中) 本研究採用系集法(Ensemble-based method),首次在台灣藉由天氣個案模擬,針對
對流尺度之預報誤差結構進行分析,個案選取 2008 年西南氣流聯合觀測實驗
(SoWMEX IOP8)期間,於 06 月 15 至 16 日之間生成之中尺度對流系統(Mesoscale
Convective Systems, MCSs),使用 WRF 單向巢狀網格,高解析度(3-km)之網格涵蓋台
灣本島與台灣海峽,以及部分巴士海峽。以 72 組系集預報結果作為樣本,運用統計方
法估算出背景(預報)誤差協方差(Background Error Covariance),其提供我們瞭解系集卡
爾曼濾波器(EnKF),在同化應用上之索引,藉此推斷觀測資料在同化期間,資訊導入
與傳遞的情況。
在 MCSs 影響期間,比較不同解析度(9, 3-km)之誤差結構,顯示高解析度的方差
量值較大,特別是垂直速度有最顯著的差異,高解析度能夠顯現較小尺度的不確定性。
在方差的時間序列中,方差隨著降雨率的強度增強而增加,降雨率減弱而趨緩。水平
風的方差結構中,擁有多重尺度作用的複雜結構,較小尺度的不確定性是由濕對流過
程(moist processes)產生;此外,降雨過程產生的冷池影響近地表溫度的方差。本研究
同時探討時間與空間上的誤差相關性,其亦受到濕對流過程影響。在交相關的部分,
溫度與垂直速度之正相關結構與潛熱釋放有關,低層之水平風 U 與 V,在台灣西南部
出現負相關之特徵,為西南氣流與地形交互作用產生。本研究對於預報誤差結構的評
估,期望能夠提供資料同化有利的策略,進而改進台灣地區雷達資料同化能力。
摘要(英) This study focus on the short-term forecast error structures with different resolution (9/
3 km) at meso- and convective scales. With a set of 72-member ensemble forecasts by
Weather Research and Forecasting (WRF) model, the error covariances are presented. A case
study during Southwest Monsoon Experiment intensive observing period 8 (SoWMEX-IOP8)
in 2008 is investigated. The characteristics of forecast error covariances are examined by the
spread and error correlation in state variables.
Compared with different resolution, the variance of state variables are larger in higher
resolution, particularly in vertical velocity. It indicates higher resolution run (3-km) can
better-represent the smaller scale uncertainties in this severe weather event. The time-series
of ensemble spread reveal that significant variances are associated with the strength of rainfall
rate. In the magnitude of horizontal wind, multi-scale interactions are found over the
southwesterly flow region. The temperature near surface has relatively large quantity of
variance in association with cold pool performances. Moist processes not only impact on the
distribution of variance, but paly important role of error correlation in temporal and spatial
structure. The cross correlation of the temperature and vertical velocity is strongly positive at
high level dominated by latent heat release. The negative cross correlation between zonal and
meridional wind over southwest quadrant of Taiwan illustrates the range affected by
orography. The information of forecast error provides optimal strategies of data assimilation,
especially for assimilating radar network over Taiwan area.
關鍵字(中) ★ 預報誤差協方差
★ 中尺度對流系統
關鍵字(英) ★ Forecast Error Covariance
★ Mesoscale Convective Systems
論文目次 目錄

摘要 i
Abstract ii
致謝 iii
目錄 iv
圖表目錄 vii
第一章 緒論 1
1-1 前言 1
1-2 文獻回顧 2
1-3 研究目的 4
第二章 研究方法 5
2-1 資料同化之基本概念 5
2-1-1 原理介紹 5
2-1-2 誤差協方差之重要性說明 7
2-2 預報誤差之評估方法 8
2-2-1 方差 8 v

2-2-2 誤差相關係數 9
2-3 模式系統 9
2-4 初始系集之取得 10
第三章 個案概述 12
3-1 綜觀天氣分析 12
3-2 中尺度對流系統(Mesoscale Convective Systems, MCSs) 13
第四章 預報誤差結構分析 14
4-1 降雨模擬結果 14
4-2 方差結構 15
4-2-1 動力與熱力變數(水平風速、垂直速度、溫度與比濕) 15
4-2-2 水象變數( ??、??、??、?? 與 ?? ) 19
4-3 誤差相關性之結構 20
4-3-1 降雨、非降雨與層狀降雨區自相關比較 20
4-3-2 時間延遲自相關性 21
4-3-3 溫度誤差自相關性之垂直分布 21
4-3-4 雨水混合比誤差相關性 22
4-3-5 誤差交相關(cross correlation) 22 4-4 對流尺度預報誤差與資料同化效益之探討 23
第五章 總結與未來展望 25
5-1 總結 25
5-2 未來展望 26
參考文獻 27
附錄 32
I 卡爾曼濾波器 32
II 系集卡爾曼濾波器 33
III 局地化系集轉換卡爾曼濾波器 33
附表 36
附圖 37
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指導教授 鍾高陞(Kao-Shen Chung) 審核日期 2017-8-23
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