統計分析2008年西南氣流實驗期間對流系統的雙偏極化雷達拉格朗日特徵

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葉玉婕(Yu-Chieh Yeh) 查詢紙本館藏

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大氣科學學系

論文名稱

統計分析2008年西南氣流實驗期間對流系統的雙偏極化雷達拉格朗日特徵
(Statistical Analysis of Dual-Polarization Parameter Lagrangian Features of Convective Storms During SoWMEX/TiMREX)

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摘要(中)

西南氣流伴隨梅雨鋒面不僅能為台灣帶來豐沛的降水量，過多的雨水也會帶來致災的風險。本篇研究希望透過了解對流在結構上的變化、動力場的特徵及微物理過程的演化，診斷出對流胞當時的發展特徵，進一步分析這些過程隨時間上的表現。而要做到上述事情，必須仰賴對流胞辨識與追蹤技術，「SMART 」 (Storm Motion Analysis by Radar Tracking) 就此誕生。本篇研究收集了2008年西南氣流聯合觀測實驗中，NCAR SPOL 所提供的雷達雙偏參數資料，透過給定回波門檻與面積門檻來進行對流胞的辨識。研究中利用兩個不同的回波門檻，針對相同的降水事件，定義出兩種對流胞範圍。低回波門檻辨識出的對流胞稱為「parent-cell」，用以選取整個系統的降水範圍；高回波門檻辨識出的對流胞稱為「child-cell」，用來找出對流胞的核心區域。針對兩種辨識結果，皆能計算出如下的對流胞特徵：幾何中心(X, Y)、回波權重中心(??, ??)、面積(A)、長軸與短軸(?1 與 ?2)、方向性(θ)以及該對流胞範圍內的雙偏參數(DPM)。因此，隨著對流胞的移動，這些特性將得到進一步的檢驗。
本研究透過38個個案統計與5個個案分析的結果，定量上的探討雙偏參數在水平及垂直上的分離現象與特徵。其結果指出，當對流胞發展至成熟階段，雙偏參數在水平方向會有顯著的 ZDR 與 KDP 分離現象。而從垂直分離趨勢可知，當對流胞從發展至成熟階段，雙偏參數會出現正轉負的分離趨勢；反之，當對流胞從成熟至消散階段，則會出現負轉正的分離趨勢。透過趨勢上的轉換，更能幫助我們了解其雙偏參數隨對流胞發展至不同階段的特徵。本研究分析結果顯示了利用雙偏極化參數診斷對流胞發展的潛力。

摘要(英)

The mesoscale convective systems (MCSs) associated with East Asia summer south-westly monsoon and Mei-Yu front play essential role in contributing heavy precipitation in Taiwan. A storm identification and tracking technique (SMART: Storm Motion Analysis by Radar Tracking) using radar data was applied to investigate various characteristics of structural evolutions, dynamic, microphysics processes of these precipitation systems. The NCAR SPOL data during SoWMEX/TiMREX was analyzed to derived the storm characteristics. Storms were identified by considering two reflectivity threshold values. Lower reflectivity threshold value reveals entire precipitation system. On the other hand, the higher reflectivity threshold value locates the core of the convective system. The dual-reflectivity threshold technique distinguishes ‘child-cell’ (convective core zone) from ‘parent-cell’ (complete precipitation area). After identifying child-cell and parent-cell, the storm properties including geometric centroid (X, Y), reflectivity-weighted centroid (??, ??), size (A), major and minor axes (?1 ??? ?2), orientation of the major axes relative to the x axis (θ) and dual-polarimetric parameters within the storm area are analyzed. In addition, microphysical characteristics of convective system are investigated by the vertical slop and horizontal separation distance of various dual-polarimetric measurements (DPMs). These properties thus are examined with the evolution of the storm track.
There are 38 cases selected for statistical analysis and 5 cases selected for detailed case study. Both horizontal and vertical microphysics characteristics are analyzed quantitatively. The tendency of vertical slope of dual-polarimetric parameters vary from positive to negative values during the developing stage of the storm. Subsequently, the tendency varies from negative to positive during dissipating stage. The analysis has shown the potential of diagnosing the storm development by utilizing dual-polarimetric parameters. Furthermore, pronounced horizontal separation distance between ZDR and KDP centers can be noticed during mature state of the storm. As the result shows, the separation distance has high correlation to the mid-level wind condition (6 km).

關鍵字(中)

★ 雙偏極化雷達
★ 對流胞辨識
★ 對流胞追蹤

關鍵字(英)

★ Dual-Polarization Parameter
★ Storm identification
★ Storm tracking

論文目次

摘要 vii
Abstract viii
Acknowledgment x
Outline xii
List of Table xiv
List of Figures xv
Chapter 1 Introduction 1
1.1 Motivation 1
1.2 Literature Review 2
1.3 Research Purposes 6
1.4 Paper Structure 6
Chapter 2 Data and Methodology 7
2.1 International Field Campaign 7
2.2 Reanalysis dataset 8
2.3 Storm Identification and Tracking System 8
2.3.1 Radar Data Processing 9
2.3.2 2-Dimensional and 3-Dimensional Storm Identification 10
2.3.3 Storm Properties 12
2.3.4 2-Dimensional Moment Invariants 13
2.3.5 2-Dimensional Storm Tracking Methodology 15
2.4 Dual-Polarimetric Parameters 17
Chapter 3 Results and Discussions 21
3.1 Overview of SoWMEX SPOL Observations 21
3.2 Case analysis 22
3.2.1 Statistical Characteristics of 38 Cases 24
3.2.2 Horizontal Separation Discussion – 5 Cases 31
3.2.2.1 Weak Case 1 (case number 22) 33
3.2.2.2 Weak Case 2 (case number 20) 34
3.2.2.3 Moderate Case (case number 34) 35
3.2.2.4 Strong Case 1 (case number 29) 36
3.2.2.5 Strong Case 2 (case number 30) 38
3.3 Statistical Performance of Motion Vectors 39
Chapter 4 Conclusions and Future Works 41
4.1 Conclusions 41
4.2 Future Works 43
References 44
Tables 48
Figures 51
Appendix 90

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指導教授

張偉裕(Wei-Yu Chang)

審核日期

2021-8-25

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