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研究生： 陳恩浩
hao
論文名稱： 使用 CloudSat 分析南海與海洋大陸地區之深對 流與動力環境特徵
Characteristics of Deep Convections and Associated Dynamic Conditions from CloudSat over the South China Sea and Maritime Continent
指導教授： 劉千義
Chian-Yi Liu
口試委員:
學位類別： 碩士
Master
系所名稱： 太空及遙測研究中心 - 遙測科技碩士學位學程
Master of Science Program in Remote Sensing Science and Technology
論文出版年： 2019
畢業學年度： 107
語文別： 英文
論文頁數： 76
中文關鍵詞： 深對流系統 、深對流核心結構 、動力環境特徵
外文關鍵詞： DCS, DCC Structure, Characteristics of Dynamical Environment
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    • 深對流在全球氣候中扮演重要的角色，不但影響輻射收支平衡、水文循環，也將污染粒子、能量、水氣從邊界層傳輸至高層大氣，間接造成溫室效應。因此，本研究嘗試分析在南海與海洋大陸地區之十年(2007-2016) CloudSat衛星觀測與ERA-Interim資料，經由雷達回波特性定義出之深對流系統，進一步分析動力環境參數，進而探討深對流發生頻率、對流雲結構、動力環境參數特徵、時空間分佈特性，及彼此間的關係。
    結果顯示海洋大陸地區傾向有較多獨立對流系統(0.74%發生率)且對流頂端雲滴與雨滴粒子較大較密集(CTH-H_10dBZ: 3.43km)；南海區域則較多中尺度對流(0.88%發生率)且對流層頂端之粒子較小較分散(CTH-H_10dBZ: 3.77km)。系統水平跨幅、回波高度差、垂直速度、高層輻散(10-16 km)皆成正相關，尤其深對流核心對上升運動與高層輻散場具高度敏感性。小於20ms-1之垂直風切會使對流系統水平跨幅增大，有利中尺度系統之發展，大於20ms-1之垂直風切卻使對流雲的結構分散，降低獨立系統的發生。高度在十公里是一重要分界，垂直上升速度於此高度有最大值，且高層輻散也從十公里處開始。
    根據對流系統的海陸分布、日夜變化與垂直動力結構，我們推論對流系統主要有兩種不同的形成機制：邊界層在下午因地表加熱變得不穩定，小水平尺度的對流系統(S-type; <300km)容易形成，其最大的上升速度出現在中低層(2-8 km)，將大粒子抬升至對流核心上層，有較小的回波高度差(~3km)；邊界層在夜間和海洋上則因雲輻射冷卻使低層大氣不穩定，創造了淺對流發展成深對流有利的條件，小水平尺度或大水平尺度對流系統（L-type; >300km）能在這種情況下發展，其特徵在於具有較大的回波高度差(~4km)。

    Deep convection plays an important role in the global climate. It affects not only the balance of radiation and the hydrological cycle but also transports polluted particles, energy and moisture from the boundary layer to the upper atmosphere, which might link to the greenhouse effect. We conduct the analysis of CloudSat and ERA-Interim data from 2007 to 2016, to identify the deep convective systems (DCS) over the Maritime Continent (MC) and the South China Sea (SCS). The associated vertical structure, horizontal span, dynamic environmental factors, and spatial and temporal characteristics of deep convection were analyzed to seek the possible atmosphere dynamic controls of deep convection in the targeting regions.
    The results show that more isolated convective systems formed at MC (0.74% incidence) with more packed and larger particles at the upper-convective core (CTH-H_10dBZ: 3.43km). There are more organized convections formed over SCS (0.88% incidence) with more dispersed and smaller particles at the upper-convective core (CTH-H_10dBZ: 3.77km). The system horizontal span and echo height difference, rising velocity and the upper-level divergence are all positively correlated, especially, the deep convective core is highly sensitive to the ascending motion and the upper-level divergence (10-16 km). The vertical wind shear (VWS) less than 20ms-1 may increase the horizontal size of DCS, which is beneficial to the development of mesoscale systems. However, VWS over than 20ms-1 disperses the structure of the convective cloud, decreasing the occurrence frequency of the isolated system. Also, 10 km height is a critical threshold level, where the maximum vertical updraft velocity and the upper-level divergence.
    According to the land-sea distribution, diurnal variation and vertical dynamic structure of DCS, that there might be two different formation mechanisms for convective systems: 1) the boundary layer becomes unstable due to surface heating in the afternoon, and the isolated systems (S-type; <300km) are formed which characterized by small echo-top height difference (~3km) and strong lower-level (2-8 km) ascending motion which transports the large particles from the bottom to the upper level; 2) Boundary-layer cloud radiative cooling destabilizes the low-layer atmosphere, creating a favorable condition for shallow convection to develop to deep convection in the nighttime and over the ocean. Isolated or organized convective system （L-type; >300km） formed under this condition which characterizes with larger echo-top height differences (~4km).

    摘要 i Abstracts ii Table of Contents iv List of Tables vi List of Figures vii 1. Introduction 1 1.1. Deep Convection and Its Effects 1 1.2. Dynamic Environmental Factors Impacts on Deep Convection 2 1.3. Challenging of NWP Model at Cumulus Parameterization 3 1.4. Research Objective 4 2. Data and Methodology 6 2.1. Materials 6 2.1.1. CloudSat 2B-GEOPROF 7 2.1.2. ECMWF ERA-Interim 8 2.2. Targeting Domains 10 2.3. Data Process and Analysis 11 3. General Features of Deep Convection 15 3.1. Deep Convection Synoptic Feature 15 3.1.1. Deep Convection Incidence 15 3.1.2. Horizontal span of the deep convective systems 16 3.1.3. Vertical structure of deep convective core 17 3.2. Deep Convection Sensitivity to Dynamic Factors 18 3.2.1. Single-Variable Trends 19 3.2.2. Double-Variable Trends 23 3.3. Influence of Dynamic Parameters on Deep Convection Structure 24 3.3.1. Horizontal span of the deep convective systems and dynamic factors 24 3.3.2. Vertical structure of deep convective core and dynamic factors 26 4. Sensitivity of Deep Convective System 30 4.1. L/S-type DCS Sensitivity to Dynamic Factors 30 4.2. Diurnal variation of L/S-type DCS 33 4.2.1. Spatial distribution of L/S-type DCS in daytime and nighttime 33 4.2.2. Dynamic Properties and Vertical Structure of L/S-type DCS 34 5. Summary and Future work 37 Bibliography 41 Table 46 Figure 49

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