博碩士論文 102022005 詳細資訊




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姓名 陳恩浩(hao)  查詢紙本館藏   畢業系所 遙測科技碩士學位學程
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)
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摘要(中) 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)。
摘要(英) 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).
關鍵字(中) ★ 深對流系統
★ 深對流核心結構
★ 動力環境特徵
關鍵字(英) ★ DCS
★ DCC Structure
★ Characteristics of Dynamical Environment
論文目次 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
參考文獻 [1] Anber, U., S. Wang, and A. Sobel, 2014: Response of Atmospheric Convection to Vertical Wind Shear: Cloud-System-Resolving Simulations with Parameterized Large-Scale Circulation. Part I: Specified Radiative Cooling. Journal of the Atmospheric Sciences, 71, 2976-2993.
[2] Arakawa, A., 2004: The Cumulus Parameterization Problem: Past, Present, and Future. Journal of Climate, 17, 2493-2525.
[3] Bony, S., J.-L. Dufresne, H. Le Treut, J.-J. Morcrette, and C. Senior, 2004: On dynamic and thermodynamic components of cloud changes. Climate Dynamics, 22, 71-86.
[4] Bony, S., K.-M. Lau, and Y. C. Sud, 1997: Sea Surface Temperature and Large-Scale Circulation Influences on Tropical Greenhouse Effect and Cloud Radiative Forcing. Journal of Climate, 10, 2055-2077.
[5] Byers, H. R., and L. J. Battan, 1949a: Some Effects of Vertical Wind Shear on Thunderstorm Structure. Bulletin of the American Meteorological Society, 30, 168-175.
[6] Byers, H. R., and L. J. Battan, 1949b: Some effects of vertical wind shear on thunderstorm structure. Bulletin of the American Meteorological Society, 168-175.
[7] Cecil, D. J., S. J. Goodman, D. J. Boccippio, E. J. Zipser, and S. W. Nesbitt, 2005: Three Years of TRMM Precipitation Features. Part I: Radar, Radiometric, and Lightning Characteristics. Monthly Weather Review, 133, 543-566.
[8] Chen, Q., J. Fan, S. Hagos, W. I. Gustafson, and L. K. Berg, 2015: Roles of wind shear at different vertical levels: Cloud system organization and properties. Journal of Geophysical Research: Atmospheres, 120, 6551-6574.
[9] Cifelli, R., W. A. Petersen, L. D. Carey, S. A. Rutledge, and M. A. F. da Silva Dias, 2002: Radar observations of the kinematic, microphysical, and precipitation characteristics of two MCSs in TRMM LBA. Journal of Geophysical Research: Atmospheres, 107, LBA 44-41-LBA 44-16.
[10] CIRA, 2008: CloudSat Standard Data Products Handbook. Cooperative Institute for Research in the Atmosphere, Colorado State University.
[11] Coniglio, M. C., and D. J. Stensrud, 2001: Simulation of a Progressive Derecho Using Composite Initial Conditions. Monthly Weather Review, 129, 1593-1616.
[12] Dee, D. P., and Coauthors, 2011: The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Quarterly Journal of the Royal Meteorological Society, 137, 553-597.
[13] Del Genio, A. D., A. B. Wolf, and M. S. Yao, 2005: Evaluation of regional cloud feedbacks using single-column models. Journal of Geophysical Research: Atmospheres, 110.
[14] DeMott, C. A., and S. A. Rutledge, 1998: The Vertical Structure of TOGA COARE Convection. Part I: Radar Echo Distributions. Journal of the Atmospheric Sciences, 55, 2730-2747.
[15] Dodson, J. B., D. A. Randall, and K. Suzuki, 2013: Comparison of observed and simulated tropical cumuliform clouds by CloudSat and NICAM. Journal of Geophysical Research: Atmospheres, 118, 1852-1867.
[16] Fan, J., and Coauthors, 2009: Dominant role by vertical wind shear in regulating aerosol effects on deep convective clouds. Journal of Geophysical Research, 114.
[17] Feng, Z., X. Dong, B. Xi, C. Schumacher, P. Minnis, and M. Khaiyer, 2011: Top-of-atmosphere radiation budget of convective core/stratiform rain and anvil clouds from deep convective systems. Journal of Geophysical Research: Atmospheres, 116, n/a-n/a.
[18] Ferrier, B. S., J. Simpson, and W.-K. Tao, 1996: Factors Responsible for Precipitation Efficiencies in Midlatitude and Tropical Squall Simulations. Monthly Weather Review, 124, 2100-2125.
[19] Garstang, M., and A. K. Betts, 1974: a review of the tropical boundary layer and cumulus convection: structure, parameterization, and modeling. Bulletin of the American Meteorological Society, 55, 1195-1205.
[20] Halverson, J. B., B. S. Ferrier, T. M. Rickenbach, J. Simpson, and W.-K. Tao, 1999: An Ensemble of Convective Systems on 11 February 1993 during TOGA COARE:Morphology, Rainfall Characteristics, and Anvil Cloud Interactions. Monthly Weather Review, 127, 1208-1228.
[21] Haynes, J. M., T. S. L′Ecuyer, G. L. Stephens, S. D. Miller, C. Mitrescu, N. B. Wood, and S. Tanelli, 2009: Rainfall retrieval over the ocean with spaceborne W-band radar. Journal of Geophysical Research: Atmospheres, 114, n/a-n/a.
[22] Haynes, J. M., and G. L. Stephens, 2007: Tropical oceanic cloudiness and the incidence of precipitation: Early results from CloudSat. Geophysical Research Letters, 34.
[23] Heymsfield, G. M., J. M. Shepherd, S. W. Bidwell, W. C. Boncyk, I. J. Caylor, S. Ameen, and W. S. Olson, 1996: Structure of Florida Thunderstorms Using High-Altitude Aircraft Radiometer and Radar Observations. Journal of Applied Meteorology, 35, 1736-1762.
[24] Houze, R. A., Jr., 2004: Mesoscale convective systems. Reviews of Geophysics, 42.
[25] Igel, M. R., and S. C. van den Heever, 2015a: The relative influence of environmental characteristics on tropical deep convective morphology as observed by CloudSat. Journal of Geophysical Research: Atmospheres, 120, 4304-4322.
[26] Igel, M. R., and S. C. van den Heever, 2015b: Tropical, oceanic, deep convective cloud morphology as observed by CloudSat. Atmospheric Chemistry and Physics Discussions, 15, 15977-16017.
[27] Im, E., C. Wu, and S. L. Durden, 2005: Cloud profiling radar for the CloudSat mission. IEEE Aerospace and Electronic Systems Magazine, 20, 15-18.
[28] Kubar, T. L., D. E. Waliser, and J. L. Li, 2011: Boundary Layer and Cloud Structure Controls on Tropical Low Cloud Cover Using A-Train Satellite Data and ECMWF Analyses. Journal of Climate, 24, 194-215.
[29] Kubota, H., A. Numaguti, and S. Emori, 2004: Numerical Experiments Examining the Mechanism of Diurnal Variation of Tropical Convection. Journal of the Meteorological Society of Japan. Ser. II, 82, 1245-1260.
[30] Liu, C., and M. W. Moncrieff, 2001: Cumulus Ensembles in Shear: Implications for Parameterization. Journal of the Atmospheric Sciences, 58, 2832-2842.
[31] Liu, C., E. J. Zipser, and S. W. Nesbitt, 2007: Global Distribution of Tropical Deep Convection: Different Perspectives from TRMM Infrared and Radar Data. Journal of Climate, 20, 489-503.
[32] Luo, Y., R. Zhang, W. Qian, Z. Luo, and X. Hu, 2011: Intercomparison of Deep Convection over the Tibetan Plateau–Asian Monsoon Region and Subtropical North America in Boreal Summer UsingCloudSat/CALIPSO Data. Journal of Climate, 24, 2164-2177.
[33] Luo, Z., G. Y. Liu, and G. L. Stephens, 2008: CloudSat adding new insight into tropical penetrating convection. Geophysical Research Letters, 35.
[34] Luo, Z. J., J. Jeyaratnam, S. Iwasaki, H. Takahashi, and R. Anderson, 2014: Convective vertical velocity and cloud internal vertical structure: An A-Train perspective. Geophysical Research Letters, 41, 723-729.
[35] Machado, L. A. T., and H. Laurent, 2004: The Convective System Area Expansion over Amazonia and Its Relationships with Convective System Life Duration and High-Level Wind Divergence. Monthly Weather Review, 132, 714-725.
[36] Mapes, B. E., and R. A. Houze, Jr., 1993: Cloud Clusters and Superclusters over the Oceanic Warm Pool. Monthly Weather Review, 121, 1398-1416.
[37] Marchand, R., G. G. Mace, T. Ackerman, and G. Stephens, 2008: Hydrometeor Detection UsingCloudsat—An Earth-Orbiting 94-GHz Cloud Radar. Journal of Atmospheric and Oceanic Technology, 25, 519-533.
[38] Mohr, K. I., and E. J. Zipser, 1996: Defining Mesoscale Convective Systems by Their 85-GHz Ice-Scattering Signatures. Bulletin of the American Meteorological Society, 77, 1179-1190.
[39] Moncrieff, M. W., 1997: Momentum Transport by Organized Convection. The Physics and Parameterization of Moist Atmospheric Convection, R. K. Smith, Ed., Springer Netherlands, 231-253.
[40] Neale, R., and J. Slingo, 2003: The Maritime Continent and Its Role in the Global Climate: A GCM Study. Journal of Climate, 16, 834-848.
[41] Qian, J.-H., 2008: Why Precipitation Is Mostly Concentrated over Islands in the Maritime Continent. Journal of the Atmospheric Sciences, 65, 1428-1441.
[42] Randall, D. A., M. Khairoutdinov, A. Arakawa, and W. Grabowski, 2003: Breaking the Cloud Parameterization Deadlock. Bulletin of the American Meteorological Society, 84, 1547-1564.
[43] Randall, D. A., and Coauthors, 2007: Climate models and their evaluation. Climate change 2007: The physical science basis. Contribution of Working Group I to the Fourth Assessment Report of the IPCC (FAR), Cambridge University Press, 589-662.
[44] Richardson, Y. P., K. K. Droegemeier, and R. P. Davies-Jones, 2007: The influence of horizontal environmental variability on numerically simulated convective storms. Part I: Variations in vertical shear. Monthly Weather Review, 135, 3429-3455.
[45] Rickenbach, T., and Coauthors, 2008: The Relationship between Anvil Clouds and Convective Cells: A Case Study in South Florida during CRYSTAL-FACE. Monthly Weather Review, 136, 3917-3932.
[46] Riehl, H., and J. S. Malkus, 1958: On the Heat Balance in the Equatorial Trough Zone. Geophysica, 6, 503–537.
[47] Robe, F. R., and K. A. Emanuel, 2001: The Effect of Vertical Wind Shear on Radiative–Convective Equilibrium States. Journal of the Atmospheric Sciences, 58, 1427-1445.
[48] Rotunno, R., J. B. Klemp, and M. L. Weisman, 1988: A Theory for Strong, Long-Lived Squall Lines. Journal of the Atmospheric Sciences, 45, 463-485.
[49] Saxen, T. R., and S. A. Rutledge, 2000: Surface Rainfall–Cold Cloud Fractional Coverage Relationship in TOGA COARE: A Function of Vertical Wind Shear. Monthly Weather Review, 128, 407-415.
[50] Schmetz, J., K. Holmlund, M. Koenig, and H.-J. Lutz, 2018: OBSERVATION OF THE DIURNAL VARIATION OF UPPER TROPOSPHERIC DIVERGENCE IN A TROPICAL CONVECTIVE SYSTEM.
[51] Soden, B. J., and R. Fu, 1995: A Satellite Analysis of Deep Convection, Upper-Tropospheric Humidity, and the Greenhouse Effect. Journal of Climate, 8, 2333-2351.
[52] Stephens, G. L., and Coauthors, 2008a: CloudSat mission: Performance and early science after the first year of operation. Journal of Geophysical Research: Atmospheres, 113.
[53] Stephens, G. L., and Coauthors, 2008b: CloudSat mission: Performance and early science after the first year of operation. Journal of Geophysical Research, 113.
[54] Stephens, G. L., and N. B. Wood, 2007: Properties of Tropical Convection Observed by Millimeter-Wave Radar Systems. Monthly Weather Review, 135, 821-842.
[55] Takemi, T., 2007: A sensitivity of squall-line intensity to environmental static stability under various shear and moisture conditions. Atmospheric research, 84, 374-389.
[56] Tao, S. Y., 1987: A review of recent research on the East Asian summer monsoon in China. Monsoon Meteorology, 60-92.
[57] Tian, B., G. J. Zhang, and V. Ramanathan, 2001: Heat Balance in the Pacific Warm Pool Atmosphere during TOGA COARE and CEPEX. Journal of Climate, 14, 1881-1893.
[58] Weisman, M. L., J. B. Klemp, and R. Rotunno, 1988: Structure and Evolution of Numerically Simulated Squall Lines. Journal of the Atmospheric Sciences, 45, 1990-2013.
[59] Yuter, S. E., and R. A. Houze, 1998: The natural variability of precipitating clouds over the western Pacific warm pool. Quarterly Journal of the Royal Meteorological Society, 124, 53-99.
[60] Yuter, S. E., and R. A. H. Jr., 1995: Three-Dimensional Kinematic and Microphysical Evolution of Florida Cumulonimbus. Part II: Frequency Distributions of Vertical Velocity, Reflectivity, and Differential Reflectivity. Monthly Weather Review, 123, 1941-1963.
[61] Zelinka, M. D., and D. L. Hartmann, 2009: Response of Humidity and Clouds to Tropical Deep Convection. Journal of Climate, 22, 2389-2404.
指導教授 劉千義(Chian-Yi Liu) 審核日期 2019-1-30
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