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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 陳正平(Jen-Ping Chen) | |
dc.contributor.author | Ting-Yu Chang | en |
dc.contributor.author | 張丁瑀 | zh_TW |
dc.date.accessioned | 2021-06-16T09:19:53Z | - |
dc.date.available | 2018-07-07 | |
dc.date.copyright | 2017-07-07 | |
dc.date.issued | 2017 | |
dc.date.submitted | 2017-07-04 | |
dc.identifier.citation | Allan, R. P., & Soden, B. J. (2008). Atmospheric Warming and the Amplification of Precipitation Extremes. Science, 321(5895), 1481-1484. doi: 10.1126/science.1160787
Austin, P.M. and R.A. Houze, 1972: Analysis of the Structure of Precipitation Patterns in New England. J. Appl. Meteor., 11, 926–935, https://doi.org/10.1175/1520-0450(1972)011<0926:AOTSOP>2.0.CO;2 Chen, J.-P., & Liu, S.-T. (2004). Physically based two-moment bulkwater parametrization for warm-cloud microphysics. Quarterly Journal of the Royal Meteorological Society, 130(596), 51-78. doi: 10.1256/qj.03.41 Chou, C., Neelin, J. D., Chen, C.-A., & Tu, J.-Y. (2009). Evaluating the “Rich-Get-Richer” Mechanism in Tropical Precipitation Change under Global Warming. Journal of Climate,22(8), 1982-2005. doi: 10.1175/2008jcli2471.1 Dai, A. (2006). Precipitation Characteristics in Eighteen Coupled Climate Models. Journal of Climate, 19(18), 4605-4630. doi: 10.1175/JCLI3884.1 Han, J.-Y., Hong, S.-Y., Lim, K.-S. S., & Han, J. (2016). Sensitivity of a Cumulus Parameterization Scheme to Precipitation Production Representation and Its Impact on a Heavy Rain Event over Korea. Monthly Weather Review, 144(6), 2125-2135. doi: 10.1175/mwr-d-15-0255.1 Scinocca, J. F., & McFarlane, N. A. (2004). The Variability of Modeled Tropical Precipitation. Journal of the Atmospheric Sciences, 61(16), 1993-2015. doi: 10.1175/1520-0469(2004)061 2.0.co;2 Kharin, V. V., Zwiers, F. W., Zhang, X., & Hegerl, G. C. (2007). Changes in Temperature and Precipitation Extremes in the IPCC Ensemble of Global Coupled Model Simulations. Journal of Climate, 20(8), 1419-1444. doi: 10.1175/jcli4066.1 Korolev, A. V., Isaac, G. A., Strapp, J. W., Cober, S. G., & Barker, H. W. (2007). In situ measurements of liquid water content profiles in midlatitude stratiform clouds. Quarterly Journal of the Royal Meteorological Society, 133(628), 1693-1699. doi: 10.1002/qj.147 Lim, K.-S. S., J. Fan, L. R. Leung, P.-L. Ma, B. Singh, C. Zhao, Y. Zhang, G. Zhang, and X. Song (2014), Investigation of aerosol indirect effects using a cumulus microphysics parameterization in a regional climate model. Journal of Geophysical Research: Atmospheres. doi: 10.1002/2013JD020958 Liu, S. C., Fu, C., Shiu, C.-J., Chen, J.-P., & Wu, F. (2009). Temperature dependence of global precipitation extremes. Geophysical Research Letters, 36(17), doi: 10.1029/2009GL040218 Pawlowska, H., & Brenguier, J.-L. (2003). An observational study of drizzle formation in stratocumulus clouds for general circulation model (GCM) parameterizations. Journal of Geophysical Research: Atmospheres, 108(D15). doi: 10.1029/2002JD002679 Song, X., & Zhang, G. J. (2011). Microphysics parameterization for convective clouds in a global climate model: Description and single-column model tests. Journal of Geophysical Research: Atmospheres, 116(D2), doi: 10.1029/2010JD014833 Song, X., G. J. Zhang, and J.-L. F. Li. (2012): Evaluation of microphysics parameterization for convective clouds in the NCAR Community Atmosphere Mode CAM5. J. Climate,25, 8568–8590, doi:10.1175/JCLI-D-11-00563.1. Yang, B., Qian, Y., Lin, G., Leung, L. R., Rasch, P. J., Zhang, G. J., McFarlane, S.A., Zhao, C., Zhang, Y., Wang, H., Wang, M., & Liu, X. (2013). Uncertainty quantification and parameter tuning in the CAM5 Zhang-McFarlane convection scheme and impact of improved convection on the global circulation and climate. Journal of Geophysical Research: Atmospheres, 118(2), 395-415. doi: 10.1029/2012JD018213 | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/59299 | - |
dc.description.abstract | 全球尺度模式因為無法解析對流尺度過程而發展出的積雲參數化,目前就微物理而言簡化了許多過程,而這些過程可能增加了模式的不確定性。其中,以Zhang-McFarlane scheme為例,降水的轉換效率為定值,將上升水氣通量以固定比例移除,這個步驟非但只考慮到單一一層的降水,並且忽略該層以上之雨滴成長對於微物理碰撞蒐集的影響。此外,觀測上也注意到降水強度和雲厚度有高次方項的關係存在,但雲厚度在現有的參數化之中對降雨卻是相對不敏感。
為了體現雲物理於積雲參數化中對於降水強度表顯的重要性,本研究將著重於理論分析,使用現有具備物理基礎且針對暖雲的雙矩量微物理參數法,計算在穩定態下(steady-state)不同雲水分布和雲滴數量濃度底下,雨水的質量和數量濃度之變化隨高度影響,其中包含雲滴的自動轉換、雨水蒐集雲滴和雨水自我蒐集過程,討論雲水轉換為雨水的效率,將此結果視為雲物理過程對於降水強度的影響。結果顯示不僅厚度,雲水的分佈和雲滴數量濃度都會影響到降水強度。為了進一步討論雲物理對於積雲參數化的影響,將分析所得的降水轉換效率作為對流厚度和高度的函數,放入Zhang-McFarlane scheme內,使用NCAR全球模式第五版的一維氣柱模式,討論修正後降水轉換效率對於不同厚度對流底下,對流和層狀降雨的變化。就一維氣柱模式的結果而言,對流降水隨對流厚度加深而增加,反之層狀降雨隨後度增加而減少,這樣的結果來自於對流加深對於環境的影響。考慮對流和層狀降雨的分配,在對流活躍時期,對流降雨比例通常較低並使總體降水隨厚度增加而減少,而對流較弱時期,對流降雨比例偏高,使對流對深度變化成為主導項而使降雨隨厚度增加。 | zh_TW |
dc.description.abstract | The cumulus parameterization schemes in GCMs are generally oversimplified in terms of cloud physics, and this has been recognized as a source of model uncertainties in precipitation. The conversion efficiency C0 is a constant in Zhang and McFarlane scheme. The use of C0 not only simplified the local production of rainwater but also ignored the accretion of cloud water at lower layers because in GCMs rainwater is immediately removed from the grid once formed. Some observational study found that rainfall intensity has high-order dependence on cloud depth (Pawlowska 2003). In contrast, rainfall intensity form typical cumulus parameterization only depends linearly on cloud depth and has minimal dependence on microphysical processes.
To understand the importance of cloud macrophysics (e.g., cloud depth) and microphysics to precipitation intensity in the cumulus parameterization, this study presented theoretical analysis for resolving the steady-state dependence of precipitation intensity on cloud depth and microphysical processes (including accretion, auto-conversion and sedimentation) using the physically based parameterization for warm-cloud (Chen and Liu 2004). The results suggest that rainfall intensity is rather sensitive to both microphysical and macrophysical factors. Besides cloud depth, the vertical profile of cloud water content and cloud number concentration both are factors that control the conversion efficiency. Furthermore, to show how C0 vertical variation has significant influence on convective precipitation intensity, the theoretically derived C0 as function of convection depth and height was applied in the single column mode of the NCAR Community Atmospheric Model (SCAM) version5. The distribution of convective and stratiform precipitation in the single column model changes with depth of convection. Since the ratio of convective precipitation is assumed to be determined the tendency of precipitation with convection depth, the convective precipitation increases with convection depth and stratiform precipitation decreases with convective depth. As a result, the total precipitation would increase or decrease with depth depends on the types of rainfall: the higher the ratio of convective precipitation (i.e. non-active period) is more likely to induce the total precipitation increasing with depth. | en |
dc.description.provenance | Made available in DSpace on 2021-06-16T09:19:53Z (GMT). No. of bitstreams: 1 ntu-106-R04229003-1.pdf: 5253142 bytes, checksum: d921f0ea9685c02a1e562338499adb73 (MD5) Previous issue date: 2017 | en |
dc.description.tableofcontents | 致謝 ii
中文摘要 iii Abstract iv Contents v List of tables vi List of figures vii 1. Introduction 1 2. Methodology 7 2.1. RAINDROP GROWTH RATE 7 2.2. Integration over the cloud depth 10 2.3. SCAM 14 3. Results 17 3.1. 1-D theoretical analyses 17 3.2. SCAM results 22 3.2.1. Control run 22 3.2.2. CE cases 23 3.2.3. C0/4 and CE/4 cases 25 3.2.4. Deeper Convections 27 3.2.5. Feedback from grid-scale responses 29 4. Discussion and Summary 31 Reference 38 | |
dc.language.iso | en | |
dc.title | 降雨強度之微物理與宏物理控制:理論分析 | zh_TW |
dc.title | Theoretical analysis on the microphysical and macrophysical control of precipitation intensity | en |
dc.type | Thesis | |
dc.date.schoolyear | 105-2 | |
dc.description.degree | 碩士 | |
dc.contributor.coadvisor | 黃彥婷(Yen-Ting Hwang) | |
dc.contributor.oralexamcommittee | 吳健銘(Chien-Ming Wu),許晃雄(Huang-Hsiung Hsu),楊明仁(Ming-Jen Yang) | |
dc.subject.keyword | 雲微物理,雲宏物理,積雲參數化,全球模式,降水轉換效率, | zh_TW |
dc.subject.keyword | cloud microphysics,cloud macrophysics,cumulus parameterization,climate model,precipitation conversion efficiency, | en |
dc.relation.page | 63 | |
dc.identifier.doi | 10.6342/NTU201701243 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2017-07-05 | |
dc.contributor.author-college | 理學院 | zh_TW |
dc.contributor.author-dept | 大氣科學研究所 | zh_TW |
顯示於系所單位: | 大氣科學系 |
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