博碩士論文 946201014 詳細資訊




以作者查詢圖書館館藏 以作者查詢臺灣博碩士 以作者查詢全國書目 勘誤回報 、線上人數:7 、訪客IP:3.229.118.253
姓名 紀雍華(Yong-hua Ji)  查詢紙本館藏   畢業系所 大氣物理研究所
論文名稱 藉由雷達模擬軟體QuickBeam探討雲與降水遙測之原理
(A study of the remote sensing theories of cloud and precipitation by QuickBeam radar simulation software)
相關論文
★ 淡水河河口水質與懸浮細泥之調查研究★ 東亞地區降水氣候的特徵分析
★ 全球與區域水氣收支初步分析★ 海氣通量計算與海洋混合層模擬
★ 夏季西北太平洋副熱帶高壓之年際及年代際變化★ 評估NOAH陸地過程模式在石門水庫集水區模擬之水文循環過程
★ 影響夏季西北太平洋副熱帶高壓年際變化之氣候因子★ 伴隨氣候變化的台灣地區降雨特性分析
★ 藉由莫拉克颱風及西南氣流個案探討雲微物理參數化法模擬雷達回波結果之比較★ 西北太平洋熱帶氣旋生成之多尺度分析
★ 熱源驅動Gill模型解與熱帶年際震盪的比較
檔案 [Endnote RIS 格式]    [Bibtex 格式]    [相關文章]   [文章引用]   [完整記錄]   [館藏目錄]   [檢視]  [下載]
  1. 本電子論文使用權限為同意立即開放。
  2. 已達開放權限電子全文僅授權使用者為學術研究之目的,進行個人非營利性質之檢索、閱讀、列印。
  3. 請遵守中華民國著作權法之相關規定,切勿任意重製、散佈、改作、轉貼、播送,以免觸法。

摘要(中) 雲與降水過程為大氣科學研究的重要議題,為了探討此些現象,裝載
有主被動微波感應器的衛星,如熱帶雨量測量任務衛星(Tropical Rainfall
Measuring Mission, TRMM)和CloudSat衛星陸續發射;而模擬雲與降水過程
的高解析度模式的發展亦趨於完備。隨著衛星觀測資料的日益增加和模式
模擬雲值的可用度提升,如何有效應用衛星資料評估模式輸出值變得相當
重要。基於上述理由,此時需將模式模擬雲值轉換為有效雷達反射率因子
(Ze),藉此模式轉換之Ze值便可和星載雷達觀測的Ze值比較。QuickBeam為
一氣象雷達模擬軟體,不論模擬的雷達電磁波傳輸方向為由天空往下或由
地表往上行進,只要藉由在常用的微波頻率範圍內給定水象粒子資訊,便
可模擬垂直的雷達反射率剖面。本研究目的著重於了解此雷達模擬軟體所
依據的原理,並討論其使用上的特性和限制。
QuickBeam的運算過程包含兩大部分:藉由水象粒子和氣象場變數資
料獲得粒子的微物理特性,並計算粒子的光學效應。首先在包含有雲滴至
降水粒子尺寸的雲內,藉由指定各種水象粒子的滴譜(drop-size distribution)
可計算得各種粒子的幾何截面積。接著計算反散射效率(Q(s)),在QuickBeam
中對所有尺寸的水象粒子(在此假設粒子均為球形)均使用米氏理論計算,
幾何截面積乘上Q(s)值並對粒子直徑積分後便可得雷達反射係數(η)。將η值
轉換為Ze值,扣除Ze值因水象粒子和空氣分子所造成之衰減,便得到考慮
衰減修正的雷達反射率。
本研究利用QuickBeam 內附包含六種水象粒子(雲水、雨、雪、撞併、
軟雹、雲冰)混合比的個案,檢驗QuickBeam 內的各項計算,並得到以下
結論:1)如何將觀測或模擬得的水象粒子混合比參數化為粒子數目( n(D))
是QuickBeam 運算中的關鍵過程;2)對水象粒子及空氣分子的各種光學特
性之理解將有助於評估QuickBeam 的模擬結果。
然而,目前對上述議題(如雲與降水的微物理過程及粒子的光學特性)
之瞭解仍相當有限,這造成QuickBeam 在模擬雷達反射率時的限制。
摘要(英) Clouds and precipitation is the central issue in atmospheric research.
Many passive and active microwave sensors have been developed and launched
(e.g. TRMM and CloudSat) for measuring clouds and precipitation from space.
High resolution models are also becoming better and more affordable. With
more satellite measurements and model-simulated clouds becoming available,
how to best utilize the data to evaluate model outputs becomes
ever-increasingly important. The above concern motivates an approach to
convert model simulated clouds into effective radar reflectivity factor (Ze) so it
can be compared directly with measured Ze by space-borne radar. QuickBeam
is a meteorological radar simulation package. It is designed to simulate vertical
radar reflectivity profiles from given hydrometeor information at any common
microwave frequency, from either the top-down (i.e. satellite-based radars such
as CloudSat) or the bottom-up. The purpose of this study is to understand
the theory and the limitations of the radar simulation software.
QuickBeam consists of two major parts: to derive cloud microphysical
properties from given cloud information, and to compute cloud radiative effects.
The first part is to get geometric cross-section area of all hydrometeors. This is
done by specifying a drop size distribution function for each bulk category of
clouds. The second part is to calculate the backscatter efficiency, Q(s), for cloud
particles of different size (normally diameter assuming clouds are spherical
shape) based on Mie theory. By multiplying the geometric cross-section area
with Q(s) and integrating it over the whole cloud spectrum, one gets the radar
reflective coefficient (η). Finally, one can convert η to Ze, and subtract the
attenuation by hydrometeor and atmospheric gases to get the corrected volume
reflectivity.
We applied QuickBeam to an example of given vertical profiles of mixing
ratio for six common bulk categories of clouds: cloud water, rain, cloud ice,
snow, aggregate, graupel. A careful examination of each step of the calculation
reveals the following:
(1) How to specify the number of hydrometeors ( n(D)) from a given cloud
mixing ratio is a critical step that requires extensive knowledge and observational
evidence in cloud microphysics.
(2) A good knowledge of spectrally dependent cloud optical properties is
required to assess the model results.
Our current understanding about the above issues is still quite limited.
This poses limitations of QuickBeam.
關鍵字(中) ★ 米氏散射
★ 有效雷達反射率因子
★ 水象粒子
關鍵字(英) ★ Mie scattering
★ effective radar reflectivity factor
★ hydrometeor
論文目次 中文摘要 …………………………………………………………i
英文摘要 ………………………………………………….….....iii
目錄 …………………………………………………….......v
圖目錄 …………………………………………………….....vii
表目錄 …………………........................................................x
第一章 緒論..…....…..........………...……….………………….1
1-1 研究動機…....…….........….….........…………………....1
1-2 文獻回顧..................………........……………………….1
1-3 雷達氣象方程…......………........……………………….2
1-4 文章架構…..............……..……………………………...4
第二章 QuickBeam模擬原理…................…….………………..5
2-1 雷達模擬簡介…...…….................……..………………5
2-2 QuickBeam輸入值..........................................................6
2-3 水象粒子微物理計算.......................................................8
2-3-1 建立固定的分離粒子尺寸列...........................................9
2-3-2 雲雨滴譜(DSD)的計算.....................................................9
第三章 粒子光學特性..............................................................15
3-1 水相和冰相複數折射指數.............................................15
3-2 米氏散射及衰減和反散射效率…......….......................19
3-3 和未考慮衰減的Ze值……........…...…….......………21
3-4 水象粒子和空氣分子造成之衰減…......…...............…23
第四章 個案分析與比較..........................................................…27
4-1 滴譜設定之重要性...........................................................27
4-2 反散射效率對Ze值的影響..............................................29
4-3 水象粒子和空氣分子之衰減...........................................30
4-4 程式內部設定…….………..................…………………32
4-5 和觀測雷達原理之比較...................................................33
第五章 結論....................................................................................35
參考文獻 ............................................................................................37
附錄一 ............................................................................................42
附錄二 ............................................................................................43
附錄三 ............................................................................................44
附錄四 ............................................................................................46
參考文獻 [1] 王寶貫,雲物理學,渤海堂,台北市,民國八十六年一月。
[2] 呂崇華,「雙偏極化雷達資料分析梅雨鋒面雨滴粒徑分佈的物理特性」,國立中央大學,碩士論文,民國九十五年。
[3] 曾忠一,大氣輻射,聯經,台北市,民國七十七年。
[4] Battan, L. J., Radar observation of the atmosphere, University of Chicago Press, Chicago, 1973.
[5] Bertie, J. E., H. J. Labbe, and E. Whalley, “Absorptivity of Ice I in the Range 4000–30 cm–1”, J. Chem. Phys., Vol.50, pp.4501-4520, May 1969.
[6] Brown, P. R. A. and Swann, H.A., “Evaluation of key microphysical parameters in three-dimensional cloud-model simulations using aircraft and multiparameter radar data”, Q. J. R. Meteorol. Soc., Vol.123, pp.2245-2275, October 1997.
[7] Cole, K.S. and Cole, R.H., “Dispersion and absorption in dielectrics”, J. Chem. Phys., Vol.9, pp.341-351, April 1941.
[8] Douglas, R. H., “Hail size distributions”, Proc. Conf. on Radio Meteorology and 11th Weather Radar Conf. Amer. Meteor. Soc., pp.146-149, Boulder, CO, 1964.
[9] Flatau, P. J., G. J. Tripoli, J. Verlinde, and W. R. Cotton, The CSU-RAMS cloud microphysical module:general theory and documentation., Colorado State Univ., Dep. Atmos. Sci., Fort Collins, Colorado, 1989.
[10] Haynes, J. M., “QuickBeam radar simulation software user’s guide”, Colorado State University, October 2007.
[11] Haynes, J. M., R. T. Marchand, Z. Luo, A. Bodas-Salcedo, and G. L. Stephens, “A multipurpose radar simulation package: QuickBeam”, Bull. Amer. Meteor. Soc., Vol.88, pp.1723-1727, November 2007.
[12] Heymsfield, A. J., “Ice crystal terminal velocities”, J. Atmos. Sci., Vol.29, pp.1348-1357, October 1972.
[13] Heymsfield, A. J., “Precipitation development in stratiform ice clouds: A microphysical and dynamical study”, J. Atmos. Sci., Vol.34, pp.367-381, February 1977.
[14] Heymsfield, A. J. and Platt, C. M. R., “A parameterization of the particle size spectrum of ice clouds in terms of ambient temperature and ice water content”, J. Atmos. Sci., Vol.41, pp.846-855, March 1984.
[15] Houze, R. A., Cloud dynamics, Academic Press., U.S.A., 1993.
[16] Kessler, E., On the distribution and continuity of water substance in atmospheric circulation, Vol.10, Meteor. Monogr., Amer. Meteor. Soc., U.S.A., 1969.
[17] Kreyszig, E., Advanced engineering mathematics, 8th, John Wiley & Sons, Singapore, 1999.
[18] Liebe, H. J., “An updated model for millimeter wave propagation in moist air”, Radio Science, Vol. 20, pp.1069-1089, September- October 1985.
[19] Lin, Y. L., R.D. Farley, and H.D. Orville, “Bulk parameterization of the snow field in a cloud model”, J. APPL. Meteor., Vol. 22, pp.1965-1902, February 1983.
[20] Liou, K. N., An introduction to atmospheric radiation, Vol.84, 2nd, Academic Press, California, 2002.
[21] Luo, Z., J. Chern, J. M. Haynes, G. L. Stephens, W. Tao, and N. B. Wood, “Evaluating Colorado State University and NASA Goddard multi-scale modeling framework (MMF) representation of tropical cloud and precipitation structures using CloudSat data”, Evaluation of Cloud Paramete- rizations Using Multiconstellation Satellite Platforms I, San Francisco, CA, U.S.A., December 2007.
[22] Marshall, J. S. and Palmer, W. McK., “The distribution of raindrops with size”, J. Meteor., Vol.5, pp.165-166, August 1948.
[23] Petty, G. W., A first course in atmospheric radiation, 2nd, University of Wisconsin-Madison: Sundog Publishing, U.S.A., 2006.
[24] Platt, C. M. R., “A parameterization of the visible extinction coefficient in terms of the ice/water content”, J. Atmos. Sci., Vol.54, pp.2083-2098, August 1997.
[25] Ray, P. S., “Broadband Complex Refractive Indices of Ice and Water”, Applied Optics, Vol.11, pp.1836-1844, August 1972.
[26] Reisner, J., Rasmussen, R. J., and Bruintjes, R. T., “Explicit forecasting of supercooled liquid water in winter storms using the MM5 mesoscale model”, Quart. J. Roy. Meteor. Soc., Vol.124, pp.1071–1107, April 1998.
[27] Richard, J. D. and Dusan, S. Z., Doppler radar and weather observations, 1st, Academic Press, U.S.A., 1984.
[28] Rogers, R. R. and Yau, M. K., A short course in cloud physics, 3rd, Butterworth-Heinemann, U.S.A., 1996.
[29] Rosenkranz, P. W., “Shape of the 5mm oxygen band in the atmosphere”, IEEE Tran. Antennas Propag., Vol.23, pp.498-506, July 1975.
[30] Rosenkranz, P. W., “Comment on absorption and dispersion in the O2 microwave spectrum at atmospheric pressures”, J. Chem. Phys., Vol.77, pp.2216–2217, August 1982.
[31] Ryan, B., “A bulk parameterization of the ice particle size distribution and the optical properties of ice clouds”, J. Atmos. Sci., Vol.57, pp.1436-1451, May 2000.
[32] Sekhon, R. S. and Srivastava, R. C., “Snow size spectra and radar reflectivity” J. Atmos. Sci., Vol.27, pp.299-307, March 1970.
[33] Smith, P. L., JR., C. G. Myers, and H. D. Orville, “Radar reflectivity factor calculations in mumerical cloud models using bulk parameterization of precipitation”, J. Appl. Meteor., Vol.14, pp.1156-1165, September 1975.
[34] Stone, N. W. B., L. A. A. Read, A. Anderson, I.R. Dagg, and W. Smith, “Temperature dependent collision-induced absorption in nitrogen”, Can. J. Phys., Vol.62, pp.338–347, April 1984.
[35] Thompson, G., R.M. Rasmussen, and K. Manning, “Explicit forecasts of winter precipitation using an improved bulk microphysics scheme. Part I: Description and sensitivity analysis”, Mon. Wea. Rev., Vol.132, pp.519 -542, February 2004.
[36] Ulbrich, C. W., “Natural variations in the analytical form of the raindrop size distribution”, J.Climate Appl. Meteor., Vol.22, pp.1764-1775, October 1983.
[37] Verlinde, J. P. J. Flatau, and W. R. Cotton, “Analytical solutions to the collection growth equation: comparison with approximate methods and application to cloud microphysics parameterization schemes”, J.Atmos. Sci., Vol.47, pp.2871-2880, December 1990.
[38] Walko, R. L., W. R. Cotton, M. P. Meyers, and J. Y. Harrington, “New RAMS cloud microphysics parameterization Part I: the single-moment scheme”, Atmos. Rec., Vol.38, pp.29-62, November 1995.
[39] Warren, S. G., “Optical constants of ice from the ultraviolet to the microwave”, Applied Optics, Vol.23, pp.1206-1225, April 1984.
[40] Zhao, Q., J. Cook, Q. Xu, and P. R. Harasti, “Using radar wind observations to improve mesoscale numerical weather prediction”, Weather and Forecasting, Vol.21, pp.502-522, August 2006.
指導教授 隋中興(Chung-hsiung Sui) 審核日期 2008-7-17
推文 facebook   plurk   twitter   funp   google   live   udn   HD   myshare   reddit   netvibes   friend   youpush   delicious   baidu   
網路書籤 Google bookmarks   del.icio.us   hemidemi   myshare   

若有論文相關問題,請聯絡國立中央大學圖書館推廣服務組 TEL:(03)422-7151轉57407,或E-mail聯絡  - 隱私權政策聲明