博碩士論文 108621024 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:5 、訪客IP:18.217.228.35
姓名 宋柏璋(Bo-Jhang Sung)  查詢紙本館藏   畢業系所 大氣科學學系
論文名稱 臺灣西南部海洋邊界層垂直結構特性分析
(Characteristics of the Vertical Structure of the Marine Boundary Layer at Southwest Taiwan)
相關論文
★ 土地利用型態對地表能量收支與海陸風模擬的影響★ 探討邊界層參數化對氣象與空氣污染模擬結果的影響
★ 探討土地利用型態對珠江口沿岸地區氣象模擬的影響:高污染事件日之個案分析★ 探討台灣地區在春季期間經長程傳輸所觀測之一氧化碳濃度與綜觀天氣之關係
★ 探討地表參數對台灣地區氣象模擬的影響★ 探討區域尺度氣候變遷對台灣地區氣象場及汙染物濃度模擬的影響
★ 使用CMAQ-HDDM探討台灣地區臭氧之非線性 反應及估算高臭氧區的來源貢獻量: 2011年個案分析★ 地表水文循環過程與大氣耦合作用對土壤溼度以及氣象模擬的影響
★ 使用VVM探討陸氣交換過程對台灣地區高解析氣象模擬的影響--理想個案模擬★ 使用群集分析分類綜觀尺度天氣型態以探討台灣北部地區午後熱對流系統局部環流結構與系統發展特性
★ 台灣中部山區局部環流結構特性與其對空氣汙染物傳送過程的影響★ 開發適用於大氣邊界層觀測的無人機系統
★ 雲林地區細懸浮微粒的來源解析★ 臺灣中部山區埔里盆地之局部環流與邊界層結構特性
★ 臺灣背風渦旋特性分析及其對空氣污染物傳輸過程影響★ 探討地下水參數化對於臺灣地表水文過程之影響
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) 空氣污染除了受到人為排放影響,天氣型態也扮演著重要角色。臺灣在冬季受大陸冷高壓天氣系統影響,盛行風為東北風,中南部地區在東北季風影響時,因位於背風面,呈現靜風穩定大氣條件。
臺灣大氣邊界層觀測實驗計畫(Taiwan atmospheric PBL Observation, Modeling, and Data Assimilation experiments, T-POMDA),於2021年1月1日至6日,搭乘海研船三號進行海上觀測實驗,包含探空氣球釋放,並架設10-m氣象塔,收集海面以及大氣邊界層觀測數據。配合海研三號所安排的船期以及行經路線,從高雄港出發往北至中部外海,並返回高雄港。臺中以北因受東北季風影響,海況較差,無法進行觀測。臺中至雲林外海為本次觀測重點區域,探空氣球施放次數較為頻繁。本文結合綜觀氣象、當地天氣特性,來說明大氣邊界層垂直結構特性。
海上觀測期間,受大陸冷高壓天氣系統配置影響,綜觀氣象條件主要受東北季風以及高壓迴流環流結構影響。東北季風盛行時,高屏沿岸呈現弱風尾流特性,而高壓迴流天氣型態下,盛行東風因中央山脈地形阻擋,西半部整體風場微弱,大氣擴散條件不佳,皆有利於污染物濃度的累積。而在此情況下,大氣邊界層垂直結構發展對污染物的擴散行為,也更為重要。
在陸地,白天熱力作用加熱地表,使混合層發展,熱力作用在中午最旺盛,混合邊界層高度為當日最高,晚上隨著輻射冷卻增強,底層形成穩定邊界層,使邊界層高度下降。然而在海洋,因海水的日夜溫差較小,使中午熱力作用較不易加熱海面,夜晚及清晨的輻射冷卻也較不明顯,因此海洋邊界層高度的日變化相比陸地是較小的。
分析結果顯示,中部外海因受管道效應(Channel Effect)影響,風速較高,熱力作用也較明顯,在大氣較不穩定的條件下,邊界層的高度較高,較好的擴散條件使PM2.5濃度較低;然而,南部外海因位於中央山脈較背風面,環境綜觀風不易影響該地,使風速較低,熱力作用也因此不明顯,大氣穩定的情況下使邊界層高度較低,不利的污染物擴散條件使高污染事件更容易發生。
摘要(英) Apart from anthropogenic emissions, air pollution also plays an important role in weather patterns. In winter, Taiwan is affected by Asian continental anticyclone system, and the prevailing wind is northeasterly. Under the influence of the northeast monsoon, central and southern regions become stable atmospheric condition, because they are located at the leeside area of Central Mountain Range.
Taiwan atmospheric PBL Observation, Modeling, and Data Assimilation experiments (T-POMDA) took R/V Ocean Researcher 3 to do the experiment from January 1 to 6, 2021, including the casting of sounding balloons, and erected a 10-meter meteorological tower, to collect observed data from sea surface and atmospheric boundary layer. In line with the schedule and track arranged by R/V Ocean Researcher 3, departing from Kaohsiung Port, to the north to outer-sea of central area, and returned to Kaohsiung Port. Due to the influence of the northeast monsoon to the north of Taichung, the sea conditions were poorer, and the observation couldn’t be carried out. The outer-sea of Taichung to Yunlin is the key area of the observation, so the sounding balloons were released more frequently. This paper combines synoptic weather and local weather characteristics to illustrate the vertical structure characteristics of the planetary boundary layer.
During marine observation, affected by the configuration of Asian continental anticyclone system, synoptic meteorological conditions were mainly affected by the northeast monsoon and the structure of continental high-pressure peripheral circulation. When the northeast monsoon prevailed, the coast of KP area presented the characteristic of the weak wind outflow. While in the weather pattern of high-pressure peripheral circulation, due to the barrier of the Central Mountain Range, the wind prevailed easterly, and the wind field of west side was totally weak, the atmospheric diffusion condition was bad, so that could easily accumulate the pollutants. The development of vertical structure of the planet boundary layer is also more important to the diffusion of pollutants in the situation.
At land, the surface is heated by the thermal action in daytime, and the mixing layer develops, the thermal action is strongest at noon, mixing boundary layer height is highest in the day. Through the enhancement of radiative cooling at nighttime, the bottom layer forms stable boundary layer, and the boundary layer height decreases. However, at the ocean, due to the smaller difference of sea temperature, the thermal action won’t be easier to heat the sea surface at noon, and radiative cooling at night and dawn is less obvious, so the diurnal variation of marine boundary layer height is smaller than land.
The analysis results show that central offshore is influenced by Channel Effect, the wind speed is higher, and the thermal action is more obvious. Under the condition of relatively unstable atmosphere, the boundary layer height is higher, and the better pollutants diffusion condition makes PM2.5 concentration lower. However, the southern offshore is located at more leeside area of Central Mountain Range, the synoptic wind won’t be easier to influence the area, the wind speed is lower, and the thermal action is less obvious. The condition of stable atmosphere makes the boundary layer height lower, the unfavorable pollutant diffusion condition makes severe pollution events occurred easily.
關鍵字(中) ★ 海洋邊界層
★ 細懸浮微粒
★ 臭氧
★ 探空觀測
關鍵字(英) ★ Marine boundary layer
★ PM2.5
★ ozone
★ Sounding observation
論文目次 摘要 i
Abstract iii
致謝 v
表目錄 viii
圖目錄 ix
第一章 緒論 1
1-1 前言 1
1-2 文獻回顧 2
1-3 研究目的 3
第二章 研究方法及資料 5
2-1 海上觀測資訊 5
2-2 天氣型態及各環保署觀測結果 8
2-3 氣象模式介紹及其設定 9
第三章 實驗結果及討論 11
3-1 模式評估及其表現 11
3-2 海面觀測 13
3-3 探空觀測及其和海面觀測的結合 18
第四章 結論及未來展望 24
4-1 結論 24
4-2 未來展望 25
參考文獻 26
附表 32
附圖 36
參考文獻 1. Anthes, R. A., 2001: Applications of COSMIC to meteorology and climate. Terr. Atmos. Ocean Sci., 11(1), 115-156.
2. Anthes, R. A., Bernhardt, P. A., Chen, Y., Cucurull, L., Dymond, K. F., Ector, D., Healy, S. B., Ho, S.-P., Hunt, D. C., Kuo, Y.-H., Liu, H., Manning, K., McCormick, C., Meehan, T. K., Randel, W. J., Rocken, C., Schreiner, W. S., Sokolovskiy, S. V., Syndergaard, S., Thompson, D. C., Trenberth, K. E., Wee, T.-K., Yen, N. L., & Zeng, Z., 2008: The COSMIC/FORMOSAT-3 mission: Early results. Bull. Amer. Meteorol. Soc., 89(3), 313-333.
3. Basha, G., & Ratman, M. V., 2009: Identification of atmospheric boundary layer height over a tropical station using high-resolution radiosonde refractivity profiles: Comparison with GPS radio occultation measurements. J. Geophys. Res., 114, D16101.
4. Bi, Y.-M., Yuan, B., Wang, Y.-F., Ma, G., & Zhang, P., 2013: Assimilation experiment of GPS Bending angle using WRF model. J. Trop. Meteorol., 29(1), 149-156.
5. Bolton, D., 1980: The computation of equivalent potential temperature. Mon.
Weather Rev., 108(7), 1046-1053.
6. Brooks, I. M., 2003: Finding boundary layer top: application of a wavelet covariance transform to lidar backscatter profiles. J. Atmos. Ocean Technol., 20(8), 1092-1095.
7. Cheng, F.-Y., & Hsu, C.-H., 2019: Long-term variations in PM2.5 concentrations under changing meteorological conditions in Taiwan. Sci. Rep., 9(1), 6635.
8. Cheng, W.-L., 2002: Ozone distribution in coastal central Taiwan under sea-breeze conditions. Atmos. Environ., 36(21), 3445-3459.
9. Chou, C.-K., Liu, C., Lin, C.-Y., Shiu, C.-J., & Chang, K.-H., 2006: The trend of surface ozone in Taipei, Taiwan, and its causes: Implications for ozone control strategies. Atmos. Environ., 40(21), 3898-3908.
10. Ciesielski, P. E., Schubert, W. H., & Johnson, R. H., 2001: Diurnal variability of the marine boundary layer during ASTEX. Atmos. Sci., 58(16), 2235-2376.
11. de Oliveira, B. F., Ignotti, E., Artaxo, P., do Nascimento, Saldiva P. H., Junger, W. L., & Hacon, S., 2012: Risk assessment of PM(2.5) to child residents in Brazilian Amazon region with biofuel production. Environ. Health, 11, 64.
12. Ding, J.-C., Kuo, Y.-H., Guo, Y.-R., Du, M.-B., Yang, Y.-M., Ye, Q.-X., He, Q.-S., & Guo, P., 2011: The composite analysis of the thermal structure of 17 typhoons by using COSMIC data. J. Trop. Meteorol., 27(1), 31-43.
13. Ek, M. B., Mitchell, K. E., Lin, Y., Rogers, E., Grunmann, P., Koren, V., Gayno, G., & Tarpley, J. D., 2003: Implementation of Noah land surface model advances in the National Centers for Environmental Prediction operational mesoscale Eta model. J. Geophys. Res. Atmos., 108(D22).
14. Franklin, M., Koutrakis, P., & Schwartz, P., 2008: The role of particle composition on the association between PM2.5 and mortality. Epidemiology 19(5), 680-689.
15. Garractt, J. R., 1992: The atmospheric boundary layer. University Press, Cambridge.
16. Google map.
17. Hong, S.-Y., Y. Noh & J. Dudhia, 2006: A new vertical diffusion package with an explicit treatment of entrainment processes. Mon. Weather Rev., 134(9), 2318-2341.
18. Hsu, C.-H., & Cheng, F.-Y., 2016: Classification of weather patterns to study the influence of meteorological characteristic on PM2.5 concentrations in Yunlin County, Taiwan. Atmos. Environ., 144, 397-408.
19. Hsu, C.-H., & Cheng, F.-Y., 2019: Synoptic weather patterns and associated air pollution in Taiwan. Aerosol Air Qua. Res., 19(5), 1139-1151.
20. Huynh, M., Woodruff, T. J., Parker, J. D., & Schoendorf, K. C., 2006: Relationships between air pollution and preterm birth in California. Paediatr. Perinat. Epidemiol. 20(6), 454-461.
21. Jiménez, P. A., Dudhia, J., González-Rouco, J. F., Navarro, J., Montávez, J. P., & García-Bustamante, E., 2012: A revised scheme for the WRF surface layer formulation. Mon. Weather Rev., 140(3), 898-918.
22. Kain, J. S., 2004: The Kain–Fritsch convective parameterization: an update. J. Appl. Meteorol., 43(1), 170-181.
23. Kells, Lyman M., Kern, Willis F., & Bland, James R., 1940: Plane And Spherical Trigonometry. McGraw Hill Book Company, Inc., 323-326.
24. Kok, G. L., Lind, J. A., & Fang, M., 1997: An airborne study of air quality around the Hong Kong territory. J. Geophys. Res., 102(15), 19043-19057.
25. Kuo, C.-L., Ade, P. A. R., Bock, J. J., Cantalupo, C., Daub, M. D., Goldstein, J., Holzapfel, W. L., Lange, A. E., Lueker, M., Newcomb, M., Peterson, J. B., Ruhl, J., Runyan, M. C., & Torbet, E., 2008: High-resolution observations of the cosmic microwave background power spectrum with ACBAR. Astrophys. J., 600(1), 32-51.
26. Kursinski, E. R., 1997: The GPS radio occultation concept: Theoretical performance and initial results. California Institute of Technology, 3695.
27. Kursinski, E. R., Hajj, G. A., Schofield, J. T., Linfield, R. P., Hardy, K. R., 1997: Observing Earth’s atmosphere with radio occultation measurements using the Global Positioning System. J. Geophys. Res., 102(19), 23429-23466.
28. Lai, H.-C., & Lin, M.-C., 2020: Characteristics of the upstream flow patterns during PM2.5 pollution events over a complex island topography. Atmos. Environ. 227, 117418.
29. Liu, Y., Tang, N.-J., Yang, X.-S., 2016: Height of atmospheric boundary layer as detected by COSMIC radio occultation data. J. Trop. Meteorol., 22(1), 74-82.
30. Mahrt, L., 1981: Modelling the Depth of the Stable Boundary Layer. Boundary-Layer Meteorol., 21, 3-19.
31. Martinelli, N., Girelli, D., Cigolini, D., Sandri, M, Ricci, G., Rocca, G., & Olivieri, O., 2012: Access rate to the emergency department for venous thromboembolism in relationship with coarse and fine particulate matter air pollution. PLoS One 7(4), e34831.
32. Monin, A. S., & Obukhov, A. M., 1954: Basic laws of turbulent mixing in the surface layer of the atmosphere. Contrib. Geophys. Inst. Acad. Sci. USSR, 151(163), e187.
33. Pope, C. Arden, Burnett, Richard T., Thun, & Michael J., 2002: Cancer, cardiopulmonary mortality, and long-term exposure to fine particulate air pollution. J. Amer. Med. Assoc. 287(9), 1132-1141.
34. Rocken, C., Anthes, R., Exner, M., Hunt, D., Sokolovskiy, S., Ware, R., Gorbunov, M., Schreiner, W., Feng, D., Herman, B., Kuo, Y.-H., & Zou, X., 1997: Analysis and validation of GPS/MET data in the neutral atmosphere. J. Geophys. Res., 1022(D25): 29849-29866.
35. Schwartz, J., 2000: Harvesting and long term exposure effects in the relation between air pollution and mortality. Am. J. Epidemiol. 151(5), 440-448.
36. Skamarock, W. C., Klemp, J. B., Dudhia, J., Gill, D. O., Barker, D. M., Duda, M. G., Huang, X.-Y., Wang, W., & Powers, J. G., 2008: A Description of the Advanced Research WRF Version 3. National Center for Atmospheric Research Technical Note, NCAR, Boulder, CO, USA.
37. Subrahamanyam, D., Radhika, R., Sen, G., & Mandal, K., 2001: Variability of mixed layer heights over the Indian Ocean and central Arabian Sea during INDOEX, IFP-99. Boundary-Layer Meterol., 107(3), 683-695.
38. Tang, X.-B., & Xue J.-S., 2009: Preliminary study of the use of COSMIC data in the global 3-Dimentional variance assimilation system of GRAPES. J. Trop. Meteorol., 25(5): 521-531.
39. United State Environmental Protection Agency.
40. Wang, T., Poon, C. N., Kwok, Y. H., & Li, Y. S., 2003: Characterizing the temporal variability and emission patterns of pollution plumes in the Pearl River Delta of China. Atmos. Environ. 37(25), 3539-3550.
41. Wang, T., & Kwok, Y. H., 2003: Measurement and Analysis of a multiday photochemical smog episode in the Pearl River Delta of China. J. Appl. Meteorol., 42(3), 404-416.
42. Wang, T., Wu, Y.-Y., Cheung, T.-F., & Lam, K.-S., 2001: A study of surface ozone and the relation to complex wind flow in Hong Kong. Atmos. Environ., 35(18), 3203-3215.
43. Xing, Y.-F., Xu, Y.-H., Shi, M.-H., & Lian, Y.-H., 2016: The impact of PM2.5 on the human respiratory system. J. Thorac. Dis., 8(1), 69-74.
44. Zhang, M.-G., Mueller, Noel T., Wang, H.-J., Hong, X.-M., Appel, Lawrence J., & Wang, X.-B., 2018: Maternal Exposure to Ambient Particulate Matter ≤ 2.5 µm During Pregnancy and the Risk for High Blood Pressure in Childhood. Hypertension, 72(1), 194-201.
45. Zhong, J.-T., Zhang, X.-Y., Dong, Y.-S., Wang, Y.-Q., Liu, C., Wang, J.-Z., Zhang, Y.-M., & Che, H.-C., 2018: Feedback effects of boundary-layer meteorological factors on cumulative explosive growth of PM2.5 during winter heavy pollution episodes in Beijing from 2013 to 2016. Atom. Chem. Phys., 18, 247-258.
46. 林毓琇, (2018). 以迴歸模式預測海溫趨勢 – 以澎湖為例, 國立中山大學海洋環境與工程學系碩士論文.
47. 國立中山大學 新海研3號貴重儀器使用中心.
48. 黃光遠, 劉聖宗, (2006). 赴美研習WRF數值預報天氣模式報告書, 交通部民用航空局.
49. 中華民國海洋協會.
50. 張志誠, 劉龍偉, (1985). 馬公地區冬季強風預報與分析, 空軍氣象預報與分析, 104, 29-34.
51. 吳政忠, 呂芳川, 陳文定, 趙尊憲, 莊漢明, (2005). 冬季臺灣附近海域強風預報研究, 中央氣象局.
指導教授 鄭芳怡(Fang-Yi Cheng) 審核日期 2022-8-20
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