海岸帶地區海表拖曳係數與海表粗糙度（均方傾度）之相依關係

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：53

、訪客IP：18.191.72.220

姓名

塔薩努(Nurul Tazaroh) 查詢紙本館藏

畢業系所

水文與海洋科學研究所

論文名稱

海岸帶地區海表拖曳係數與海表粗糙度（均方傾度）之相依關係
(THE DEPENDENCY OF SEA SURFACE DRAG COEFFICIENT ON MEAN SQUARE SLOPE IN COASTAL ZONE)

相關論文

★ 西北太平洋長期波候變遷之研究	★ 近岸海洋波浪對海面粗糙度之影響
★ 濁水溪河口懸浮沉積物輸送之調查研究	★ 低掠角微波雷達海面背向散射強度受波浪影響程度之探討
★ 澎湖海域潮流之數值模擬及其發電潛能評估	★ 台灣沿海表面風之週期特性
★ 微波雷達與CCD影像分析於潮間帶地形測量之應用	★ The directional spreading of surface wave in the shallow water zone
★ Resuspension of bottom sediment on Inner shelf - A case study of North-western coast of Taiwan	★ 平緩海灘表層含水量變化特性研究
★ Development of S-band and Coherent-on-Receive Marine Radar for Ocean Surface Wave and Current Measurement	★ 內陸棚及河口混合與擴散特性觀測研究
★ 臺灣海峽海洋塑料垃圾的輸運	★ 有限項目的連續水質監測應用於探討觀新藻礁區水體環境即時變化
★ 應用微波雷達監測海流之演算法流程改善	★ 微型資料浮標觀測波浪及MSS的比對分析與演算流程的改善

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]

本電子論文使用權限為同意立即開放。
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。
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)

海表粗糙度是控制海洋邊界層的主要因素，可以由拖曳係數來表示。另外，均方傾度（mean square slope，MSS）也是一種表征海表面粗糙度的參數。因此，本研究目的在於以ADCP觀測資料估計MSS的算法，並討論其有效性和準確性。第二，藉助岸基通量塔以渦動方差法量測海表拖曳係數。第三，探討控制大氣邊界層特性的海表粗糙度，風速和波浪參數，並討論這些參數之間的内在聯係。
三維超音波風速計以渦動方差法量測紊流，進而推算拖曳係數（C_d）。風速計位於台灣西岸的TaiCOAST沿海工作站，距離平均海面15m的通量塔上。ADCP被錨定在距離永安海岸西北方向大約1.4公里的位置，被用以量測波浪數據。觀測時間為2011年5月26日到2011年6月22日。之後，方向波譜可由水位高度數據計算得出，經轉換成波數波譜後，被用以估算均方傾度（MSS）。
本研究中，我們發現15公尺海表風速小於10 m/s時，拖曳係數與風速呈現正相關，當風速在10m/s到15m/s之間時，拖曳係數與風速成負相關。另外，MSS與風速呈現相關性，相關係數為0.7，p值是2×〖10〗^(-20)。與此同時，根據第二類回歸模型，拖曳係數與MSS呈現正相關，然而相關係數為0.01. 拖曳係數與均方傾度之間的對應關係離散程度較大意味著，除均方傾度之外，仍有其他參數可用來解釋拖曳係數與均方傾度的關係。因此，為探究哪些其他參數對拖曳係數的與均方傾度的關係有影響，我們做了8組實驗，每個實驗被設計爲測試一組參數來討論結果。這些參數是，潮流方向，示性波高，示性波浪周期，主波向，風速，風與波浪之間的夾角，風生波浪海表粗糙度雷諾數（wind sea surface roughness Reynolds number，Rb），以及波齡。最後，在我們探究風與波浪參數的内在關係后，我們發現Rb和波齡最適合被用以分類討論拖曳係數與均方傾度的關係，以及被用以分類討論拖曳係數與風速的關係。

摘要(英)

The sea surface roughness which is a dominating factor controlling marine boundary layer (MBL) can be described by the drag coefficient〖(C〗_d). Additionally, the mean square slope also can be a parameter of the sea surface roughness. Therefore, this study proposes to implement an algorithm that estimates the mean square slope (MSS) from ADCP measurement and to discuss its effectiveness and correctness. Second, to implement the observation of sea surface drag coefficient using the eddy covariance method from coastal based flux tower. Third, to investigate the characteristics of sea surface roughness, wind speed, and wave parameters, which control the MBL and discuss the inter-relationship among the characteristics.
The C_d was estimated from turbulence measurement from a 3-D ultrasonic anemometer using the eddy-covariance method. The instrument installed on a flux tower above 15 m of mean sea level in TaiCOAST station located on the western coast of Taiwan. While around 1.4 km to the northwest from the Yongan coast, in-situ wave data was obtained by ADCP that mounted at the bottom sea from 26 May 2011 to 22 June 2011. Then, the wave directional spectrum calculated from water elevation data was transformed into the wavenumber spectrum to estimate the MSS.
In this study, we found the drag coefficient was positively correlated to wind speed when u ̅_15 was less than 10 m/s, while the trend became negative when u ̅_15 was between 10 m/s and 15 m/s. Next, the MSS shows a strong dependency on u ̅ with a correlation coefficient of 0.7 and p-value of 2×〖10〗^(-20). While the C_d was positively correlated to MSS base on model II regression, however, the dots were scattered so that the correlation coefficient r was 0.01. The scattered dependency of C_dN on MSS indicated there were other parameters except for MSS to explain the pattern of C_dN. Thus, to investigate what are the other parameters that have more influence on C_dN, we made 8 experiments, each experiment including one parameter, to discuss the result. And, these parameters were tidal current direction, H_(1⁄3), T_(1⁄3), D_p, wind speed, the angle difference between wind and wave direction, R_b, and wave age. Finally, after we did inter-relationship between wind-wave parameters, we found that R_b and β were suitable parameters to categorize the pattern of drag coefficient in relationship with wind speed as well with MSS.

關鍵字(中)

★ 拖曳係數
★ 風速
★ 均方傾度
★ 方向波譜
★ 波數譜

關鍵字(英)

★ drag coefficient
★ wind speed
★ mean square slope
★ directional wave frequency spectrum
★ wavenumber spectrum

論文目次

摘要 i
ABSTRACT iii
ACKNOWLEDGMENTS v
TABLE OF CONTENTS vii
LIST OF FIGURES x
LIST OF TABLES xv
Chapter 1 Introduction 1
1.1 Research motivation and aims 1
1.2 Fundamental theories 3
1.2.1 Method of MSS estimation 4
1.2.2 Method of C_dN estimation 14
1.3 Research Strategy 16
Chapter 2 Datasets and Data Processes 18
2.1 Data Source 18
2.2 MSS estimation 21
2.2.1 Analysis of Wave Directional Spectrum 28
2.2.2 Data Quality Control 35
2.2.3 MSS Estimation 44
2.3 C_dN estimation 51
2.3.1 In-situ Measurement of Turbulence 51
2.3.2 Quality Control of 3-D Supersonic Anemometer Data 52
2.3.3 Datasets of wind and wave data 62
Chapter 3 Results and Discussion 65
3.1 Relationship between u ̅_15 and C_dN 65
3.2 Relation between u ̅_15 and MSS 71
3.3 Relationship between MSS and C_dN 74
3.4 Discussion of the inter-relationship among the characteristics of the marine boundary layer (MBL) 75
Chapter 4 Conclusions 97
References 100
Appendix-A Wave Gauge Arrangement 107
Appendix-B The Results of Performance Test of DIWASP Toolbox 108
Appendix-C Tidal Analysis (Flood-Ebb Tide Detection) 112
Appendix-D Validation of Wind Data 113

Appendix-E The Correlation Between Drag Coefficient and Reynolds Windsea Number 114
Appendix-F The Correlation Between Drag Coefficient and Wave Age 115

參考文獻

Barber, N. F. (1961). The directional resolving power of an array of wave detectors, Ocean Wave Spectra. Prentice Hall. Inc., 137–150.
Bryant, K. M., & Akbar, M. (2016). An exploration of wind stress calculation techniques in hurricane storm surge modeling. Journal of Marine Science and Engineering, 4 (3), 58.
Capon, J. (1969). High-resolution frequency-wavenumber spectrum analysis. Proceedings of the IEEE, 57(8), 1408-1418.
Chen, D. D., Ruf, C. S., & Gleason, S. T. (2016). Response time of mean square slope to wind forcing: An empirical investigation. Journal of Geophysical Research: Oceans, 121 (4), 2809-2823.
Chien, H., Zhong, Y. Z., Yang, K. H., & Cheng, H. Y. (2018). Diurnal variability of CO2 flux at coastal zone of Taiwan based on eddy covariance observation. Continental Shelf Research, 162 (August 2017), 27–38.
Cox, C., & Munk, W. (1956). Deduced From Photographs. Bulletin of the Scripps Institution of Oceanography, 401–488.
Cox, C. S. (1958). Measurements of slopes of high-frequency wind waves. J. Mar. Res., 16, 199–225.
Dale, S. (2019). BP Statistical Review of World Energy. In British Petroleum (BP).
Deacon, E., & Webb, E. K. (1962). Interchange of properties between sea and air. In The Sea, 43–87.
Denman, K. L., & Miyake, M. (1973). Upper Layer Modification at Ocean Station Papa : Observations and Simulation. Journal of Physical Oceanography, Vol. 3, 185–196.
Donelan, M. (1979). On the fraction of wind momentum retained by waves. In Elsevier Oceanography Series, Vol. 25, 141–159. Elsevier.
Feng, Y. J. (2011). On the Gravity Wave and Sea Surface Roughness Relationship in Coastal Ocean.
Francis, J. R. D. (1951). The aerodynamic drag of a free water surface. Proceedings of the Royal Society of London. Series A. Mathematical and Physical Sciences, 206 (1086), 387-406.
Garrat, J. R. (1977). Review of Drag Coefficients over Oceans and Continents. Monthly Weather Review, 105.
Geernaert, G. L., Larsen, S. E., & Hansen, F. (1987). Measurements of the wind stress, heat flux, and turbulence intensity during storm conditions over the North Sea. Journal of Geophysical Research: Oceans, 92 (C12), 13127–13139.
Gordon, R. L. (2011). Acoustic Doppler current profiler: Principles of operation, a practical primer, 32.
Haimbach, S. P. (1985). Development of slope spectra of the wind-disturbed water surface. University of Delaware.
Hashimoto, N., & Kobune, K. (1987). Estimation of directional spectra from a Bayesian approach in incident and reflected wave field. Report Port & Harbour Res. Inst., 26 (4, Dec. 1987), 3-33.
Hashimoto, N., Nagai, T., & Asai, T. (1995). Extension of the maximum entropy principle method for directional wave spectrum estimation. In Coastal Engineering 1994, 232-246.
Hashimoto, N., Nagai, T., & Asai, T. (1993). Modification of the extended maximum entropy principle for estimating directional spectrum in incident and reflected wave field. Rept. of PHRI, 32(4), 25-47.
Heron, M. L., Skirving, W. J., &Michael, K. J. (2006). Short-wave ocean wave slope models for use in remote sensing data analysis. IEEE Transactions on Geoscience and Remote Sensing, 44 (7), 1962–1973.
Hsu, S. A., Meindl, E. A., & Gilhousen, D. B. (1994). Determining the Power-Law Wind-Profile Exponent under Near-Neutral Stability Conditions at Sea. Journal of Applied Meteorology, 33(6), 757–765.
Hwang, P. A., & Fan, Y. (2018). Low-frequency mean square slopes and dominant wave spectral properties: Toward tropical cyclone remote sensing. IEEE Transactions on Geoscience and Remote Sensing, 56(12), 7359–7368.
Isobe, M., Kondo, K., & Horikawa, K. (1984). Extension of mlm for estimating directional wave spectrum, in ‘Symp. on Description and Modelling of Directional Seas’. DHI and MMI, Copenhagen, 1-15.
Iida, N., Toba, Y., & Chaen, M. (1992). A new expression for the production rate of sea water droplets on the sea surface. Journal of Oceanography, 48 (4), 439–460.
Janssen, J. A. M. (1997). Does wind stress depend on sea-state or not?--A statistical error analysis of Hexmax data. Boundary-Layer Meteorology, 83(3), 479–503.
Johnson, H. K., Højstrup, J., Vested, H. J., &Larsen, S. E. (1998). On the dependence of sea surface roughness on wind waves. Journal of Physical Oceanography, 28(9), 1702–1716.
Jones, I. S., & Toba, Y. (2001). Wind Stress over the Ocean, 65-67. Cambridge: Cambridge University Press.
Kawai, S., Okada, K., & Toba, Y. (1977). Field data support of three-seconds power law andgu* σ− 4-spectral form for growing wind waves. Journal of the Oceanographical Society of Japan, 33(3), 137-150.
Lange, B., Larsen, S., Hojstrup, J., & Barthelmie, R. (2004). Importance of thermal effects and sea surface roughness for offshore wind resource assesment. Journal of Wind Engineering and Industrial Aerodynamics, 92, 959–988.
Li, S., Zhao, D., Zhou, L., & Liu, B. (2013). Dependence of mean square slope on wave state and its application in altimeter wind speed retrieval. International Journal of Remote Sensing, 34.
Long, S. R., & Huang, N. E. (1976). On the variation and growth of wave-slope spectra in the capillary-gravity range with increasing wind. Journal of Fluid Mechanics, 77 (2), 209–228.
Lu, Q. H. (2012). The Directional Spreading Of Surface Wave In The Shallow Water Zone.
Merzi, N., & Graf, W. (1985). Evaluation of the drag coefficient considering the effects of mobility of the roughness elements. Ann. Geophys., 3, 473–478.
Pawka, S. S. (1983). Island shadows in wave directional spectra. Journal of Geophysical Research: Oceans, 88(C4), 2579-2591.
Phillips, O. M., ed. 1977. The Dynamics of the Upper Ocean. 2nd ed., 336. Cambridge: Cambridge University Press.
Sheppard, P. A. (1958). Transfer across the earth’s surface and through the air above. Quarterly Journal of the Royal Meteorological Society, 84 (361), 205–224.
Stull, R. B. (1988). An Introduction to Boundary Layer Meteorology. Dordrecht: Kluwer Academic Publisher, 67.
Suzuki, N., Ebuchi, N., Akiyama, M., Suwa, J., & Sugimori, Y. (1998). Relationship between non-dimensional roughness length and wave age investigated using tower-based measurements. Journal of Advanced Marine Science and Technology Society, 4 (2), 217–224.
Suzuki, N., Toba, Y., &Komori, S. (2010). Examination of drag coefficient with special reference to the windsea Reynolds number: Conditions with counter and mixed swell. Journal of Oceanography, 66 (5), 731–739.
Toba, Y., Komori, S., Suzuki, Y., & Zhao, D. (2006). Similarity and dissimilarity in air–sea momentum and CO 2 transfers: the nondimensional transfer coefficients in light of the windsea Reynolds number . Atmosphere-Ocean Interactions, 23, 53–82.
Toba, Yoshiaki, Suzuki, Y., & Iida, N. (1999). Study on global distribution with seasonal variation of the whitecap coverage and sea-salt aerosol production on the sea surface. The Wind-Driven Air-Sea Interface, 355–356.
Wilson, B. W. (1960). Note on surface wind stress over water at low and high wind speeds. Journal of Geophysical Research, 65 (10), 3377–3382.
Wu, J. (1967). Wind Stress and Surface Roughness at Air-Sea Interface. Hydronautics Inc Laurel Md.
Wu, J. (1971). Slope and curvature distributions of wind-disturbed water surface. JOSA, 61(7), 852-858.
Wu, K.Y., Huang, Y.H., & Wu, J.H. (2018). Impact of electricity shortages during energy transitions in Taiwan. Energy, 151, 622–632.
Young, I. R. (1999). Wind Generated Ocean Waves. In Encyclopedia of Ocean Sciences (First edit), 20-23. Oxford: Elsevier.
Zhao, D., & Toba, Y. (2001). Dependence of whitecap coverage on wind and wind-wave properties. Journal of oceanography, 57(5), 603-616.

指導教授

錢樺(Hwa Chien)

審核日期

2019-12-24

推文