|dc.description.abstract||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.||en_US|