本研究結合離岸測風塔之氣象資料，固定式光達(Lidar)的現地量測，與岸上氣象站之風力資料，進行比較驗證及交叉分析，進而建立風剖面分佈。此研究以離岸測風塔之十分鐘平均風速資料，進行每月的指數定律的次方項分析和韋伯分佈常數計算。在多數研究一個特定區域的風況中，常被認定或當作一個固定且大於零的常數。然而在此研究發現，指數並不是恆為正，並隨著風速大小有不同的變化。當風速越快，韋伯分佈常數越大。
本研究亦使用資料重建方法(MCP)，以岸上氣象站之風力資料重建離岸測風塔之風力資料，再以不同方式取樣，推算極端風速，分析該地風場的情況。在三種的海上測風塔之風速資料與岸上氣象站之風速資料的回歸分析中，以二次方法做回歸分析，擁有較佳的決定係數，因此本研究採用二次方法進行資料重建。用不同取樣方式：每小時、每日、每月和每年的最大風速，帶入萊利、韋伯、常態、極值、逆高斯和廣義柏拉圖分佈，所推估的極端風速值，不盡相同。原始離岸測風塔之風力資料與重建後之風力資料，在相同取樣方式，所推出的極端風速值大略相同。重建後之風力資料所推出的極端風速值，隨著取樣點減少而增加。

In this study, offshore wind data from Offshore meteorological measurements, Lidar measurement wind data and onshore wind data from weather station were used to analyze wind conditions and wind profile exponents. The 10-min mean wind speed data for offshore were used to analyze the shear exponent of the power law and the parameters of Weibull distribution each month. The shear exponent values in the power law were considered as a fixed constant in a measurement site before. However, the shear exponent values derived from this study are not always positive and vary with wind speeds.
The MCP (Measure-Correlate-Predict) methods have been used to reconstruct long-term offshore wind data from wind data collected at Wuqi weather station from Aug 1999 to Apr 2017. The quadratic regression method has largest correlation coefficient among the three regression methods for offshore wind speed data and onshore weather station, and was used in this study. The data were conducted with different sampling methods and then used for estimates of wind speed associated with return periods of 1, 5, 50 years. The maxima of hourly, daily, monthly and yearly wind data were used to fit statistical probability distributions such as Rayleigh, Weibull, normal, generalized extreme value, inverse Gaussian, and generalized Pareto distributions. The estimates of wind speed for the return periods of 5 and 50 years based on original wind speed data and that based on wind speed data reconstructed using the MCP method have similar results in the same sampling methods with the extraction method of hourly maximum wind speeds (HMAX) and daily maximum wind speeds (DMAX). The estimates of wind speeds for the return periods of 5 and 50 years based on wind speed data reconstructed using the MCP method increase with the decreasing of sampling data.

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