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Correlation Analysis between Wave Power and Seawater Temperature and Salinity

机译:波浪力量与海水温度与盐度的相关分析

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Although it has been studied extensively for more than four decades, same as wind and solar energy, wave energy harvesting technology has lagged significantly when compared with other renewable energy technologies. Wave energy is directly affected by wave period and wave height; however, it is also very important to fully understand the correlation between wave energy with other factors. Physical properties of seawater not only influence the behavior of ocean circulation, but also directly or indirectly affect the generation of wave energy. In this project, five years of data related to salinity, surface temperature, and other meteorological factors used for calculating wave energy were analyzed. A geographical information system based spatial and temporal analysis method, which was developed by integrating MATLAB and ArcGIS spatial analysis functions, was used to determine the correlations between selected factors and wave energy. There are strong positive and negative correlations between these two factors and wave power in the GoM, while the regions with positive and negative correlations are mixed up in the most areas of the GoM without clear boundaries between each other. The results also show that the correlation patterns between two factors and wave power are different with inconsistent monthly and seasonal patterns.
机译:虽然已经广泛研究了四十多年,但与风能和太阳能相同,与其他可再生能源技术相比,波能量收集技术已经显着滞后。波能量受波段和波浪高度影响;然而,充分了解波能与其他因素之间的相关性也是非常重要的。海水的物理性质不仅影响了海洋循环的行为,还影响了波能的产生或间接地影响波能的产生。在该项目中,分析了与盐度,表面温度和用于计算波能的其他气象因子相关的五年数据。通过集成MATLAB和ArcGIS空间分析功能开发的基于地理信息系统的空间和时间分析方法,用于确定所选因素和波能之间的相关性。在GOM中的这两个因素和波力之间存在强烈的正面和负相关,而具有正和负相关的区域在GOM的大部分区域中混合在没有透明边界的情况下。结果还表明,两个因素和波力之间的相关模式与月度和季节性模式不一致。

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