Better understanding of the global wave climate is required to inform wave energy device design and large-scale deployment. Spatial variability in the global wave climate is analysed here to provide a range of characteristic design wave climates. K-means clustering was used to split the global wave resource into 6 classes in a device agnostic, data-driven method using data from the ECMWF ERA5 reanalysis product. Classification using two sets of input data were considered: a simple set (based on significant wave height and peak wave period) and a comprehensive set including a wide range of relevant wave climate parameters. Both classifications gave resource classes with similar characteristics; 55% of tested locations were assigned to the same class. Two classes were low energy, found in enclosed seas and sheltered regions. Two classes were moderate wave energy classes; one swell dominated and the other in areas with wave action often generated by more local storms. Of the two higher energy classes; one was more often found in the northern hemisphere and the other, most energetic, predominantly on the tips of continents in the southern hemisphere. These classes match existing regional understanding of resource. Consideration of publicly available device power matrices showed good performance was primarily realised for the two highest energy resource classes (25–30% of potential deployment locations); it is suggested that effort should focus on optimising devices for additional resource classes. The authors hypothesise that the low-risk, low variability, swell dominated moderate wave energy class would be most suitable for future exploitation.

需要更好地了解全球波浪气候，才能为波浪能设备的设计和大规模部署提供信息。本文分析了全球波浪气候的空间变异性，以提供一系列特征性设计波浪气候。使用来自ECMWF ERA5重新分析产品的数据，在设备不可知的数据驱动方法中，使用K均值聚类将全局波动资源分为6类。考虑使用两组输入数据进行分类：一个简单的组（基于重要的波高和波峰周期）和一个综合的组，其中包括各种相关的波浪气候参数。两种分类都给出了具有相似特征的资源类别。55％的测试位置被分配到同一班级。在封闭的海域和庇护区中发现了两类低能量能源。有两个类别是中等波浪能类别；一种浪潮占主导地位，另一种浪潮地区往往是由更多局部风暴产生的波浪作用。在两个较高的能量等级中；一种更常见于北半球，另一种最活跃，主要位于南半球各大洲的尖端。这些课程与现有的区域资源理解相匹配。对公开可用的设备功率矩阵的考虑表明，良好的性能主要是针对两种最高的能源资源类别（潜在部署位置的25％至30％）实现的；建议将精力集中在为其他资源类别优化设备上。作者假设低风险，低可变性，溶胀为主的中波能级将最适合将来的开采。一种浪潮占主导地位，另一种浪潮地区往往是由更多局部风暴产生的波浪作用。在两个较高的能量等级中；一种更常见于北半球，另一种最活跃，主要位于南半球各大洲的尖端。这些课程与区域对资源的现有理解相匹配。对公开可用的设备功率矩阵的考虑表明，良好的性能主要是针对两种最高的能源资源类别（潜在部署位置的25％至30％）实现的；建议将精力集中在为其他资源类别优化设备上。作者假设低风险，低可变性，溶胀为主的中波能级将最适合将来的开采。一种浪潮占主导地位，另一种浪潮地区往往是由更多局部风暴产生的波浪作用。在两个较高的能量等级中；一种更常见于北半球，另一种最活跃，主要位于南半球各大洲的尖端。这些课程与现有的区域资源理解相匹配。对公开可用的设备功率矩阵的考虑表明，良好的性能主要是针对两种最高的能源资源类别（潜在部署位置的25％至30％）实现的；建议将精力集中在为其他资源类别优化设备上。作者假设低风险，低可变性，溶胀为主的中波能级将最适合将来的开采。