Linking the long-term variability in global wave energy to swell climate and redefining suitable coasts for energy exploitation

The sustainability of wave energy linked to the intra- and inter-annual variability in wave climate is crucial in wave resource assessment. In this study, we quantify the dependency of stability of wave energy flux (power) on long-term variability of wind and wave climate to detect a relationship between them. We used six decades of re-analysis wind and simulated wave climate in the entire globe and using two 30-yearly periods, we showed that not only the previously suggested minimum period of 10 years for wave energy assessment appears to be insufficient for detecting the influence of climate variability, but also the selection period for wave energy assessment can lead to an over/underestimation of about 25% for wave power. In addition, we quantified the dependency of rates of change of wave power, wind speed and wave parameters and showed that the change in wave power is mainly a function of change in swell wave climate globally. Finally, we redefined the suitability of global hotspots for wave energy extraction using intra-annual fluctuation, long-term change, and the available wave power for the period of six decades. The results highlight the importance of climate variability in resource assessment, sustainability, and prioritizing the hotspots for future development

Combining methodologies on the impact of inter and intra-annual variation of wave energy on selection of suitable location and technology

In this study, based on 55 years’ worth of high-resolution simulated wave data using numerical modeling off the southern coasts of China, intra-annual and decadal variations of the wave climate and wave energy were evaluated. The results show that it is important to consider a sufficiently long time period for wave energy assessment to take into account the changing climate. The high-resolution wave dataset enabled the quantitative analysis in both nearshore and offshore, and the quantitative analysis was performed in two phases: First, using two different approaches. i.e., “Climate-dependent Sustainability Index” and “Wave Exploitability Index”, the wave power and its short and long-term changes were considered to prioritize the candidate stations for further assessment. Then, a modified “Multi-Criteria Approach” consisting of both sea state and Wave Energy Converters (WECs) was applied to determine the most suitable combination of WEC and location in the domain, which is Wave Dragon in the eastern parts of the domain with the energy production of around 92, 000 MWh for a single device. The results provide the quantitative analysis for different scenarios of development plans in the study area on the selection of appropriate location and technology

Assessment of wave power stability and classification with two global datasets

Global distribution of the wave climate and energy using a re-analysis dataset provides the opportunity to study spatio-temporal variation of different parameters, and offers inputs for future sustainability plans. The study assesses two global scale products ERA5 and ERA-Interim, evaluating differentiation in wave climate and energy parameters. Results compare the performance globally and analyse the rate of change for wave power and its persistence characteristics. Based on results for the spatial distribution and rate of change for wave characteristics, wave power and joint distributions are expected to increase. The study provides novel information with a wave energy development index and rate of change globally, suggesting the most appropriate areas for further assessment based on the discussed criteria

Change of nearshore extreme wind and wave climate in Southeast Africa

Climate change impact assessment is vital in order to investigate not only the change of average wind and wave climate, but also the extreme events. Such kind of events can affect the activities in nearshore areas such as marine operation, as well as on design of coastal and marine structures. In this research, long-term assessment of wind and wave data has been conducted to determine the effect of climate change by comparing the dataset for historical and future projections. The analysis has been done mainly in nearshore areas and the results were discussed in order to evaluate the impact of climate change, quantitatively

Sustainability of wave energy resources in southern Caspian Sea

This study aims to evaluate the wave energy potential and its spatial and temporal variations in the southern Caspian Sea. For this purpose, SWAN model was used to hindcast wave characteristics for 11 years. The wave energy assessment was conducted in four nearshore stations in order to assess the feasibility of wave energy harvesting and locate the most appropriate station. Assessment of seasonal and monthly variations of the mean and maximum wave powers showed that the central station contains the highest values, especially in November; while the north-eastern station has the lowest values with the highest variation of directional distribution of the wave power. Moreover, the seasonal and monthly variability indices indicate a relatively stable wave condition in all stations. The total and exploitable storages of wave energy were also higher in the central station. Therefore, it was concluded that the central station is the most appropriate location for wave energy harvesting. Furthermore, the inter-annual variations of the mean wave power illustrate no significant long-term change in wave power in the southern Caspian Sea. Therefore, considering the relatively stable condition and comparable exploitable storage of wave energy, this area can be a suitable location for developers

Combining methodologies on the impact of inter and intra-annual variation of wave energy on selection of suitable location and technology

In this study, based on 55 years’ worth of high-resolution simulated wave data using numerical modeling off the southern coasts of China, intra-annual and decadal variations of the wave climate and wave energy were evaluated. The results show that it is important to consider a sufficiently long time period for wave energy assessment to take into account the changing climate. The high-resolution wave dataset enabled the quantitative analysis in both nearshore and offshore, and the quantitative analysis was performed in two phases: First, using two different approaches. i.e., “Climate-dependent Sustainability Index” and “Wave Exploitability Index”, the wave power and its short and long-term changes were considered to prioritize the candidate stations for further assessment. Then, a modified “Multi-Criteria Approach” consisting of both sea state and Wave Energy Converters (WECs) was applied to determine the most suitable combination of WEC and location in the domain, which is Wave Dragon in the eastern parts of the domain with the energy production of around 92,000 MWh for a single device. The results provide the quantitative analysis for different scenarios of development plans in the study area on the selection of appropriate location and technology

Spatio-temporal wave climate using nested numerical wave modeling in the northern Indian Ocean

In order to simulate the wave climate in a specific region for different purposes such as climate change impact assessment, wave energy assessment, etc., it is important to consider the long-term variations (Shimura et al., 2015). Due to the scarcity of the wave measurements, numerically modeled wave data are an appropriate alternative to provide the wave characteristics in desired spatial and temporal coverage. There are limited studies which investigated the wave climate in the northern Indian Ocean. Amrutha et al. (2016) studied the wave climate in the eastern Arabian Sea at the west of India by comparison of the results of a nested numerical modeling with buoy data. Kamranzad et al. (2016) also assessed the temporal-spatial variation of wave energy and nearshore hotspots in northern Gulf of Oman based on the locally generated wind waves. In this study, wave modeling performance is investigated in the northern Indian Ocean (NIO) considering long distance swells. A nested wave modeling was utilized in the NIO to discuss the accuracy of wave simulation both temporally (by comparing to buoy dataset) and spatially (by comparing to the satellite altimeter records in the domain). High temporal resolution is important to consider the peak events for extreme value analysis, while the accurate estimation of spatial distribution is important for long-term variation of average wave climate in a domain

Spatio-temporal assessment of climate change impact on wave energy resources using various time dependent criteria

The wave energy resources in the Indian Ocean can be considered as a potential alternative to fossil fuels. However, the wave energy resources are subject to short-term fluctuations and long-term changes due to climate change. Hence, considering sustainable development goals, it is necessary to assess both short-term (intra-annual) variation and long-term change. For this purpose, the simulated wave characteristics were utilized, and the wave power and its variation and change were analyzed in the whole domain and nearshore areas. The short-term fluctuation was investigated in terms of monthly and seasonal variations and the future change was discussed based on absolute and relative changes. Both analyses show that the Southern Indian Ocean, despite experiencing extreme events and having higher wave energy potential, is more stable in terms of both short and long-term variation and change. The assessment of the total and exploitable storages of wave energy and their future change revealed the higher potential and higher stability of the nearshores of the Southern Indian Ocean. It can be concluded that based on various factors, the south of Sri Lanka, Horn of Africa, southeast Africa, south of Madagascar and Reunion and Mauritius islands are the most suitable areas for wave energy extraction

Temporal-spatial variation of wave energy and nearshore hotspots in the Gulf of Oman based on locally generated wind waves

This study aims to assess the wave energy at five coastal stations in the Gulf of Oman using the time series of locally generated wind waves obtained by numerical modeling for 11 years. For this purpose, the spatial, seasonal, monthly, directional, inter-annual of wave energy and power were investigated. The spatial distribution shows that the wave power increases towards the Indian Ocean and the highest mean wave power is located at the eastern station in all seasons. In addition, monthly mean wave power is highest during July and August while the monthly maximum wave power is highest during February at all stations. The ratio of monthly maximum to mean wave power is also the lowest during May to August. Moreover, Monthly Variability Index is the highest in west of the domain where there is no significant wave power potential. In addition, annual wave power as well as total and exploitable wave energies increases from west to east, where the dominant waves propagate from the south, and the exploitable wave energy is approximately 20 times greater than of the central stations