Projection of spatiotemporal variability of wave power in the Persian Gulf by the end of 21st century: GCM and CORDEX ensemble

Abstract

This study investigates future variability of wave power in the Persian Gulf. The contribution of this paper is twofold: (a) to evaluate spatiotemporal resolutions, downscaling techniques and global circulation model (GCM) selection impacts running multi-climate models, and (b) to project wave energy resources and its variability by the end of 21st century using RCP4.5 and RCP8.5 as two different representative concentration pathways (RCPs). The SWAN (Simulating Waves Nearshore) model forcing with near surface wind components was employed for wave simulation. The numerical wave model was calibrated and validated using wave measurements by two buoys prior to wave energy computations. The results of wave models obtained from different climate models showed a wide range of variety for different climatic resources associated with GCM selection, temporal and spatial resolutions and downscaling approach. Outputs of the wave model forcing with 3 hourly wind data of CMCC-CM and CORDEX-MPI (Max Plank Institute) with daily temporal resolution were recognized as the models with the best performance. Using a weighted average of these two models, the wave characteristics were obtained and wave energy were computed for the historical and future periods. Temporal distribution of energy shows highly intra-annual and seasonal variability when the mean wave power for the strongest month exceeds 1000 Watt per meter that is 10 times higher than the mean wave power in the weakest month. Similarly, a strong spatial variability in wave power distribution was revealed where the middle part of the Gulf has found to have the highest energy and the eastern and northwestern regions have the lowest energy. The projections illustrated a decreasing trend on future wave energy up to 40% in the Iranian coastlines and lower rate of changes in the southern stripe of the study area.

Introduction

There is a growing demand and popularity to use renewable energy resources due to their wide availability and environmental compatibility. Moreover, they are considered as an appropriate alternative to fossil fuels to attenuate greenhouse gas emissions and impacts. Recently, extraction of wave energy as a renewable energy resource attracted attention of many researchers and a large number of devices were designed and tested for this purpose. An abundance of wave energy due to big oceans and seas covering the earth’s surface implies great potential of this type of renewable energy for increasingly demand to clean energy in the future. However, their spatiotemporal distribution and their sustainability under future warmer conditions require regional studies to have a thorough understanding of the subject.

Wave energy resources have been evaluated for different locations all over the world and the results were promising to employ this type of energy for future power supply (Kamranzad et al., 2016, López et al., 2015, Penalba et al., 2018, Rashid and Hasanzadeh, 2011, Rodriguez-Delgado et al., 2019, Rusu and Soares, 2012, Sierra et al., 2014, Sierra et al., 2017). More interestingly, Bergillos et al. (2018) demonstrated that wave energy convertor farms can play an important role on coastal protection along with its energy supply role. Furthermore, Curto et al. (2019) showed suitability of sea wave power to increase the energy sustainability of small islands through a combined system of solar, wind and wave energies. Morim et al. (2019) explored temporal variability of wave power extracted from wave energy convertors in the central shelf of New South Wales, Australia. They found that the intra- and inter-annual variability in the wave power change the energy production remarkably. However, these studies have not considered wave energy sustainability and variability under future climatic scenarios.

Climate change is an ongoing issue expected to affect different atmospheric and oceanic phenomena among others. Considering climate change impacts on renewable energy resources (e.g., wind, wave, and tidal power), many studies employed different representative concentration pathways (RCPs) and formerly emission scenarios obtained from different global/regional circulation models (GCMs/RCMs). The results revealed high dependency of the parameters on the spatial characteristics in which in some regions a decreasing trend was projected and for some other regions an increasing trend was predicted (Carvalho et al., 2017, Davy et al., 2018, Falchetta et al., 2019, Reeve et al., 2011). Sierra et al. (2017) compared different climatic scenarios of IPCC 4th assessment to explore future variation in wave energy in Menorca, Spain. The results indicated a similar spatial and directional distribution of wave energy but slightly lower annual and seasonal power for future period against those of the historical simulations. Generally, few studies devoted to address climate change impacts on wave energy resources. As the wave energy is directly dependent on the wave height and period, studies exploring climate change impacts on wave characteristics are useful to some extent to find trends in wave energy and its variability under future climatic conditions (Aarnes et al., 2017). However, it should be noticed that regional studies dealing with climate change impacts on wave characteristics (such as significant height and period) are more important for nearshore areas due to their importance on coastal erosion and geomorphology. On the other hand, it is a common practice to investigate wave energy on offshore regions. Therefore, model specifications and interesting locations may differ based on the purpose of the study.

There are a large number of GCMs/RCMs projecting climatic variables under different representative concentration pathways (RCPs). Each RCPs consists of different assumptions about energy consumption, population, economic, and land use by the end of 21st century. Wang et al. (2015) demonstrated that for wave climate projection, uncertainty associated with GCM selection can be much higher than the uncertainty due to RCP selection. For regional studies, bias correction or downscaling is a common approach to modify GCM simulations considering local conditions. Aside from GCMs, the COordinated Regional climate Downscaling EXperiment (CORDEX) is an effort to generate regional climate models (RCMs) with finer spatial resolution and more reliable predictions gaining different downscaling techniques and GCMs outputs as lateral boundary conditions over the area. Therefore, to project wave energy variability under future climatic conditions, consistency and reliability of the GCM/RCM simulations should be taken under consideration. To do that, efficiency of different GCMs/RCMs are usually evaluated against the reference data during historical (control) period to select the suitable models.

This study is therefore aimed to employ appropriate GCM/RCM simulations for exploring the future variability of wave energy in the Persian Gulf. Prior to the wave energy projection, efficiency of the CORDEX outputs and different GCMs with different spatial and temporal resolutions have been evaluated for the historical wave simulations. A distributed Weibull approach is used for downscaling of near surface wind components of the GCMs. The numerical wave model is calibrated using wave records in deep water conditions to efficiently simulate offshore wave characteristics accordingly to meet the purpose of the study. Afterwards, the climatic models resulting the best wave simulations are selected to project future changes of wave energy by the end of 21st century (2081–2100). The seasonal, inter- and intra-annual variability of the wave energy over the Gulf are analyzed. Moreover, some energy hotspots in the area are selected to provide more details about the future variability of the wave power and its directional distribution under two future scenarios of RCP4.5 and RCP8.5.