Evaluation of the near future wave energy resources in the Black Sea under two climate scenarios

Liliana Rusu

Renewable Energy, 2019, vol. 142, issue C, 137-146

Abstract: The objective of this study is to evaluate the near future wave power resources (2021–2050) in the Black Sea, based on the results coming from a wave modelling system forced with wind fields provided by a Regional Climate Model (RCM). Such wind fields have been produced in the framework of the EURO-CORDEX experiment. They cover the entire European domain and have a resolution of 0.11°. Two different wind fields are considered in the wave model simulations, according to two Representative Concentration Pathways (RCPs) scenarios, namely RCP4.5 and RCP8.5. The SWAN (Simulating Waves Nearshore) model, which has been implemented over entire the Black Sea basin, is considered for the wave energy predictions. Furthermore, in order to estimate the impact of climate change on the wave energy resources in the Black Sea basin, the results obtained in the near future 30-year period (covering the early 21st century) are compared with historical data. These are the wave energy resources resulted from SWAN model simulations performed also for a 30-year (1976–2005) time-slice. Thus, these historical wave energy resources are obtained using historical RCM wind fields to force the wave model. The results show an increase in the range 0.05–0.18 kW/m (a rise of 5–16%) of the mean wave power under RCP4.5 scenario in almost all the western part of the Black Sea and also in the north-eastern area, while under RCP8.5 is quite double in. On the other hand, the linear regressions fitted to the annual means computed to each 30-year time-slice in 8 reference points did not indicate significant trends.

Keywords: Climate change; Wave power; SWAN; Black Sea; Near future projection (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (14)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:142:y:2019:i:c:p:137-146

DOI: 10.1016/j.renene.2019.04.092

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