Wave energy assessment based on reanalysis data calibrated by buoy observations in the southern South China Sea

Abstract

This study assesses wave energy by combining long-term model reanalysis data with in situ observations in a multi-island region. A buoy was deployed in the center area of the southern South China Sea (SCS) for 16 consecutive months. Neural network models are introduced to calibrate the significant wave height and the mean wave period of the European Center for Medium-Range Weather Forecasts (ECMWF) ERA5 reanalysis data. Based on the calibrated reanalysis data, wave energy potential in the region is assessed. The results show relatively available wave resources from October to February in climatology, with an average energy density higher than 5 kW m−1 and an available level frequency higher than 50%. Wave energy potential is relatively poor in other months. In the last 40 years, the wave energy density, available level frequency, and rich level frequency have shown significant increasing trends, consistent with the wind enhancement in the northeast SCS. It is suggested that the growth trend of waves in the northeast SCS may spread to the south region as swell propagation. The analysis emphasizes that there can be significant differences in the results of wave energy assessments, whether the data are calibrated or not. Therefore, the data accuracy needs to be fully evaluated when adopting model results for the planning and utilization of wave energy in such region.

Keywords

• Wave energy
• The southern South China Sea
• Neural network
• Reanalysis data
• Buoy
• Multiisland region