Impacts of Large-Scale Offshore Wind Farms on Tropical Cyclones: A Case Study of Typhoon Hato

Abstract

Abstract With the rising global demand for renewable energy sources, a great number of offshore wind farms are being built worldwide, as well as in the northern South China Sea. There is, however, limited research on the impact of offshore wind farms on the atmospheric and marine environment, particularly tropical cyclones, which frequently occur in summertime in the South China Sea. In this paper, we employ the Weather Research and Forecasting (WRF) Model to investigate the impacts of large-scale offshore wind farms on tropical cyclones, using the case of Typhoon Hato, which caused severe damage in 2017. Model results reveal that maximum wind speeds in coastal areas decrease by 3–5 m s−1 and can reach a maximum of 8 m s−1. Furthermore, the wind farms change low-level moisture convergence, causing a shift in the precipitation center toward the wind farm area and causing a significant overall reduction (up to 16%) in precipitation. Model sensitivity experiments on the area and layout of the wind farm have been carried out. The results show that larger wind farm areas and denser turbine layouts cause a more substantial decrease in the wind speed over the coast and accumulated precipitation reduction, further corroborating our findings. Significance Statement This study holds significant implications for developing offshore wind farms in tropical cyclone-prone regions like the South China Sea. By focusing on Typhoon Hato as a case study, the research sheds light on the previously understudied relationship between large-scale offshore wind farms and tropical cyclones. The observed decrease in coastal wind speeds and altered precipitation patterns due to wind farm presence highlights the potential for mitigating cyclone-related risks in these regions. Additionally, the study’s sensitivity experiments underscore the importance of careful planning and design in optimizing wind farm layouts for maximum impact reduction. This research contributes vital insights into sustainable energy infrastructure development while minimizing environmental and meteorological risks in cyclone-prone areas.