Impact of Large-Scale Meteorological Patterns on Offshore Wind Energy Variability and Extreme Wind Events in China

Abstract

Offshore wind energy exhibits strong spatiotemporal variability fundamentally driven by large-scale meteorological patterns (LSMPs), but the mechanisms linking LSMPs to both wind energy variability and extreme wind events remain insufficiently understood. Focusing on the offshore region of China, this study uses the self-organising map algorithm to identify the dominant seasonal LSMP transition pathways affecting wind energy and to establish explicit links between specific LSMPs and the spatial distribution of extreme wind events. The results show that wintertime transitions involving Siberian High-enhanced pathways contribute to persistently strong winds and stable power output. In other seasons, dominant LSMP evolution pathways lead to pronounced spatial redistribution of wind energy, causing the optimal regions for offshore wind power generation to alternate between the northern and southern seas. LSMPs also regulate the occurrence of extreme wind speed events, as regions with positive capacity factor anomalies typically experience lower frequencies of low wind speed extremes. A further decomposition of the interannual variability in seasonal capacity factor and the frequency of extreme wind speed events shows that changes in wind energy characteristics under a given LSMP (within-pattern component) are the primary drivers of their interannual variability. These findings suggest that future research should pay greater attention to how evolving thermal gradients and boundary-layer conditions under global warming may modulate offshore wind energy within individual circulation patterns.