ENSO-related variability in typhoon-induced high-wave exposure along the Guangdong coast

Typhoon-generated high waves are a recurrent coastal hazard along Guangdong, southern China, however, the extent to which the El Niño–Southern Oscillation (ENSO) can inform annual-scale coastal exposure remains uncertain. This study integrates hourly ERA5 wave and wind data (1979–2025) from six coastal-shelf grid points, tropical cyclone (TC) best track records from the China Meteorological Administration, and NOAA Oceanic Niño Index (ONI) data. A site-specific 95th-percentile event catalogue comprising 1,249 site-events and a regional TC-track sample of 542 TCs entering within 700 km of the site network are analysed at annual and event scales. Analyses reveal that ENSO conditions significantly influence annual patterns of typhoon-induced wave exposure. At the annual scale, the TC-season ONI-window composite is negatively associated with site-event frequency (r = −0.29, p = 0.048) and cumulative wave exceedance (r = −0.41, p = 0.004). Mean annual cumulative exceedance is 937.6 m·h in La Niña years and 499.3 m·h in El Niño years, although substantial interannual variability remains. Track diagnostics identify a robust westward shift in mean TC genesis longitude during La Niña, whereas the phase difference in mean nearest distance is small and uncertain. At the event-scale, regression analyses of 1,242 site-events (clustered into 318 parent-TC; R² = 0.292) identified nearest TC distance and TC wind velocity as the strongest predictors of peak significant wave height (Hs). In contrast, the standardized ONI coefficient is weak and not conventionally significant (−0.063, p = 0.066), highlighting the limited direct influence of ENSO on individual event severity. These findings indicate the scale-dependent impact of ENSO: ENSO variability is more clearly associated with annual TC-wave occurrence and cumulative coastal exposure than with the peak Hs of individual events. ENSO information can offer valuable climatic context to support seasonal coastal hazard preparedness. However, it should not be regarded as a deterministic forecasting tool or as a replacement for event-specific observations, real-time forecasts, or detailed engineering design analyses.