Extreme sea level events result from the joint effects of processes operating on different time scales, including sea level rise (SLR), astronomical tides, non-tidal residuals, the seasonal cycle, and interannual-to-decadal variability. These events threaten coastal cities, ports, and disaster-mitigation infrastructure. The Northwest Pacific accounts for approximately one-third of global tropical cyclone activity, and the El Niño–Southern Oscillation (ENSO) strongly modulates typhoon genesis, tracks, landfall intensity, and associated storm-surge responses. The region is therefore well suited to investigating how climate variability and typhoons jointly influence extreme coastal water levels. Using long-term sea-level records from 58 tide gauges across the Northwest Pacific, we identified extreme events with a percentile-based threshold and decomposed the records into their constituent components. We then analyzed the derived metrics in relation to ENSO indices to assess long-term trends and interannual variability across subregions. Extreme-event occurrence generally increased across the network, with SLR likely acting as the dominant driver. In Southeast Asia, annual extreme-event frequency also exhibited pronounced interannual variability, suggesting that regional risk may be jointly shaped by ENSO phase, typhoon activity, and local shoreline configuration and coastal topography. We will next apply a Bayesian spatial extreme-value model with typhoon track, landfall location, distance from shore, intensity, and impact radius as covariates. The model will estimate station-specific return levels and typhoon-related risk amplification. Through a Bayesian hierarchical framework and spatial random effects, it will borrow strength across neighboring stations and reduce uncertainty associated with sparse extreme-event samples at individual sites. The analysis will quantify spatial heterogeneity in typhoon impacts along the southeastern coast of China, in the Philippines, and across the wider Southeast Asian region. The resulting estimates will support coastal hazard early warning and revisions to design standards for coastal protection infrastructure.