Teleconnection effects drive significant variations in the frequency of extreme temperature, precipitation, and wind speed events. This study evaluates extreme climate events in East and Southeast Asia under the influence of major teleconnection indices—Arctic Oscillation (AO), North Atlantic Oscillation (NAO), Niño 3.4 (NINO3.4), and Dipole Mode Index (DMI). Using generalized extreme value (GEV) modeling, quantile-based evaluations, lagged correlation analysis, and composite event analysis, the research reveals intricate regional impacts. GEV modeling effectively characterizes the distribution and intensity of annual maximum daily extremes, highlighting heightened sensitivity to wind extremes in coastal cities like Taipei and Hong Kong, and increased vulnerability to temperature and precipitation extremes in inland cities like Bangkok and Phnom Penh. AO and NAO are shown to exert immediate effects, influencing short-term variations in East Asia, while NINO3.4 and DMI demonstrate delayed impacts, significantly affecting extreme precipitation and wind patterns in Southeast Asia. High-percentile extremes (90th% and 99th%) are found to be more sensitive to lagged teleconnection effects, particularly at short-term lags. Composite event analysis identifies cities such as Phnom Penh, Bangkok, and Tokyo as hotspots for multi-factor extreme events, including temperature-precipitation and temperature-wind combinations. These findings underscore the complex interplay of teleconnections, monsoonal systems, and local atmospheric dynamics in shaping regional climate variability, offering valuable insights for risk assessment and adaptation strategies.