Ensemble forecasting is a promising tool to aid in making informed decisions against risks of coastal storm surges. Although tropical cyclone (TC) ensemble forecasts are commonly used in operational numerical weather prediction systems, their potential for disaster prediction has not been maximized. Here we present a novel, efficient, and practical method to utilize a large ensemble forecast of 1000 members to analyze storm surge scenarios toward effective decision making such as evacuation planning and issuing surge warnings. We perform the simulation of TC Hagibis (2019) using the Japan Meteorological Agency’s (JMA) non-hydrostatic model. The simulated atmospheric predictions were utilized as inputs for a statistical surge model named the Storm Surge Hazard Potential Index (SSHPI) to estimate peak surge heights along the central coast of Japan. We show that Pareto optimized solutions from an ensemble storm surge forecast can describe potential worst (maximum) and optimum (minimum) storm surge scenarios while exemplifying a diversity of trade-off surge outcomes among different coastal places. For example, some of the Pareto optimized solutions that illustrate worst surge scenarios for inner bay locations are not necessarily accountable for bringing severe surge cases in open coasts. We further emphasize that an in-depth evaluation of Pareto optimal solutions can shed light on how meteorological variables such as track, intensity, and size of TCs influence the worst and optimum surge scenarios, which is not clearly quantified in current multi-scenario assessment methods such as those used by JMA/National Hurricane Center in the United States.