Abstract Understanding changes in the hazard component of climate risk is important to inform societal resilience planning in a changing climate. Here, we examine local changes in wind speed, rainfall, and flooding related to tropical cyclones (TCs) and compare them across statistical and dynamical modeling approaches. Our focus region is the Delaware River Basin, located in the northeastern United States. We pair event-based downscaling with large ensemble climate model information to capture the details of extreme TC wind, rain, and flooding, and their likelihood, in a changing climate. We identify local TCs in the Community Earth System Model 2 Large Ensemble (CESM2-LENS). We find fewer TCs in the future, but these future storms have higher wind speeds and are wetter. We also find that TCs produce heavier 3-day precipitation distributions than all other summertime weather events, with TCs constituting a larger percentage of the upper tail of the full precipitation distribution. With this information, we identify a small collection of 200-year return events and compare the resulting TC rain and wind across dynamical and statistical downscaling methods. We find that dynamical downscaling produces peak rain rates far higher than CESM or the statistical downscaling method. It can also produce quite different future changes in precipitation totals for the small set of events considered here. This leads to vastly different flood responses. Overall, our results highlight the need to interpret future changes of event-based simulations in the context of downscaling method limitations.