Dynamic conditions occur in the coastal ocean during severe storms. Forecasting these conditions is challenging, and large-scale numerical models require significant computing power. In this paper, we describe a real-time modelling system (DUNEX-RT), developed in support of the DUring Nearshore Event eXperiment (DUNEX) in North Carolina, USA. The model is run with wave, current, and water level boundary conditions from larger-scale models, and provides 36-hour forecasts of significant wave height, depth-averaged velocity, and water levels every 6-hours using Delft3D-SWAN. Observations and forecasts run at different times are compared and communicated via an interactive website to verify model performance in real-time and to visualize uncertainty from changing inputs. Here, we evaluate model sensitivity to inputs from different atmospheric hindcasts and forecasts for Hurricane Dorian (2019). The real-time model had relatively low errors across the system, indicating that this novel approach can be applied to forecast other areas of the coastal ocean.