The accuracy of atmospheric forcing is a critical component for total water level (TWL) prediction and coastal flood management during hurricanes. In this study, three classes of atmospheric inputs, parametric (Holland Model; HM), physics-based models (ECMWF-ERA5, Global Forecast System (GFS), and North American Mesoscale Forecast System (NAM)), and blended (HM+Physics-based), were evaluated during Hurricane Michael (October 2018) in the northeast Gulf of America (GoA). Simulations with and without wave coupling were carried out using Delft3D FM to quantify the contribution of wave-induced forces to TWL and flooding at Tyndall Air Force Base (TAFB) and Mexico Beach. HM captures the hurricane core winds, but underpredicts the far-field winds, whereas the physics-based models underestimate winds >20 m/s by over 50%. Blended forcing rectifies these biases with a decreased normalized root-mean-square error in TWL to as low as 0.05, with NAM-based blending outperforming ERA5- and GFS-based approaches due to a finer (∼12 km) spatial resolution. The physics-based models underpredicted the peak significant wave height (SWH), while the HM model overpredicted peak and underpredicted smaller SWHs. The blended models balanced these errors, enabling Delft3D FM (D-Waves) to reproduce large and small SWHs and to capture the 1D/2D spectra observed west of the hurricane track, with minor energy bias linked to phase shift. Overall, blending high-resolution physics-based with parametric core winds improves surge-wave prediction accuracy. While spatial resolution primarily controls blending skill, efficiency is region-dependent and event-specific. The necessity of blending remains sensitive to the nonlinear interaction between storm intensity, size, track, and geographic location.

AE Elkut, F Shi, JC Dietrich, J Figlus, US Lima, JA Puleo (2026). “Performance of Parametric, Physics-Based, and Blended Approaches for Hurricane Atmospheric Forcing in Storm Surge, Wave, and Flood Modelling.” Ocean Modelling, 203, 102781, DOI: 10.1016/j.ocemod.2026.102781.