Enhancing Tropical Cyclone Predictions with High-Resolution Wind Fields: A Nested Moving Grid Approach for Hurricanes Florence and Ida

Tropical cyclones pose significant threats to coastal regions, causing extensive damage through high winds, heavy rainfall, and storm surges. Accurate prediction of these phenomena is crucial for effective disaster preparedness and mitigation. Often, storm surge models are driven by parametric vortex models that construct wind fields spatially and temporally using the best track information. However, studies have shown that these models tend to underestimate tropical cyclonic winds beyond a certain radius from the storm’s eye, leading to underestimation of surge and coastal inundation levels. To address this issue, there have been previous efforts to combine wind fields from parametric models and gridded wind datasets to better represent tropical cyclones. However, storm features will still be poorly represented if the combined output is saved at the resolution of a typical large-scale grid, e.g., 0.25° x 0.25°, or larger, while file sizes can become overwhelming if the combined output is saved at a typical storm resolving scale, e.g., 0.01° x 0.01°.

Recently, Luettich et al. (2025) have developed a standalone MATLAB framework for the parametric tropical cyclone model GAHM (Generalized Asymmetric Holland Model: Gao, 2018) and a scheme for blending the output with any large-scale gridded atmospheric fields. In this work, we adopt a nested moving grid method to build storm wind and pressure fields using GAHM that are blended with ERA5 reanalysis fields. The nested, moving grid approach allows for higher resolution storm wind fields compared to ERA5. As a case study, we used this approach to model storm surge and waves for Hurricanes Florence (2018) and Ida (2021), which made landfall along the US east and Gulf coasts, respectively. Simulations were carried out using the ADCIRC+SWAN coupled modeling framework for both hurricanes, and results such as wind speed, water levels, and significant wave heights were compared with in-situ observations to assess model skill. Overall, the results indicate that the new blended approach improves wind fields and water levels compared to runs that use a parametric wind model by itself. Another significant advantage of the nested moving grid method is its ability to include multiple storms in the gridded wind field, allowing for the study of more than one storm over longer time scales.