Characterizing the Impacts of Horizontal Turbulence and Surface Roughness Length Parametrizations on Real Hurricane Dynamics and Tracks

Hurricanes are highly complex geophysical flows that have caused billions of dollars in damage in recent years. Despite the significance of these extreme weather events, the turbulence and surface friction mechanisms that derive the dynamics of hurricane flow systems are poorly understood and ineffectively parameterized in numerical weather prediction (NWP) models. Thus, it is imperative to improve hurricane forecasts to mitigate their economic ramifications. The objective of this study is to bridge these knowledge gaps by assessing the accuracy and deficiencies of existing turbulence models in NWPs for hurricane forecasts and investigate the trends of hurricane tracks subject to changing the surface roughness. Weather and Research Forecasting (WRF) Model is employed to conduct a suite of 5 real hurricane simulations by varying the grid resolution, turbulence models, and horizontal mixing length values, and 6 real hurricanes and non-hurricane cases are simulated by varying the surface roughness lengths. It is found that increasing the grid resolution considerably improves the wind intensity forecasts in all hurricanes regardless of the employed turbulence model but has lower effects on track error. Moreover, decreasing the default horizontal mixing length values in WRF remarkably improves the wind intensity forecasts, indicating that existing parameterizations are overly dissipative for hurricane flows, and thus, generate weaker vortex compared to observations. These deficiencies are shown to stem from the crude horizontal mixing-length parameterization in WRF that is prescribed as only a function of grid size without considering the physics of the flows. Furthermore, it is found that hurricane tracks tend to shift more toward the west by decreasing the default roughness length and vice versa. This behavior is shown to be likely due to the changes in environmental flow patterns. We thus, provide new insights into the role of turbulent fluxes in simulated hurricane evolutions that can be useful to advance the turbulence and surface layer parameterizations for hurricane forecasts in NWP models.