The Impact of Observed Drag Reduction Over Land on Typhoon Forecasting

Abstract

The surface drag coefficient plays a crucial role in determining the momentum exchange between the Earth’s surface and the atmosphere. Previous studies have observed a tendency for the drag coefficient to decrease at high wind speeds over land, primarily due to the inverse energy cascade. This study aims to examine the impacts of the reduced drag coefficient on the typhoon forecasting skills in terms of the track, the central pressure, and the 10‐m maximum wind speed. Drag reduction is approached through the logarithmic wind profile and a new formula that considers the reduction in roughness length. The results show that the track and the 10‐m maximum wind speed forecasts are improved, but these improvements are primarily evident over plain areas, as the typhoon structure is significantly disrupted by the topography over mountainous areas. Additionally, the reduced drag coefficient results in less dissipation of the typhoon’s wind fields over land. As the wind speeds at coastal areas are enhanced compared with those in operational model, the changes in the Coriolis force are responsible for the track prediction improvement. These findings highlight the importance of parameterizing coherent processes in current numerical models.

A Physical Model for the Observed Inverse Energy Cascade in Typhoon Boundary Layers

“…This, in turn, can lead to the inadequate representations of other turbulence parameters in numerical models. Researchers have identified the sensitivity of typhoon forecasting to turbulence parameters such as the drag coefficient (Shao et al., 2023b) and eddy diffusivity (Ming et al., 2023). Nevertheless, adjustments to these parameters remain empirical.…”

“…Furthermore, parent vortex of typhoons can directly gain energy from turbulence through this inverse energy cascade channel. Given that these dynamics are essential for the maintenance and intensification of typhoons, understanding of the observed inverse energy cascade is crucial for improving turbulence parameterization schemes and typhoon forecasting (Shao et al., 2023b).…”