Recent studies have shown that climate change and global warming considerably increase the risks of hurricane winds, floods, and storm surges in coastal communities. Turbulent processes in Hurricane Boundary Layers (HBLs) play a major role in hurricane dynamics and intensification. Most of the existing turbulence parameterizations in the current numerical weather prediction (NWP) models rely on the Planetary Boundary Layer (PBL) schemes. Previous studies (Zhang 2010; Momen et al. 2021) showed that there is a significant distinction between turbulence characteristics in HBLs and regular atmospheric boundary layers (ABLs) due to the strong rotational effects of hurricane flows. Nevertheless, such differences are not considered in the current schemes of NWPs, and they are primarily designed and tested for regular ABLs.
In this talk, we aim to bridge this knowledge gap by conducting new hurricane simulations using the Weather Research and Forecasting (WRF) model as well as large-eddy simulations. We investigate the role of the PBL parameterizations and momentum roughness length in multiple hurricanes by probing the parameter space of the problem. Our simulations have shown that the most widely used WRF PBL schemes do not capture the hurricane intensification properly and underestimate their intensity.
We will present that decreasing the roughness length close to the values of observational estimates and theoretical hurricane intensity models in high wind regimes (≳ 45 m s-1) led to significant improvements in the intensity forecasts of strong hurricanes. Furthermore, by decreasing the existing vertical diffusion values, on average more than 20% improvements in hurricane intensity forecasts were obtained compared to the default runs. Our results provide new insights into the role of turbulence parameterizations in hurricane dynamics and can be employed to improve the accuracy of real hurricane forecasts. The implications of these results and improvements for coastal resiliency and fluid-structure interactions will also be discussed.
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The Impacts of Vertical Diffusion Parameterizations on Intensifying Hurricane Simulations
Tropical cyclones are one of the deadliest natural disasters in the world that cause significant damage to the environment and infrastructure. The Hurricane Boundary Layer (HBL) plays a major role in hurricane dynamics and its intensification. Most of the existing vertical diffusion parameterizations in the current numerical weather prediction models rely on the Planetary Boundary Layer (PBL) schemes. Previous studies (Momen et al. 2021; Romdhani et al. 2022) showed that there is a significant distinction between turbulence characteristics in HBLs and regular atmospheric boundary layers (ABLs) due to the strong rotational effects of hurricane flows. Nevertheless, such differences are not considered in the current PBL schemes, and they are primarily designed and tested for regular ABLs.
In this talk, we aim to bridge this knowledge gap by conducting real hurricane simulations using the Weather Research and Forecasting (WRF) model. We investigate the role of the PBL height and eddy momentum exchange coefficients in five intensifying hurricanes by probing the parameter space of the problem. Our simulations have shown that the most widely used WRF PBL schemes do not capture the hurricane intensification properly and underestimate their intensity.
We will demonstrate how limiting the amount of the vertical transport of momentum greatly benefits the skill of forecasting in major hurricane simulations. We will also present how changing the height of the PBL significantly impacts the accuracy of the forecasts. By reducing the PBL height, simulated hurricanes become stronger and larger – representing the actual rapid intensification process much more accurately. Not only changes are seen in the predicted wind intensities, but also remarkable impacts are observed in storm size, the radius of maximum wind speed, hurricane track, and minimum sea level pressure. The results of this study provide insights into the role of vertical diffusion parameterizations in hurricane dynamics. Our findings can be used to improve the accuracy of real hurricane forecasts in numerical weather prediction models.
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- Award ID(s):
- 2228299
- NSF-PAR ID:
- 10466620
- Publisher / Repository:
- https://ams.confex.com/ams/103ANNUAL/meetingapp.cgi/Paper/415851
- Date Published:
- Format(s):
- Medium: X
- Location:
- Denver, USA
- Sponsoring Org:
- National Science Foundation
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