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Forecasting hurricanes is critically important for mitigating their devastating impacts caused by wind damage, storm surges, and flooding. Despite remarkable advancements in numerical weather prediction (NWP) models, such as the Weather Research and Forecasting (WRF) model, accurate hurricane forecasts remain challenging likely due to inaccurate physical parameterizations of complex dynamics of these storms. One major issue of these models is related to their Planetary Boundary Layer (PBL) schemes, which are not typically designed for hurricane flows with strong rotation. Previous studies have shown that the existing PBL schemes of hurricane simulations are often overly dissipative, leading to underestimations of the storm intensity (Matak and Momen 2023; Romdhani et al. 2022). Our recent research (Khondaker and Momen 2024) demonstrated that reducing diffusion in these models improved the hurricane’s intensity and size forecasts by more than ~30% on average in four considered major hurricanes. This reduced diffusion is due to the strong rotational nature of hurricanes, which suppresses turbulence and produces smaller eddies compared to regular PBLs (Momen et al. 2021). While prior studies showed that decreasing the vertical diffusion significantly improves major hurricane intensity forecasts, they mostly relied on simplified and often invariable adjustments of vertical diffusion such as multiplying it by a constant coefficient. The objective of this study is to address this issue by introducing a rotation-based variable adjustment of diffusion to account for the strong rotational nature of tropical cyclone (TC) dynamics. To this end, we will present multiple real strong and weak hurricane simulations using the Advanced Research WRF (ARW) model in the US. We modified the vertical eddy diffusivity based on the relative vorticity to accommodate the rotational dynamics of TCs in PBL schemes. While the default model significantly underpredicts hurricane intensity, our new adjustments outperform the default schemes for these strong hurricanes (see, e.g., attached fig. a), with notable improvements in track and minimum sea level pressure accuracy. This modification also remarkably increases the inflow in hurricanes compared to default models and leads to the intensification of the TC vortex (see, e.g., attached fig. b,c). Our newly adjusted model matched more closely with dropsonde, and satellite observations compared to the default WRF’s PBL schemes. These modifications to the PBL schemes make them more physics-based adjustments compared to previous treatments, offering valuable insights for improving hurricane forecasts in NWP models. References: Khondaker, M. H., and M. Momen, 2024: Improving hurricane intensity and streamflow forecasts in coupled hydro-meteorological simulations by analyzing precipitation and boundary layer schemes. J Hydrometeorol, https://doi.org/10.1175/JHM-D-23-0153.1. Matak, L., and M. Momen, 2023: The Role of Vertical Diffusion Parameterizations in the Dynamics and Accuracy of Simulated Intensifying Hurricanes. Boundary Layer Meteorology, https://doi.org/10.1007/s10546-023-00818-w. Momen, M., M. B. Parlange, and M. G. Giometto, 2021: Scrambling and Reorientation of Classical Atmospheric Boundary Layer Turbulence in Hurricane Winds. Geophysical Research Letters, 48, https://doi.org/10.1029/2020GL091695. Romdhani, O., J. A. Zhang, and M. Momen, 2022: Characterizing the Impacts of Turbulence Closures on Real Hurricane Forecasts: A Comprehensive Joint Assessment of Grid Resolution, Horizontal Turbulence Models, and Horizontal Mixing Length. Journal of Advanced Modeling Earth System, 14, https://doi.org/10.1029/2021ms002796. 

Hurricanes have been the most expensive natural catastrophe in the United States causing significant damages and disastrous floods. Considering the increased projected destructiveness of future hurricanes due to global warming, a reliable hurricane forecasting model is a national priority. Despite significant enhancement in weather prediction models, hurricane-induced flood forecasts are not sufficiently accurate yet. This inadequacy could be attributed to inaccurate hurricane intensity and track forecasts which can be due to improper physical parameterizations of unique hurricane dynamics. Previous studies have shown that remarkable differences exist in the dynamics of hurricanes compared to regular atmospheric boundary layers (Momen et al. 2021; Li et al. 2023; Matak and Momen 2023). These differences are due to strong rotational effects in hurricanes that are not represented in current turbulence and planetary boundary layer (PBL) parameterization schemes (Romdhani et al. 2022). These discrepancies in different physical schemes can cause improper hurricane structure, trajectory, intensity, and precipitation; ultimately leading to inaccurate hurricane-induced flood forecasts. It is not well known how adjusting PBL dynamics can influence hydro-meteorological forecasts in hurricanes. In this talk, we seek to bridge this knowledge gap by coupling Advanced Weather Research and Forecasting (WRF-ARW) with the hydrological model WRF-Hydro to simulate multiple hurricanes in the US. We will first show the impacts of various PBL, microphysics, and cumulus parameterizations on the accuracy of real hurricane intensity, track, and flood forecasts. All these runs will be conducted coupled with the WRF-Hydro model, which is extensively calibrated for three coastal regions in the US using multiple USGS gauges. The best-performing parameterizations will then be determined through a comprehensive sensitivity test. We will next present new adjustments to the default PBL schemes of WRF that enhance hurricane intensity forecasts. Following (Matak and Momen 2023), the default vertical diffusion of WRF is reduced to enhance hurricane intensification. Then, the impacts of these adjustments and hurricane dynamics improvements on hurricane-induced flood forecasts are quantified. For example, the attached figure shows an example of our simulations. By reducing the default diffusion, the intensity of hurricanes increases, and their size decreases compared to the default model. This remarkably influences hurricane precipitation rate and aerial distribution. Intensified hurricanes were shown to generate more intense and localized precipitation. This improved representation of hurricane dynamics led to better flood forecasts for the considered hurricanes. In total, we found that by reducing the vertical diffusion, hurricane intensity forecasts were enhanced by ~40% on average compared to the default models. This led to ~16% and 34% improvements in streamflow bias and correlation forecasts, respectively. This research provides new insights into the effects of PBL dynamics on hurricane streamflow forecasts. These new adjustments play a vital role in improving the hurricane and streamflow forecasts in coupled hydro-meteorological models. References: Li, M., J. A. Zhang, L. Matak, and M. Momen, 2023: The Impacts of Adjusting Momentum Roughness Length on Strong and Weak Hurricane Forecasts: A Comprehensive Analysis of Weather Simulations and Observations. Mon Weather Rev, 151, 1287–1302, https://doi.org/10.1175/MWR-D-22-0191.1. Matak, L., and M. Momen, 2023: The Role of Vertical Diffusion Parameterizations in the Dynamics and Accuracy of Simulated Intensifying Hurricanes. Boundary Layer Meteorol, https://doi.org/10.1007/s10546-023-00818-w. Momen, M., M. B. Parlange, and M. G. Giometto, 2021: Scrambling and Reorientation of Classical Atmospheric Boundary Layer Turbulence in Hurricane Winds. Geophys Res Lett, 48, https://doi.org/10.1029/2020GL091695. Romdhani, O., J. A. Zhang, and M. Momen, 2022: Characterizing the Impacts of Turbulence Closures on Real Hurricane Forecasts: A Comprehensive Joint Assessment of Grid Resolution, Horizontal Turbulence Models, and Horizontal Mixing Length. J Adv Model Earth Syst, 14, https://doi.org/10.1029/2021ms002796.