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Extreme weather events such as hurricanes and heatwaves could cause significant damage to the economy and urban resiliency. Accurate meteorological forecasts of these extreme events could mitigate some aspects of their damage by providing precautionary alerts. The weather forecasts heavily rely on the parameterization of the planetary boundary layer (PBL), which is the lowest layer of the atmosphere that extends up to ~1 km above the surface. In hurricanes, the rotational nature of flows can suppress turbulence; however, such effects are neglected in the conventional PBL schemes, leading to over-diffusive simulations and inaccurate hurricane intensity, size, and track forecasts. In urban areas, complex surface heterogeneities and the Urban Heat Island (UHI) effects are inadequately represented by current PBL models, causing inaccurate forecasts of atmospheric stability, aerosol transport, and wind speeds. To address these issues, the dissertation characterizes the impacts of PBL parameterizations on three problems: hurricane forecasts, air quality forecasts in cities, and wind forecasts in heterogeneous urban areas. To this end, dissertation systematically explored modifications to the existing PBL schemes, urban models, and roughness parameterizations within the Weather Research and Forecasting (WRF) model. More than 500 WRF simulations encompassing major hurricane cases and multiple U.S. cities were performed by varying grid resolutions, eddy diffusivity, UHI magnitudes, and surface roughness configurations. By reducing the vertical diffusion in hurricane simulations, hurricane intensity forecasts improved by ~38% compared to the default PBL schemes in five cases, demonstrating the deficiency of existing parameterizations for rotating cyclonic flows. Our urban simulations also showed that incorporating proper UHI representations in Houston and Dallas led to ~50% and ~12% enhancements in particulate matter and ozone forecasts, respectively, as more realistic nighttime warming prevented excessive aerosol accumulation. Additionally, a novel City-wide Enhanced Directional-Adjusted Roughness (CEDAR) parameterization was introduced that improved surface wind forecasts by ~54% and enhanced the prediction of vertical profiles of winds by ~12%, demonstrating the significance of accounting for upwind surface heterogeneities. The dissertation results collectively highlight that improving PBL processes in weather/climate models can considerably reduce forecasting errors in regular and extreme weather events. Our findings guide the future development of advanced PBL schemes that account for rotation, UHI effects, and surface roughness, thereby improving weather and air quality predictions across diverse environments. The results will be helpful to enhance operational forecasting models, which ultimately could mitigate public health risks, and optimize urban design and hurricane preparedness strategies. 

Rotation in hurricane flows can highly affect the dynamics and structure of hurricane boundary layers (HBLs). Recent studies (Momen et al. 2021) showed that there is a significant distinction between turbulence characteristics in hurricane and regular atmospheric boundary layers due to the strong rotational effects of hurricane flows. Despite these unique features of HBLs, the current planetary boundary layer (PBL) and turbulence schemes in numerical weather prediction (NWP) models are neither specifically designed nor comprehensively tested for major hurricane flows. In this talk, we will address this knowledge gap by characterizing the role of horizontal and vertical eddy diffusion under different PBL schemes in simulated hurricane intensity, size, and track. To this end, the results of multiple simulated hurricane cases will be presented using the Weather Research and Forecasting (WRF) model. The impacts of changing the grid resolution, horizontal turbulence, PBL scheme, vertical eddy diffusivity, and PBL height on hurricane dynamics and accuracy will be characterized. The results indicate that the current turbulence and PBL schemes in WRF are overly diffusive for simulating major hurricanes (Romdhani et al. 2022; Li et al. 2023) primarily since they do not account for turbulence suppression effects in rotating hurricane flows. We will also show new suites of simulations in which the default horizontal and vertical diffusion in WRF are modulated to determine the impacts of eddy diffusion changes on hurricane dynamics. The results indicate that reducing the default vertical diffusion depth and magnitude led to ~38% and ~24% improvements, on average, in hurricane intensity forecasts compared to the default models in the considered cases (Matak and Momen 2023). Moreover, by decreasing the default horizontal mixing length, we managed to decrease the intensity errors on average between ~8-23% in the WRF’s default models for both low and high resolutions. Figure A displays an example of the simulations in which our new adjustment of the vertical diffusion (reduced diffusion, blue line) agrees better with the observed data (black line) compared to the default WRF results (gray line). The figure also depicts wind speed contours that how this change in vertical diffusion can remarkably influence the structure, size, and intensity of hurricane simulations. The results of this study provide notable insights into the role of turbulent fluxes in simulated hurricanes that can be useful to advance the turbulence and PBL parameterizations of NWP models for accurate tropical cyclone forecasts. References: Li M, Zhang JA, Matak L, Momen M (2023) The impacts of adjusting momentum roughness length on strong and weak hurricanes forecasts: a comprehensive analysis of weather simulations and observations. Mon Weather Rev. https://doi.org/10.1175/MWR-D-22-0191.1 Matak L, Momen M (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, Parlange MB, Giometto MG (2021) Scrambling and reorientation of classical boundary layer turbulence in hurricane winds. Geophys Res Lett 48:.https://doi.org/10.1029/2020GL091695 Romdhani O, Zhang JA, Momen M (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. https://doi.org/10.1029/2021MS002796 

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. 

Abstract The momentum roughness length ( z 0 ) significantly impacts wind predictions in weather and climate models. Nevertheless, the impacts of z 0 parameterizations in different wind regimes and various model configurations on the hurricane size, intensity, and track simulations have not been thoroughly established. To bridge this knowledge gap, a comprehensive analysis of 310 simulations of 10 real hurricanes using the Weather Research and Forecasting (WRF) Model is conducted in comparison with observations. Our results show that the default z 0 parameterizations in WRF perform well for weak (category 1–2) hurricanes; however, they underestimate the intensities of strong (category 3–5) hurricanes. This finding is independent of model resolution or boundary layer schemes. The default values of z 0 in WRF agree with the observational estimates from dropsonde data in weak hurricanes while they are much larger than observations in strong hurricanes regime. Decreasing z 0 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. A momentum budget analysis dynamically explained why the reduction of z 0 (decreased surface turbulent stresses) leads to stronger simulated storms. 

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.