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Abstract The computational fluid dynamics of hurricane rapid intensification (RI) is examined through idealized simulations using two codes: a community‐based, finite‐difference/split‐explicit model (WRF) and a spectral‐element/semi‐implicit model (NUMA). The focus of the analysis is on the effects of implicit numerical dissipation (IND) in the energetics of the vortex response to heating, which embodies the fundamental dynamics in the hurricane RI process. The heating considered here is derived from observations: four‐dimensional, fully nonlinear, latent heating/cooling rates calculated from airborne Doppler radar measurements collected in a hurricane undergoing RI. The results continue to show significant IND in WRF relative to NUMA with a reduction in various intensity metrics: (a) time‐integrated, mean kinetic energy values in WRF are ∼20% lower than NUMA and (b) peak, localized wind speeds in WRF are ∼12 m/s lower than NUMA. Values of the eddy diffusivity in WRF need to be reduced by ∼50% from those in NUMA to produce a similar intensity time series. Kinetic energy budgets demonstrate that the pressure contribution is the main factor in the model differences with WRF producing smaller energy input to the vortex by ∼23%, on average. The low‐order spatial discretization of the pressure gradient in WRF is implicated in the IND. In addition, the eddy transport term is found to have a largely positive impact on the vortex intensification with a mean contribution of ∼20%. Overall, these results have important implications for the research and operational forecasting communities that use WRF and WRF‐like numerical models. 

This is the PhD dissertation of Yassine Tissaoui successfully defended on July 9, 2024 at NJIT in mechanical engineering. The co-main advisors for the dissertation are Simone Marras (NJIT) and Stephen Guimond (Hampton University). The increasing frequency and intensity of tropical cyclones (TCs) due to climate change pose significant challenges for forecasting and mitigating their impacts. Despite advancements, accurately predicting TC rapid intensification (RI) remains a challenge. Large eddy simulation (LES) allows for explicitly resolving the large eddies involved in TC turbulence, thus providing an avenue for studying the mechanisms behind their intensification and RI. LES of a full tropical cyclone is very computationally expensive and its accuracy will depend on both explicit and implicit dissipation within an atmospheric model. This dissertation presents two novel numerical methodologies with the potential to improve the efficiency of tropical cyclone LES in the future. The first is a pioneering non-column based implementation of the Kessler warm rain microphysics parametrization, a method which would allow for the use of three-dimensional (3D) adaptive mesh refinement (AMR) in the simulation of moist tropical cyclones. The second is an implementation of Laguerre-Legendre semi-infinite elements for use in the damping layers of atmospheric models, a method which was shown to be capable of improving the efficiency of benchmark atmospheric simulations. Finally, the dissertation presents a study of two-dimensional (2D) AMR applied to simulations of a rapidly intensifying dry tropical cyclone and shows that AMR is able to accurately reproduce the results of simulations using static grids while demonstrating considerable cost savings. 

This is the Masters thesis of Badrul Hasan from UMBC in the Department of Mechanical Engineering. The co-main advisors are Meilin Yu (UMBC) and Stephen Guimond (UMBC, now with Hampton University). Numerous aspects of human existence, both material and immaterial, can be disrupted by a hurricane. In this work, the computational fluid dynamics of hurricane rapid intensification (RI) are studied by running idealized simulations with two different codes: a community-based, finite-difference/split-explicit model (WRF) and a spectral-element/semi-implicit model (NUMA). Rapid intensification is what RI stands for, how a hurricane gets stronger quickly. The main goal of this study is to find out how implicit numerical dissipation (IND) affects the energy of the vortex's response to heating, which describes the fundamental dynamics of the hurricane RI process. The heating that is taken into account here is derived from data. These observations include four-dimensional, fully nonlinear, latent heating/cooling rates estimated using airborne Doppler radar readings acquired during RI in a hurricane. The results show that WRF has more IND than NUMA, with a decrease in several intensity parameters, such as (1) the time-integrated mean kinetic energy values that WRF predicts are 20% lower than those that NUMA predicts and (2) the peak, localized wind speeds that WRF predicts are 12 meters per second slower than those that NUMA predicts. To make a time series of intensity similar to NUMA, the eddy diffusivity values in WRF need to be less than those in NUMA by about 50%. Various analyses are conducted comparing WRF with NUMA. Kinetic energy budgets reveal that the pressure contribution is the primary cause in the model variations, with WRF generating an average 23% lower vortex energy input. The IND is associated with the low-order spatial discretization of the pressure gradient in WRF. In addition, the mean contribution of the eddy transport term to the vortex intensification is determined to be 20% positive. These findings have significant implications for the academic and operational forecasting communities that employ WRF and similar numerical methods.