Deep convection is associated with a range of hazards in the United States (US) especially over urban areas with high population density and high-value assets. While the extreme precipitation and damaging winds associated with deep convection pose a threat to the urban area, the urban environment also feedbacks to influence deep convection through the unique surface energy balance, atmospheric stability, and flow field. In this study, we investigate the urban influence on typical deep convective systems in the Southern Great Plains and Northeastern US using the Weather Research and Forecast (WRF) model. A range of experiments were performed including pure urban modification (i.e. expansion of urban areas via the land use land cover, LULC), pseudo-global-warming (PGW i.e. perturbation of initial and lateral boundary conditions), and the combination of urban expansion and a warmer climate. The experimental design also includes a range of different microphysics schemes. The urban expansion is derived based on the population growth by the end of the 21^st century under the SSP5-8.5 scenario. The PGW perturbations are also defined under the SSP5-8.5 scenario as manifest in the E3SM Model by the US Department of Energy. Results show that the urban influence on parameters such as rainfall rate (RR), vertical velocities and composite reflectivity is small when the large-scale forcing is strong, but locally forced deep convection shows a non-linear response to urbanization which is specific to the microphysics scheme and the LULC experiments may even have opposite sign of change in RR for different microphysics schemes. The sensitivity to microphysics schemes is much weaker over the larger urban areas of the US Northeast. Experiments including LULC perturbations yield different responses in the current climate and PGW experiments indicating complex interactions between the atmospheric context of the deep convection and the LULC. Results will be discussed in the context of making robust projections of future urban flooding probability under evolving socio-economic and climate.