Distributed Acoustic Sensing (DAS) offers a transformative solution for dense, high-resolution seismic monitoring to address the challenges of traditional seismometers in urban seismic surveys. Here, we employ seismic interferometry of the ambient noise field and the trace stretching method to monitor seismic velocity variations in Mexico City. We present spatiotemporal variations in relative Rayleigh wave group velocity (dU/U) calculated over two frequency bands (0.4-1.2 Hz and 1.2-3.6 Hz) using DAS data collected over a year. To investigate these variations, we model the impacts resulting from the 2022 Mw7.6 earthquake, along with the effects of precipitation and temperature on the dU/U calculated in the 0.4-1.2 Hz frequency band, which is primarily dominated by the fundamental mode of the Rayleigh waves. Our results indicate that the earthquake-induced velocity drop differs in certain fiber sections, likely due to their non-linear soil behaviors and co-seismic stress changes but without relation to the maximum local deformation registered during the earthquake. Additionally, our modeling indicates that the velocity changes are influenced by seasonal temperature variations, and the impact of precipitation is relatively minor, at least for the depth range (<~50 m) examined in this study. This study highlights the capability of DAS to enhance spatiotemporal monitoring in urban environments, providing valuable insights into both seismic and environmental responses.