In studying resilience in temporal human networks, relying solely on global network measures would be inadequate; latent sub-structural network mechanisms need to be examined to determine the extent of impact and recovery of these networks during perturbations, such as urban flooding. In this study, we utilized high-resolution aggregated location-based disaster related data to construct temporal human mobility networks. Using the constructed temporal network models, we examined characteristics such as motif distribution, motif persistence and temporal stability, and motif attributes to reveal latent sub-structural mechanisms related to the resilience of human mobility networks during disaster-induced perturbations. The results show that urban flood impacts persists in human mobility networks at the sub-structure level for several weeks. The impact extent and recovery duration is heterogeneous across different network types. Also, perturbation impacts persist at the sub-structure level while global topological network properties might indicate the network has recovered. The findings highlight the importance of examining the microstructures and their dynamic processes and attributes in understanding the resilience of temporal human mobility networks (and other temporal networks), it is essential to examine the microstructures and their perturbation impacts and recovery. The findings can also provide disaster managers, public officials, and transportation planners with insights to better evaluate impacts and to monitor recovery in affected communities based on the patterns of impact and recovery in human mobility networks at both sub-structure and global-network levels.