The spatiotemporal characteristics of air temperature and humidity mediated by urban bluespace are investigated using a combination of dense network of climatological observations in a medium-sized US city, computational fluid dynamics and analytical modeling approaches. Both numerical simulation and observational results show that the rate of change of hourly averaged air temperature and humidity at 3.5 m over urban areas peaks two hours after sunset, while it decreases with time monotonically over greenspace, indicating different impacts due to presence of urban lakes. The apparent temperature decreases with distance to lakes in urban area due to higher near-shore humidity. This highlights that urban lakes located near city center can deteriorate the nighttime cooling effects due to elevated humidity. Finally, two analytical models are presented to explain the connection between the surface and air temperature as well as the spatial variation of air temperature and humidity adjacent to the urban lakes. These simplified models with parameters being inferred from the network of measurements have reasonably good performance compared to the observations. Compared to other sophisticated numerical simulations, these analytical models offer an alternative means that is easily accessible for evaluating the efficacy of bluespace on urban nocturnal cooling.