Deciphering the sensitivity of urban canopy air temperature to anthropogenic heat flux with a forcing-feedback framework

The sensitivity of urban canopy air temperature (T-a) to anthropogenic heat flux (Q(AH)) is known to vary with space and time, but the key factors controlling such spatiotemporal variabilities remain elusive. To quantify the contributions of different physical processes to the magnitude and variability of ?T-a/?Q(AH) (where ? represents a change), we develop a forcing-feedback framework based on the energy budget of air within the urban canopy layer and apply it to diagnosing ?T-a/?Q(AH) simulated by the Community Land Model Urban over the contiguous United States (CONUS). In summer, the median ?T-a/?Q(AH) is around 0.01 K (W m(-2))(-1) over the CONUS. Besides the direct effect of Q(AH) on T-a, there are important feedbacks through changes in the surface temperature, the atmosphere-canopy air heat conductance (c(a)), and the surface-canopy air heat conductance. The positive and negative feedbacks nearly cancel each other out and ?T-a/?Q(AH) is mostly controlled by the direct effect in summer. In winter, ?T-a/?Q(AH) becomes stronger, with the median value increased by about 20% due to weakened negative feedback associated with c(a). The spatial and temporal (both seasonal and diurnal) variability of ?T-a/?Q(AH )as well as the nonlinear response of ?T-a to ?Q(AH) are strongly related to the variability of c(a), highlighting the importance of correctly parameterizing convective heat transfer in urban canopy models.

Automated summary

The sensitivity of urban canopy air temperature (T-a) to anthropogenic heat flux (Q(AH)) varies with space and time, but the exact factors controlling this variability remain unclear. To understand the contributions of different physical processes to this sensitivity, a forcing-feedback framework based on the energy budget of air within the urban canopy layer was developed and applied to simulate T-a/Q(AH) in the contiguous United States. The results showed that both direct and feedback effects play a role in this sensitivity, with the direct effect being dominant in summer and the feedback effect becoming stronger in winter due to weakened negative feedback associated with heat conductance.