Urban surface temperature observations from ground-based thermography: intra- and inter-facet variability

In this study (Morrison et al., 2021) ground based thermal cameras are used to observe urban surface temperatures (T_s) with an unprecedented combination of: temporal and spatial resolution (5 min and ~ 0.5 m → 2.5 m), spatial extent (3.9 ha), instrument number (6 static cameras) and surface heterogeneity (mixed high rise and vegetation). The camera images are classified by geometry and material properties (surface orientation, albedo, solar irradiance, and shadow history). Unlike previous methods, pixels are objectively classified using sensor view modelling and a detailed three-dimensional surface model (430 m × 430 m extent). From detailed source area analysis, the cameras are shown to observe 9.5% of the study area. Across all camera pixels, the 5th - 95th percentile T_s range is 37.5 K around midday. Roofs T_s has the greatest diurnal range (290.6 K → 329.0 K). T_s differences across sloped roofs with different sun-surface geomeetry reach 23.3 K. Walls of different cardinal orientations consistently differ by >10 K between 10:00 and 15:00. High temporal resolution (5 min) shadow tracking from the classified images is used to model cooling rates, where recently shaded (<30 min) ground can be 18.6 K warmer than equivalent unshaded T_s. West walls remain warm past sunset and are 1.2 K warmer than north walls at 23:00 (~4 h after sunset). Recently shaded walls cool exponentially to ambient T_s at a similar rate as the ground, but four times slower than roofs. The observaiton methods and observed T_s characteristics are anticipated to have a wide range of applications (e.g. informing future ground-based thermogragy campaign setups, evaluation of urban surface energy balance models, ground-truthing of satellite thermal remote sensing).

 

Morrison, W., Kotthaus, S. and Grimmond, S. (2021) ‘Urban surface temperature observations from ground-based thermography: intra- and inter-facet variability’, Urban Climate, 35, p. 100748. doi: 10.1016/j.uclim.2020.100748.