Application of the profile method for the estimation of urban sensible heat flux using roadside weather monitoring data and satellite imagery

This study explores the possibility of estimation of the sensible surface heat flux using satellite-derived surface temperature and road pavement temperature together with in-situ wind and air temperature measurements by the profile method. A 10-year series of data from the roadside weather observation network was used. This dataset contained wind (measured at 5.8–9.5 m above ground) and air temperature (measured at 2.6–4.8 m) together with road surface temperature. Another dataset consisted of 254 simultaneous MODIS observations. A high correlation (0.94) of the surface temperature measured by both methods was noted despite coarse pixel size. We considered satellite-derived surface temperature to determine the sensible heat flux by the profile method; these results were compared to the values obtained using road temperature measured by pavement-mounted sensors. While the overall correlation is relatively strong (0.70) and considerable systematic differences exist, the values of heat flux calculated at different locations show a high spatial coherence - either when using the in situ pavement temperature (correlation ranging from 0.84 to 0.94 for daytime and 0.63–0.84 for nighttime) or the satellite-derived temperature (correlation coefficient 0.72). In most cases, differences between the two flux estimates can be linked to local factors such as the land use structure. •Sensible heat flux using satellite-derived surface temperature and in-situ measurements was estimated by the classical profile method.•Satellite-derived surface temperature and road pavement temperature are highly correlated.•The temperature of the road pavement at different places in a city is highly correlated.•Sensible heat flux retrieved using the profile method reveal strong spatial coherence across the city when solely in-situ data is used•Sensible heat flux retrieved using the profile method reveal fairly strong spatial coherence when in-situ and simultaneous satellite data is used