Identification of typical diurnal patterns for clear-sky climatology of surface urban heat islands

Understanding the diurnal dynamics of surface urban heat islands (SUHIs) is an indispensable step towards their full interpretation at multiple time scales. However, because of the tradeoff between the spatial and temporal resolutions of satellite-derived land surface temperature (LST) data, the climatology, variety, and taxonomy of diurnal SUHI (DSUHI) patterns remain largely unknown for numerous cities with different bioclimates. By combining daily MODIS LST data with a newly developed four -parameter diurnal temperature cycle(DTC) model, we selected 354 Chinese megacities located in different bioclimatic zones to examine the characteristics of the DSUHI descriptors and systematically investigate the prevalent DSUHI temporal patterns. The DSUHI variations demonstrate that both the daily maximum and minimum SUHI intensity (SUHII) can occur during most periods of the day, although these intensities are more likely to occur in the early morning and noon/afternoon. Our results also reveal that both strong SUHIs (SUHII > 3 K) and surface urban cool islands (SUCIs) (SUHII < 0 K) are more prevalent than those identified directly through the four MODIS transits. According to the SUHI dynamics, five typical DSUHI temporal patterns are identified: standard-spoon, weak spoon, quasi-spoon, inverse-spoon, and straight-line patterns. A gradient was found with spoon-like patterns (DSUHI dynamics typically with a daytime valley and a roughly constant trend or a small peak at night) in North China and inverse-spoon (DSUHI dynamics with a typical daytime peak and a constant trend at night) or straight-line patterns (DSUHI dynamics virtually unchanged all day) in South China. The DSUHI shapes were found to be greatly controlled by the urban-rural contrast in the normalized difference vegetation index (NDVI) and urban geometry. Our results not only advance our understanding of the diurnal climatology of SUHIs but also provide a basis for urban surface heat mitigation by identifying the possible timing of the mitigation requirement.