Uncertainty of city-based urban heat island intensity across 1112 global cities: Background reference and cloud coverage

Abstract

As an urban heat island (UHI) is closely associated with a wide variety of environmental issues, it is necessary to monitor its spatiotemporal variations in an accurate and timely manner. However, the accuracy of surface urban heat island intensity (SUHII) estimation is greatly challenged by three issues. Namely, less attention has been given to city-based global studies, △SUHII (SUHII difference) is induced when various methods are used to the determine background reference, and uncertainty arises in the methods for coping with missing land surface temperature (LST). Thus, this paper quantitatively evaluated these different methods and their impacts on spatiotemporal SUHII variations across 1112 global cities. There are two major findings: (1) the modified equal area-rural (MEA-R) method can overcome the limitations of the other methods. The fixed buffer (FB) method is limited by the difficulty of buffer selection and the inapplicability of a single fixed buffer for various cities, particularly in large-scale studies. The simplified urban-extent (SUE) method is challenged by cluster discrepancies and data obsolescence issues, and the modified equal area-suburban (MEA-S) method underestimates SUHII resulting from strong human activities in suburban areas. The daytime △SUHII induced by different methods for the reference definition reaches 0.62 K, accounting for 42% of the average SUHII. △SUHII is 0.34 K (23%) at night. △SUHII with evident spatiotemporal variations indicates that the different methods used to define the background reference introduce a considerable uncertainty to SUHII research. (2) After comparing methods for coping with missing LST, the first spatial and after temporal aggregation with threshold removal (FSAT-T) method is demonstrated to provided improved robustness to data missing over other methods. Daytime △SUHII is over 0.1 K in 62% of cities, and nighttime △SUHII is over 0.1 K in 45% of cities. Strong latitudinal and seasonal variations of △SUHII induced by the different methods used to cope with missing data introduce uncertainty and incomparability to SUHII research. Moreover, various image quality control (QC) methods and the effects from these methods on SUHII are discussed. The accuracy of QC methods changes with the error distribution of the image quality. Further investigations are required to determine the optimal QC method. The questions of whether different background definition affects the atmospheric UHI were also discussed. In this paper, a promising strategy for estimating city-based SUHII is proposed and a global-scale database based on the Google Earth Engine (GEE) is established to support further research on the variations and controls of SUHI.