Compound daytime and nighttime heatwaves for air and surface temperature based on relative and absolute threshold dynamic classified in Southwest China, 1980–2019

Abstract

Heatwaves pose potential risks to the environment, energy, society, and public health, and compound daytime and nighttime air and surface temperature heatwaves have the most severe effects. In this study, Southwest China was taken as a case to explore the characteristics of daytime, nighttime, and concurrent daytime and nighttime heatwaves events using air and surface temperatures based on a dynamic method for classifying urban, suburban, and rural stations with 30 m resolution land use and cover data based on absolute (i.e., same threshold for the entire Southwest China) and relative thresholds (i.e., thresholds for Chongqing municipality, Sichuan, Yunnan, and Guizhou Provinces calculated separately based on built-up areas for each period). We found that heatwaves events became more frequent and more severe in urban, suburban, and rural areas based on absolute and relative thresholds for both air and surface temperatures. Overall, the positive contributions towards warming by urbanization in urban and suburban areas to different heatwaves events obviously differed among different buffer areas and the influence of urbanization was different for air and surface temperature heatwaves events based on absolute and relative thresholds. Spatially persistent compound heatwaves mainly occurred in three urban agglomerations for air temperature. This study provides an original research perspective by using air and surface temperatures during daytime, nighttime, and concurrent daytime and nighttime heatwaves to calculate indices based on absolute (fixed threshold) and relative thresholds (considering the social and economic development level of different regions) in the complex topography of the Southwest China. In addition, this study observed for the first time that the calculated heatwaves indices based on air and surface temperatures were obviously different, illustrating that results obtained using different data sources (e.g., air temperature, surface temperature, and remote sensing data) to evaluate heatwaves will differ, indicating that data sources need to be carefully considered in Southwest China and other regions.