Spatial and Temporal Characteristics and Population Exposure of Heat Waves in China's Coastal Regions
China's coastal areas are not only the most strongly interacting zones extending from land to sea,but also the natural spatial units on the surface of the earth affected by runoff,tides and the effects of human activi-ties and climate change.In this paper,using with the 2003～2018 high quality temporal resolution Land Surface Temperature(LST)and Near Surface Air Temperature(NSAT)products,the spatial and temporal distribu-tion pattern and synergy of urban heat islands and urban heat waves in coastal cities in China are systematically compared.The results show that:(1)Extreme high temperature events in China's coastal regions show a trend of increasing intensity and duration.Specifically,the intensity of urban heat islands in summer is as high as 2.25℃,the average heatwave frequency based on ground temperature in the entire coastal area is 24.59 times,and the temperature-based heat wave frequency is 16.33 times,accounting for 90.81% and 96.68% of the annu-al heat wave frequency,respectively;(2)The frequency of urban heat waves and urban heat island intensity is significantly positively correlated in the North Temperate Zone and North Subtropical Zone along the coast,and is most obvious in the North Temperate Zone.An increase of 1℃ in average LST can lead to an average in-crease in heat wave events twice.Among them,the heat wave frequency in the North Temperate Zone in-creased the fastest in the three major regions,and the compound growth rate of heat wave frequency based on LST and NSAT exceeded 5%;(3)From 2003 to 2018,the urban population of China's coastal regions in-creased by 59%,and the number of people affected by heat waves increased by nearly 370%,exceeding 5% of the total urban population(about 40 million people).Although the urban thermal environment in China's coastal regions and the El Niño and La Niña phenomena in the sea show a more consistent distribution in time and space,how the overall urban change and population growth promote the change of high temperature and ther-mal environment patterns in different regions still need to be further discussed and analysed using longer time se-ries and high spatial and spatial resolution data.
NETL
NSTL
万方数据
