The contribution of intensified urbanization effects on surface warming trends in China
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Historical temperature records are often partially biased by the urban heat island (UHI) effect. However, the exact magnitude of these biases is an ongoing, controversial scientific question, especially in regions like China where urbanization has greatly increased in recent decades. Previous studies have mainly used statistical information and selected static population targets, or urban areas in a particular year, to classify urban-rural stations and estimate the influence of urbanization on observed warming trends. However, there is a lack of consideration for the dynamic processes of urbanization. The Beijing-Tianjin-Hebei (BTH), Yangtze River Delta (YRD), and Pearl River Delta (PRD) are three major urban agglomerations in China which were selected to investigate the spatiotemporal heterogeneity of urban expansion effects on observed warming trends in this study. Based on remote sensing (RS) data, urban area expansion processes were taken into consideration and the relationship between urban expansion rates and warming trends was investigated using data from 975 meteorological stations throughout China. Although urban areas constitute less than 1% of land in China, more than 90% of the meteorological stations experienced urban land use change and the average urban expansion rate was 0.33%/a. There was also a significant positive relationship between observed warming trends and urban expansion rates. Background warming, without the influence of urbanization and extra warming induced by urbanization processes, was estimated using a linear regression model based on observed warming trends and urban expansion rates. On average, urbanization led to an additional annual warming of 0.034 ± 0.005 °C/10a. This urbanization warming effect was 0.050 ± 0.007 °C/10a for minimum temperatures and 0.008 ± 0.004 °C/10a for maximum temperatures. Moreover, it appeared that urbanization induced greater warming on the minimum temperature during the cold season and maximum temperature during the warm season.
KeywordsRemote sensing Urbanization Surface air temperature Warming Climate change
We would like to acknowledge meteorological station data provider, China National Meteorological Information Center. We also acknowledge the European Space Agency (ESA) for providing the CCI land cover product.
This work was funded by the National Natural Science Foundation of China (Grant # 41675079 and Grant # 41861124005).
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