- 著者
- JIN Kai WANG Fei ZONG Quanli QIN Peng LIU Chunxia
- 出版者
- Meteorological Society of Japan
- 雑誌
- 気象集誌. 第2輯 (ISSN:00261165)
- 巻号頁・発行日
- pp.2020-040, (Released:2020-05-09)
- 被引用文献数
- 4
Observed surface air temperature (SAT) warming at urban stations often contains both the signal of global warming and that of local urban heat island (UHI) effects which are difficult to be separated. In this study, an urban impact indicator (Uii) developed by the authors was modified to represent the extent to which the observed temperature from a station was influenced by UHI effects. While Uii was calculated through simplifying the city's shape to a circle, the modified Uii (MUii) was calculated considering the realistic horizontal distribution of the urban lands. We selected 45 urban stations in mainland China, and then selected an adjacent station for each urban station to constitute a station pair for which the background climate changes are nearly homogeneous. Thus, difference in the trends of annual averaged daily mean SAT (Trendmean), maximum SAT (Trendmax), and minimum SAT (Trendmin) between urban and adjacent stations (ΔTrend) could be mainly attributed to the difference in MUii changes between urban and adjacent stations (ΔMUii). Several linear regressions between ΔTrend and ΔMUii of 45 station pairs were calculated to estimate the UHI effects on Trendmean (UTmean), Trendmax (UTmax), and Trendmin (UTmin) of the 45 urban stations. The results showed that the mean MUii of the 45 urban stations has increased from 0.06 to 0.35 during 1992-2013. The positive correlations between ΔMUii and ΔTrend of the selected 45 station pairs were significant at the 0.001 significance level except for Trendmax. The average UTmean and UTmin of the 45 urban stations during 1954-2013 were approximately 0.05 and 0.11°C decade−1, respectively, accounting for 18 % and 31 % of the overall warming trends, respectively. The UTmin estimated in this study is about twice that of the previous result based on the regression equations between Uii and SAT trends.