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Urbanization Effect on the Observed Change in Mean Monthly Temperatures between 1951-1980 and 1971-2000 in Korea
Authors:Uran Chung  Jaeyeon Choi  Jin I Yun
Institution:1. Agricultural Climatology Laboratory, Department of Ecosystem Engineering, College of Life Sciences, Kyung Hee University, Suwon, 449-701, Korea
2. Hwasung City Agricultural Technology Center, Hwaseong, Korea
Abstract:Gridded temperature data are necessary to run ecological models at regional scales for climate impact studies and have been generated by spatially interpolating measured values at synoptic stations. Because there are few synoptic stations with long-term records in rural areas in Korea, data from urban stations have been used for this purpose. Due to the overlapping of the rapid urbanization-industrialization period with the global warming era in Korea, climate data from these urbanized areas might be contaminated with urban heat island effect. This study was conducted to differentiate urbanization and regional climate change effects on apparent temperature change. Monthly averages of daily minimum, maximum, and mean temperature at 14 synoptic stations were prepared for 1951-1980 (past normal) and 1971-2000 (current normal) periods, respectively.Differences in two temperature normals were regressed to the logarithm of the population increase at 14 corresponding cities from 1966 to 1985. The regression equations were used to determine potential effects of urbanization and to extract the net contribution of regional climate change to the apparent temperature change. According to the model calculation, urbanization effect was common in all months except April. Up to 0.5° warming of nighttime temperature was induced by urbanization in the current normal period compared with the past normal period. There was little effect of regional climate change on local warming in the warm season (May through November). The cool season was warmed mainly by regionally increased daytime temperature. The results could be used to remove urbanization effects embedded in raw data, helping restore unbiased rural temperature trends in South Korea.
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