Adjusting urban bias in the regional mean surface temperature series of South Korea, 1968–99

Abstract

The purpose of this paper is to produce a higher quality regional surface temperature series by removing urban biases in South Korean surface temperatures using statistical procedures. Monthly mean temperatures for 16 stations were obtained for a period of 32 years . Each station is defined as an urban station or a rural station. Urban (rural) stations are defined as those that have population densities greater (less) than 1000 persons per squared kilometer in 1995. Ten urban stations and six rural stations are identified. Again, urban stations are subdivided into two groups according to whether their population totals exceed one million to examine magnitude changes of urban biases with the size of urban areas. Estimates of urban bias magnitude are calculated by averaging the difference between each urban station and every rural station. Estimates of mean urban bias magnitude (Tu-r) are calculated by averaging the yearly urban bias estimates. Estimates of the urban trend ( Tu-r) are obtained by differencing period means (by doubling the differences obtained between yearly estimates averaged over two 16 year periods, 1968-83 and 1984-99). For annual or seasonal mean temperature T i , the adjusted temperature T i is determined. As all estimates of Tu-r are greater than zero, it suggests that temperatures in urban stations are warmer than those in rural stations. Estimates of the annual mean magnitude of urban bias range from 0.35°C for smaller urban stations to 0.50°C for large urban stations. Also, all estimates of Tu-r are positive, indicating an increasing trend in the urban bias time series. Seasonal variations are found in Tu-r and Tu-r. After adjusting the urban bias, an increasing trend in surface temperature series is still evident.

Change in mean temperature as a predictor of extreme temperature change in the Asia–Pacific region

“…The maximum UHI in Seoul has increased by an estimated 0.56°C over the period 1973-96 (Kim andBaik, 2002), whereas the estimated average annual urban bias in South Korea mean temperatures over the 1968-99 period was ∼0.4°C (Choi et al, 2003). Determination of urbanization effects versus regional climate-change effects in apparent (recorded) temperature change in Korea was undertaken (Chung et al, 2004), using two normal periods (1951-80 versus 1971-2000), and utilizing population data.…”

“…The population density condition is comparatively conservative, e.g. some studies have defined urban stations as having population densities greater than 1000 km −2 (Choi et al, 2003); yet, other studies, when defining station urbanization solely on population, have used a range of population criteria: e.g. Easterling et al (1997) used a population of 50 000 as the critical value for urban stations.…”

Intra‐urban differences in canopy layer air temperature at a mid‐latitude city

“…where no buildings existed previously, was monitored by Landsberg and Maisel (1972), who reported that over a period of 3 years, a heat island of up to 4.5°C appeared as the newly established town of Columbia, Maryland grew to a population of 10 000 residents. Analyses of longterm temperature records in several locations -Turkey (Tayanc and Toros, 1997); Alaska (Magee et al, 1999); Athens (Philandras et al, 1999); South Korea (Choi et al, 2003); and North America (Engelhart and Douglas, 2003) -show an increase in the UHI effect paralleling increasing urbanisation.…”

Correlation between Urbanization Rate in Local Scale and Extreme Climate Indices

“…지난 100여 년 동안 전구 평균기온은 약 0.74 ± 0.18℃ 상승하였다 (Trenberth et al, 2007) (Zhang et al, 2003;He et al, 2007;Ren et al, 2008) 반면, 그 영향이 10% 미만이었다는 의견도 있다 (Zhou et al, 2004;Li et al, 2004;Li et al, 2010) 규모를 채택하였다(e.g., Park et al, 1986;Choi et al, 2003;Ryoo et al, 2004;Li et al, 2010;김경 환 외, 2000;이승호·허인혜, 2011;고명찬·이승 호, 2013).…”