Urbanization Impact on Temperature Change in China with Emphasis on Land Cover Change and Human Activity

Abstract

The impact of urbanization on temperature trends in China was investigated with emphasis on two aspects of urbanization, land cover change, and human activity. A new station classification scheme was developed to incorporate these two aspects by utilizing land cover and energy consumption data. Observation temperature data of 274 stations and National Centers for Environmental Prediction (NCEP)–National Center for Atmospheric Research (NCAR) reanalysis temperature from 1979 to 2010 were used in conducting the observation minus reanalysis (OMR) method to detect urban influence. Results indicated that nearly half of the stations in the study area have been converted from nonurban to urban stations as a result of land cover change associated with urban expansion. It was determined that both land cover change and human activity play important roles in temperature change and contribute to the observed warming, particularly in urbanized stations, where the highest amount of warming was detected. Urbanized stations showed higher OMR temperature trends than those of unchanged stations. In addition, a statistically significant positive relationship was detected between human activity and temperature trends, which suggests that the observed warming is closely related to the intensity and spatial extent of human activity. In fact, the urbanization effect is strongly affected by specific characteristics of urbanization in local and regional scales.

Is It Possible to Distinguish Global and Regional Climate Change from Urban Land Cover Induced Signals? A Mid-Latitude City Example

“…Another way of investigating the urban impact on air temperatures is statistically analyzing the observed temperature trends from measurements in urban and rural data, where urbanization indicators such as population, urban land cover, and energy consumptions are used to distinguish between urban and rural areas [30][31][32][33][34][35]. Due to the lack of rural measurements in regions with rapid urbanization, re-analysis data are used as rural background data [30,33].…”

“…Due to the lack of rural measurements in regions with rapid urbanization, re-analysis data are used as rural background data [30,33]. Especially in regions with rapid urbanization, such as parts of the US [30] and China [33,35], temperature trends in urban areas were larger compared to temperature trends in rural areas. For Europe, there are no consistent results.…”

“…The incoherent results of this analysis might result from using the population as a measure for urbanization. Other indicators such as the changing share of urban land cover [35], energy consumption [33], or night-light data [7] might be more appropriate but are not available at a sufficient time resolution (e.g., annual) or for a long enough period of time (e.g., more than 30 years). In Table 2, the correlation coefficients between annual and seasonal (December, January, February-DJF; March, April, May-MAM; June, July, August-JJA; September, October, November-SON) differences in the daily mean temperature, T mean , daily minimum temperature, T min , and daily maximum temperature, T max , respectively, and the annual population data are presented.…”

“…The incoherent results of this analysis might result from using the population as a measure for urbanization. Other indicators such as the changing share of urban land cover [35], energy consumption [33], or night-light data [7] might be more appropriate but are not available at a sufficient time resolution (e.g., annual) or for a long enough period of time (e.g., more than 30 years). Table 2.…”

Patterns in Land Cover Changes Around Weather Stations in South Korea

“…(Yun, 2002;Chung et al, 2004;O'Hare et al, 2005;Ahn et al, 2010;Hu and Jia, 2010;Middel et al, 2012;Misra et al, 2012;Li et al, 2013).…”