Urbanization Effect on Trends of Extreme Temperature Indices of National Stations over Mainland China, 1961–2008

Abstract

Understanding the long-term change of extreme temperature events is important to the detection and attribution of climate change. It is unclear, however, how much effect urbanization has had on trends of the extreme temperature indices series constructed based on the commonly used datasets on a subcontinental scale. Applying a homogenized daily temperature dataset of the national reference climate stations and basic meteorological stations, and a rural station network previously developed, urbanization effects on trends of extreme temperature indices in mainland China for the time period 1961–2008 are evaluated. It is found that 1) the country-averaged annual- and seasonal-mean extreme temperature indices series generally experience statistically significant trends; 2) annual-mean urbanization effects in the country as a whole are statistically significant for daily minimum temperature (Tmin), maximum temperature (Tmax), and mean temperature of Tmin and Tmax (Tavg), reaching 0.070°, 0.023°, and 0.047°C (10 yr)−1, respectively, with the largest values for annual-mean Tmin occurring in north China; 3) annual- and seasonal-mean urbanization effects for the declining diurnal temperature range (DTR) are highly significant, and the largest seasonal-mean DTR decline because of urbanization occurs in winter and spring; 4) annual-mean urbanization effects for the lowest Tmin, summer days, tropical nights, and frost days series are significant, but an insignificant urbanization effect is detected for icing days series; 5) urbanization has led to a highly significant decline of annual cold nights at a rate of −1.485 days (10 yr)−1 and a highly significant increase of annual warm nights at a rate of 2.264 days (10 yr)−1. Although urbanization effects are also significant for cold days and warm days, they are relatively smaller, and 6) the smallest absolute values of annual-mean urbanization effects for most of the indices series are found to dominantly appear during 1966–76, a well-known deurbanization period resulting from the Cultural Revolution.

Dominance of climate warming effects on recent drying trends over wet monsoon regions

“…We anticipate that aerosols can play an important role in the decrease in R n in the arid region by absorbing and scattering solar irradiance. Furthermore, additional heating due to urbanization may cause different trends in atmospheric water demands between urban and rural areas (Han et al, 2012;Ren and Zhou, 2014). However, examining the effects of LULCC and aerosols on trends in surface dryness lies beyond the scope of the present study.…”

Tempo-spatial characteristics of sub-daily temperature trends in mainland China

“…Artificial heat emission and land cover change near the meteorological stations are mainly the results of city expansion or urbanization. Many studies suggested that urbanization has significantly affected surface air temperature change through modifying land cover, air composition and the anthropogenic heat release (Ren et al 2008, Ren andZhou 2014;Zhou and Ren 2009;Hu et al 2010;Zhang et al 2010;Parker 2010;Stewart 2011;Li and Zhao 2012;Wang et al 2012). Ren (2009), Zhang et al (2011a) and Ren and Zhou (2014) found that the single-site and regional-scale urbanization in mainland China had more significantly increased the minimum temperature trends and significantly narrowed the DTR during the past five decades.…”

Impact of land use/land cover change on changes in surface solar radiation in eastern China since the reform and opening up

“…Significantly increased aerosol concentrations by pollutant emission in eastern China for the last few decades have been reported (e.g., Qian et al 2009b) and have been suggested to be responsible for the observed reduction in global solar radiation (Qian et al 2007). Ren and Zhou (2014) showed that the urbanization effect significantly reduced DTR in China by comparing urban sites to rural sites, ) estimated over the entire 30-year period; those in the lower half indicate the linear trend coefficients estimated for the periods 1979-1989 and 1990-2008. * (**)Denotes that the linear trend is statistically significant at p<0.05 (0.01) which were chosen from ordinary meteorological stations based on population.…”

“…3h, which shows that the largest warming is located in North China Plain. Ren and Zhou (2014) showed that urbanization effects in China are more apparent for Tmin in North China Plain. These urbanization effects may be related mainly to the heat release from the urban infrastructure during the night.…”

“…2), which indicates that R-2 effectively captured the intraseasonal and interannual variability of the observations. However, the correlation coefficients for Tmax are generally larger than those for Tmin, indicating that R-2 to some extent do not well assimilate the surface information, particularly that related to urban conditions because the urbanization effect is observed more apparently in Tmin (e.g., Li et al 2010;Ren and Zhou 2014). Therefore, the OMR trend should primarily reflect the impact of urbanization and other changes in land use, as was proposed by Kalnay and Cai (2003).…”