With the homogeneity-adjusted surface air temperature (SAT) data at 312 stations in eastern China for 1979-2008 and the Defense Meteorological Satellite Program/Operational Linescan System (DMSP/OLS) nighttime light data, the spatial heterogeneities of the SAT trends on different scales are detected with a spatial filtering (i.e. moving spatial anomaly) method, and the impact of urbanization in eastern China on surface warming is analyzed. Results show that the urbanization can induce a remarkable summer warming in Yangtze River Delta (YRD) city cluster region and a winter warming in Beijing-Tianjin-Hebei (BTH) city cluster region. The YRD warming in summer primarily results from the significant increasing of maximum temperature, with an estimated urban warming rate at 0.132-0.250°C per decade, accounting for 36%-68% of the total regional warming. The BTH warming in winter is primarily due to the remarkable increasing of minimum temperature, with an estimated urban warming rate at 0.102-0.214°C per decade, accounting for 12%-24% of the total regional warming. The temporal-spatial differences of urban warming effect may be attributed to the variation of regional climatic background and the change of anthropogenic heat release.heterogeneous surface warming, urbanization, surface air temperature, maximum temperature, minimum temperature, eastern China
Citation:Wu K, Yang X Q. Urbanization and heterogeneous surface warming in eastern China. Chin Sci Bull, 2013Bull, , 58: 13631373, doi: 10.1007 Surface warming over recent five decades is attributed to natural climate change and anthropogenic forcing. The anthropogenic forcing mainly includes the emissions of greenhouse gases (GHG) and aerosols, as well as the land use/ cover change (LUCC) [1]. Relative to the enhanced greenhouse effect, however, the climatic effect of LUCC has not been drawn sufficient attention. The urbanization is one of the extreme processes in LUCC [2]. It can alter surface vegetation distribution, induce regional climate change and increase uncertainty in future climate projection [3]. Moreover, large-scale urbanization can affect regional surface energy and water balance [4], and thus may intensify the frequency of extreme weather/climate events. Since both GHG and urbanization tend to increase the surface air temperature (SAT), it is quite difficult to estimate the relative contribution of either effect to the surface warming [5]. A variety of methods have been adopted to detect the climatic effect of urbanization. The most conventional and direct method is the so-called urban-minus-rural (UMR) method in which the SAT at urban and rural sites is contrasted. The key of this method depends on whether or not those sites or stations can be objectively classified. In general, such a classification utilizes either population data [6][7][8][9][10][11][12][13][14][15][16][17] or satellite data (such as nighttime light imagery and land cover dataset) [18][19][20][21][22][23] as well as the geographic location of the stations. In addition, Empirical O...