城市化对地面气温变化趋势影响研究综述

在综述城市化对地面气温资料序列影响研究进展的基础上,总结评估了不同空间尺度上地面气温序列中城市化影响的性质和强度.在城市台站和局地尺度上,多数研究均发现城市化对地面气温序列影响明显;区域尺度的研究主要集中在中国、美国和欧洲等少数地区,研究结果存在较大的差异,但采用严格遴选乡村站资料的分析都得到了城市化影响很明显的结论.在中国大陆地区,国家级气象台站年平均地面气温的上升趋势中,至少有27.3%可归因于城市化影响;对于全球或半球陆地平均气温序列而言,研究工作还很不充分,但一般认为城市化影响较小,可能不超过总增温的10%.现有研究还表明,城市化对地面气温序列的影响随时间和区域有不同的表现;城市化对包括中国在内的东亚地区近半个世纪长序列地面气温趋势的影响是非常显著的,但对欧洲地区的明显影响可能主要发生在20世纪早期甚至19世纪后期.目前的研究仍然存在一些问题和困难,其中包括研究覆盖的区域和时间段有限、乡村站遴选标准不统一、城市化影响偏差订正方法有待完善等.     

中国近地表气温直减率及其季节和类型差异

近地表气温直减率是推测近地表气温空间分布的重要参数。中国幅员辽阔,气候和地形地貌条件复杂,直接使用反映对流层平均状况的单一气温直减率(0.65℃/100 m)很难表征中国近地表气温直减率的季节和类型差异。本文利用中国839个国家气象站点2000-2013年的近地表气温数据,分别在国家尺度和综合自然区划尺度上使用多元回归分析方法计算各个季节的平均气温直减率(lr_meanT)、平均最低气温直减率(lr_minT)和平均最高气温直减率(lr_maxT),并借助空间插值算法对气温直减率的可靠性进行了验证,最后分析了其季节和类型的差异。结果表明：①在国家尺度上,3种气温直减率均小于0.65℃/100 m;lr_minT、lr_meanT和lr_maxT的季节差异分别为0.05、0.13和0.24℃/100 m,且一般有夏季最大、冬季最小的季节规律;春、夏、秋、冬季气温直减率的类型差异分别为0.12、0.05、0.11和0.26℃/100m,且有lr_minT>lr_meanT>lr_maxT的规律。②在综合自然区划尺度上,气温直减率大多低于0.65℃/100 m,且存在明显的地域差异;夏季气温直减率一般大于冬季气温直减率,季节差异大多超过0.10℃/100 m;气温直减率类型差异半数区域超过或等于0.10℃/100 m,在春、夏、秋季,半数左右的区域lr_maxT >lr_minT,在冬季,多数区域的lr_minT >lr_maxT,lr_meanT一般处于lr_maxT和lr_minT之间。     

Recent changes in ground surface thermal regimes in the context of air temperature warming over the Heihe River Basin, China

Changes in ground surface thermal regimes play a vital role in surface and subsurface hydrology, ecosystem diversity and productivity, and global thermal, water and carbon budgets as well as climate change. Estimating spring, summer, autumn and winter air temperatures and mean annual air temperature（MAAT） from 1960 through 2008 over the Heihe River Basin reveals a statistically significant trend of 0.31 °C/decade, 0.28 °C/decade, 0.37 °C/decade, 0.50 °C/decade, and 0.37 °C /decade, respectively. The averaged time series of mean annual ground surface temperature（MAGST） and maximum annual ground surface temperature（MaxAGST） for 1972–2006 over the basin indicates a statistically significant trend of 0.58 °C/decade and 1.27 °C/decade, respectively. The minimum annual ground surface temperature（MinAGST） in the same period remains unchanged as a whole. Estimating surface freezing/thawing index as well as the ratio of freezing index to thawing index（RFT） in the period between 1959 and 2006 over the basin indicates a statistically significant trend of-42.5 °C-day/decade, 85.4 °C-day/decade and-0.018/decade, respectively.     

昆明城市建筑物外壁表面热力效应研究——不同季节建筑物外墙壁面表温和近旁气温时空分布特征

文章利用不同季节城市建筑物不同朝向外墙壁面表温和近旁气温的垂直观测资料,分析了外墙壁面表温和近旁气温的立体时空分布特征。得出:城市建筑物外墙壁面表温和近旁气温的立体分布存在显著的季节、朝向、高度和时间差异;温度极值出现的位置、时刻随季节和朝向不同而各异;导致温度日较差呈现显著的变化;而昼、夜平均温度的垂直变化同样呈现较大的季节、朝向和位置的分异性。     

ERA-Interim气温数据在中国区域的适用性评估

运用中国756个观测站点的逐月平均气温数据,对比分析了ERA-Interim再分析资料的误差。结果发现:ERA-Interim再分析资料能够很好地反映观测值的年际变化,相关性达到0.955~0.995。ERA-Interim在580个站点的冷偏差或暖偏差小于1℃,占站点总数的76.7%,可信度较高。64个站点的冷偏差或暖偏差大于5℃,可信度较低。ERA-Interim在东部地区的暖偏差多于西部地区,冷偏差的高值主要集中在西部地区的高海拔站点。海拔低于200 m的站点偏差最小,适用性好,多数海拔3 000 m以上的站点呈现较大冷偏差,适用性较差。通过回归分析发现,观测站点与ERA-Interim格点的高度差是导致误差的主要原因,因此通过高程校正能够有效降低误差,提高ERA-Interim适用性。     

20世纪末中国中东部耕地扩张对表面气温影响的模拟

利用WRF模式,通过4个21年（1980-2000年）的模拟实验,研究了20世纪末中国中东部耕地扩张对表面气温的影响。控制实验分析发现WRF模式能够捕捉温度场的空间格局,模拟与观测的季节平均温度场的相关系数为0.91~0.99（P < 0.001）,但模拟温度比观测温度系统性偏低2~3 ℃。控制实验与敏感实验对比分析发现,东北区和中部区的毁林和毁草开荒具有降温效应,冬季平均降幅约为-0.41 ℃,居四季之首,主要是由地表反照率增加,净短波辐射减少,感热通量随之减少所致;东南区的毁林开荒具有升温效应,夏季温度升幅最大,平均升幅为0.14 ℃,主要原因是地表粗糙度减小,湍流减弱,热量在近地层集聚,难以扩散。农业扩张的升、降温效应主要出现在局地,对区域温度变化的影响甚微,一方面是因为农业扩张占区域面积份数甚小,另一方面是因为升、降温效应在区域平均过程中相互抵消。     

Application of geographically weighted regression model in the estimation of surface air temperature lapse rate

The surface air temperature lapse rate(SATLR)plays a key role in the hydrological,glacial and ecological modeling,the regional downscaling,and the reconstruction of high-resolution surface air temperature.However,how to accurately estimate the SATLR in the regions with complex terrain and climatic condition has been a great challenge for re-searchers.The geographically weighted regression(GWR)model was applied in this paper to estimate the SATLR in China's mainland,and then the assessment and validation for the GWR model were made.The spatial pattern of regression residuals which was identified by Moran's Index indicated that the GWR model was broadly reasonable for the estimation of SATLR.The small mean absolute error(MAE)in all months indicated that the GWR model had a strong predictive ability for the surface air temperature.The comparison with previous studies for the seasonal mean SATLR further evidenced the accuracy of the estimation.Therefore,the GWR method has potential application for estimating the SATLR in a large region with complex terrain and climatic condition.     

Effects of urbanization on daily temperature extremes in North China简

The regional changes of daily temperature extremes in North China caused by ur- banization are studied further from observed facts and model estimates on the basis of ho- mogenized daily series of maximum and minimum temperature observations from 268 mete- orological stations, NCEP/DOE AMIP- Ⅱ reanalysis data （R-2）, and the data of simulations by regional climate model （RegCM3）. The observed facts of regional warming on long time scales are obtained by analyzing the indices of temperature extremes during two time periods of 1961-2010 and 1951-2010. For urbanization effect, the contributions to decreases in an- nual and winter diurnal temperature range （DTR） are 56.0% and 52.9%, respectively, and increases in the lowest minimum temperature （TNn） are 35.7% and 26.2% by comparison of urban and rural observations. Obtained by R-2 data with observations for contrast, on the other hand, increase in the number of annual warm nights （TN90p） contributed by urbaniza- tion is 60.9%. And observed facts of regional warming in daily temperature extremes are also reflected in the simulations, but what difference is urbanization progress at rural areas in North China would be prominent in the next few years relative to urban areas to some extent from model estimates.     

珠三角城市化对气温时空差异性影响

利用1967-2015年珠江三角洲21个气象站逐日气温资料,根据人口数量、人口密度和夜间灯光数据等数据集划分城市和郊区站点类型,在此基础上,对比不同时空尺度城市站和郊区站气温变化,分析了城市化对气温影响的时空差异性。结果表明：① 1967-2015年,珠三角地区年平均气温、平均最高气温和最低气温均显著升高,平均最低气温的增温速率最高,分别是平均气温的1.05~1.16倍和平均最高气温的0.95~1.32倍。其中,年平均气温变化速率的季节差异普遍表现为秋冬季节增温最强,增温速率均高于0.3 ℃/10a,春夏季节增温较弱,增温速率最低为0.16 ℃/10a。② 利用城市和海表温度对比研究城市化效应,受城市化影响,珠三角年平均气温的增温趋势是0.096 ℃/10a。③ 利用城市和郊区对比研究城市化效应,1967-2015年城市化对城区的气温升高具有显著贡献,而且城市化对平均最高气温及最低气温增温的贡献率最大。其中,城市化对年平均气温变化的贡献率的季节差异表现为夏冬季节较强,贡献率高于11.8%,春秋季节较弱,贡献率最低仅为4.46%。④ 站点划分方法,城市化发展不同阶段及研究时间尺度的选择均导致城市化增温效应的研究结果具有较大不确定性。不同站点分类方法多指示城市化对最低气温升高的贡献率最强,最高可达到38.6%。     

中国城市扩展对气温观测的影响及其高估程度(英文)

Since the implementation of the reform and opening up policy in China in the late 1970s, some meteorological stations ’entered’ cities passively due to urban expansion. Changes in the surface and built environment around the stations have influenced observations of air temperature. When the observational data from urban stations are applied in the interpolation of national or regional scale air temperature dataset, they could lead to overestimation of regional air temperature and inaccurate assessment of warming. In this study, the underlying surface surrounding 756 meteorological stations across China was identified based on remote sensing images over a number of time intervals to distinguish the rural stations that ’entered’ into cities. Then, after removing the observational data from these stations which have been influenced by urban expansion, a dataset of background air temperatures was generated by interpolating the observational data from the remaining rural stations. The mean urban heat island effect intensity since 1970 was estimated by comparing the original observational records from urban stations with the background air temperature interpolated. The result shows that urban heat island effect does occur due to urban expansion, with a higher intensity in winter than in other seasons. Then the overestimation of regional air temperature is evaluated by comparing the two kinds of grid datasets of air temperature which are respectively interpolated by all stations’ and rural stations’ observational data. Spatially, the overestimation is relatively higher in eastern China than in the central part of China; however, both areas exhibit a much higher effect than is observed in western China. We concluded that in the last 40 years the mean temperature in China increased by about 1.58℃, of which about 0.01℃ was attributed to urban expansion, with a contribution of up to 0.09℃ in the core areas from the overestimation of air temperature.     

MODIS-based estimation of air temperature of the Tibetan Plateau

The immense and towering Tibetan Plateau acts as a heating source and, thus, deeply shapes the climate of the Eurasian continent and even the whole world. However, due to the scarcity of meteorological observation stations and very limited climatic data, little is quantitatively known about the heating effect and temperature pattern of the Tibetan Plateau. This paper collected time series of MODIS land surface temperature （LST） data, together with meteorological data of 137 stations and ASTER GDEM data for 2001-2007, to estimate and map the spatial distribution of monthly mean air temperatures in the Tibetan Plateau and its neighboring areas. Time series analysis and both ordinary linear regression （OLS） and geographical weighted regression （GWR） of monthly mean air temperature （Ta） with monthly mean land surface temperature （Ts） were conducted. Regression analysis shows that recorded Ta is rather closely related to Ts, and that the GWR estimation with MODIS Ts and altitude as independent variables, has a much better result with adjusted R 2 〉 0.91 and RMSE = 1.13-1.53℃ than OLS estimation. For more than 80% of the stations, the Ta thus retrieved from Ts has residuals lower than 2℃. Analysis of the spatio-temporal pattern of retrieved Ta data showed that the mean temperature in July （the warmest month） at altitudes of 4500 m can reach 10℃. This may help explain why the highest timberline in the Northern Hemisphere is on the Tibetan Plateau.