Detecting urban warming signals in climate records

Determining whether air temperatures recorded at meteorological stations have been contaminated by the urbanization process is still a controversial issue at the global scale. With support of historical remote sensing data, this study examined the impacts of urban expansion on the trends of air temperature at 69 meteorological stations in Beijing, Tianjin, and Hebei Province over the last three decades. There were significant positive relations between the two factors at all stations. Stronger warming was detected at the meteorological stations that experienced greater urbanization, i.e., those with a higher urbanization rate. While the total urban area affects the absolute temperature values, the change of the urban area (urbanization rate) likely affects the temperature trend. Increases of approximately 10% in urban area around the meteorological stations likely contributed to the 0.13℃ rise in air temperature records in addition to regional climate warming. This study also provides a new approach to selecting reference stations based on remotely sensed urban fractions. Generally, the urbanization-induced warming contributed to approximately 44.1% of the overall warming trends in the plain region of study area during the past 30 years, and the regional climate warming was 0.30℃ (10 yr)-1 in the last three decades.     

北京地区城市热岛强度变化对区域温度序列的影响

通过对北京地区20个台站1961~2000年月平均温度资料的对比分析,证实热岛效应对城市气象站记录的地表平均气温的绝对影响随时间显著增大,近20 a尤为突出,但其相对影响即热岛增温对全部增暖的贡献却呈下降趋势。近40 a来,北京地区的国家基本、基准站平均温度距平序列与被认为不受城市热岛影响的郊区站平均温度距平序列差异明显,由于热岛效应加强因素引起的国家基本、基准站平均年温度变化速率为0.16℃/(10 a),对整个时期全部增温的贡献达到71%;近20 a来热岛效应加强因素使北京地区国家基本、基准站年平均温度每10 a增暖0.33℃,对该时期全部增温的贡献达到49%。城市热岛效应加强因素对国家基本、基准站季节平均温度上升的贡献在夏、秋季高,冬季最小。本文的结果说明,目前根据国家基本、基准站资料建立的全国或较大区域平均温度序列可能在很大程度上保留着城市化的影响,有必要做进一步的检验和订正。     

西南地区城市热岛强度变化对地面气温序列影响

利用1961—2004年我国西南地区322个站的气温观测资料, 分析了乡村站、小城市站、大中城市站和国家基准/基本站气温变化趋势特点, 着重研究了城市化对城镇站和国家站地面气温记录的影响程度和相对贡献比例。结果显示:区域平均的各类台站年平均气温呈现不同程度的上升趋势, 城市站、国家站的增温速率均高于乡村站。大中城市站和国家站的年平均热岛增温率分别为0.086 ℃/ 10a和0.052 ℃/10a, 其增温贡献率分别达57.6%和45.3%。与大多数地区不同, 西南地区的增温速率明显偏小。因此, 尽管平均热岛强度变化比许多地区弱, 但其相对贡献明显, 表明城市化对该区域气温趋势的绝对影响较弱, 但相对影响较强。另外, 城市热岛增温有明显的季节变化, 表现为秋季最强, 春季或冬季次之, 夏季最弱。热岛增温贡献率则为春季最大 (100%), 夏季次之 (73%以上), 秋季和冬季相对较小。这主要是因为春、夏两季背景气候变凉或趋势微弱, 热岛增温在实际增温中占有更高的比例。     

资料均一化对气温变化趋势及其城市化偏差估计的影响：以北京地区为例

当前的地面气候观测资料普遍存在非气候性因素导致的非均一性,对气候变化监测和研究结论可靠性造成重要影响。结合观测台站的历史沿革数据,使用ACMANT和Pairwise Comparisons方法以及RHtest V4软件,对北京地区20个台站均一化前的月平均气温序列进行了非均一性检验和订正,最后评估了均一化对北京地区气温序列变化趋势及其城市化偏差估算的影响。结果表明：除元数据中记录的断点外,无元数据记录的断点也会对序列的趋势变化造成明显影响,其中乡村站最显著;经过订正,1958—2018年整个北京地区、乡村站以及城市站增温趋势分别为0.27℃/(10 a)、0.10℃/(10 a)和0.32℃/(10 a),较订正前分别上升了0.03℃/(10 a)、0.06℃/(10 a)和0.02℃/(10 a)。利用均一化资料估算,1958—2018年北京观象台的城市化影响为0.24℃/(10 a),城市化贡献率为70.2%,评估结果较前人结论有所降低。可见,在现有的北京地区气温资料序列中,仍可能存在较明显的非均一性和未被记录的断点,对区域平均气温趋势估算具有显著影响。     

格点资料在城市气候变化研究中的应用

为了解浙江省城市增暖的地域差异及其受热岛效应影响的程度,对杭州、宁波、温州3个城市的气候变化趋势进行了分析。为减少观测资料的非均一性,运用最优插值法将浙江省1971—2010年62个站点资料的信息植入到NCEP月平均温度资料的背景场中,得到格距为5 km的格点资料。研究结果表明:3个城市在近40年表现出明显的增温趋势,城区增温明显快于乡村的。各地区增温率的时空变化存在一定差异,与人口密度、工业总产值、用电量及车辆拥有量等经济数据的分布及变化基本一致。沿海城市温州增温率最小,但城乡差异最明显。同样为沿海城市的宁波,由于经济发展地域差别较小,虽表现最明显的增温,但城市热岛效应最弱。3个城市的热岛效应及热岛增温贡献率均存在明显的季节变化:杭州的热岛效应呈春、夏、冬、秋依次减弱的变化规律;温州则呈春、秋、冬、夏依次减弱的变化规律;宁波类似于城市群发展的模式,导致其热岛效应较不明显,以夏季和秋季最强。城市化发展引起的增暖占有较大的比重,杭州和温州年平均气温的增加大约有1/3是由城市化引起的,其中杭州夏季热岛增温贡献率达到2/3以上,温州春、夏季热岛增温贡献率均达到43%左右,宁波城市热岛增温贡献率相对较小,夏季的最大,为20%左右。     

ON TEMPERATURE CHANGES OF SHANGHAI AND URBANIZATION IMPACTS

To understand how temperature varies in urban Shanghai under the background of global climate change and how it is affected by urbanization, the Shanghai temperature responses to global warming were analyzed, and then the temperature trends of urban and suburb stations under different climatic backgrounds were obtained. The urbanization effects on temperature were studied by comparing urban stations to suburb stations, the relationship between urbanization variables and temperature components were obtained, and observation data of surface and high level were combined to assess the contribution of urbanization effect. In the last part of the paper, the cause of urbanization effects on temperature was discussed. The results indicated: The long term change trend of Shanghai annual mean temperature is 1.31/100a from 1873 to 2004, the periods of 1921 – 1948 and 1979 – 2004 are warmer, and the 1979 – 2004 period is the warmest; compared to suburb stations, the representative urban station has slower decreases in the cool period and faster increases in the warm one; the urban and suburb temperatures have distinct differences resulting from urbanization and the differences are increasing by the year, with the difference of mean temperature and minimum temperature being the greatest in fall and that of maximum temperature being the largest in summer between the urban and suburban areas. The urbanization process accelerates the warming speed, with the minimum temperature being the most obvious; the urbanization effect contributes a 0.4°C increase in 1980s and 1.1°C in 1990s to the annual mean temperature.     

城市热岛效应对甘肃省温度序列的影响

对甘肃省若干国家基本/基准站、城市站和乡村站1961—2002年共42年季、年平均温度资料等进行了对比分析。结果表明:城市站和国家基本/基准站比乡村站增温趋势显著。近40多年来城市热岛效应对基本/基准站年平均温度的增温贡献率为18.5%,对城市站年平均温度的增温贡献率为37.6%。季节增温率冬季最大,秋季次之,春夏季最小;城市热岛效应对季节增暖的贡献率则为春季最大,夏季次之,秋冬季最小。     

Climate change in Turkey for the last half century

Climate change and its urban-induced bias in selected Turkish cities is studied with a quality controlled temperature and precipitation data of Turkish stations in the period of 1950–2004. These stations are classified into two groups according to their populations; S1, including rural and suburban stations and S2, including large urban stations. Moving average signals, 365-day, and their digital low pass filtered versions are produced to eliminate the short term fluctuations and examine the possible trends or anomalies in climate data. Furthermore, ‘relative difference’ signals are introduced and applied to temperature and precipitation series to observe the actual local changes in the climate data independent from large-scale effects. Mann–Kendall test statistics are calculated for maximum, minimum, mean temperature and precipitation series and plotted on maps to determine any spatial trend patterns. Signal analysis show a cool period extending from early 1960s till 1993, generally with the lowest temperature values on 1992–1993 owing to the eruption of Mount Pinatubo. A last decade significant warming trend is observed in both of the series, S1 and S2, leading to 2000–2002 temperatures to be recorded as maximums in record history. The variability of urban precipitation series is generally larger than the rural ones, suggesting that urban stations can experience more frequent and severe droughts and floods. Though not significant, an increase in the urban precipitation compared to the rural one is also found. Spatial analysis resulted in significant warming in southern and southeastern parts of the country. Particularly, minimum temperature series show significant warming in almost all of the regions indicating the effect of urbanization. Significant decreases of precipitation amounts in the western parts of Turkey, such as Aegean and Trachea regions, are found. On the other hand, some Turkish northern stations show increases in precipitation of which some are significant.     

Climate-induced changes in river water temperature in North Iberian Peninsula

With the surface air temperature (SAT) data at 37 stations on Central Yunnan Plateau (CYP) for 1961–2010 and the Defense Meteorological Satellite Program/Operational Linescan System (DMSP/OLS) nighttime light data, the temporal-spatial patterns of the SAT trends are detected using Sen’s Nonparametric Estimator of Slope approach and MK test, and the impact of urbanization on surface warming is analyzed by comparing the differences between the air temperature change trends of urban stations and their corresponding rural stations. Results indicated that annual mean air temperature showed a significant warming trend, which is equivalent to a rate of 0.17 °C/decade during the past 50 years. Seasonal mean air temperature presents a rising trend, and the trend was more significant in winter (0.31 °C/decade) than in other seasons. Annual/seasonal mean air temperature tends to increase in most areas, and higher warming trend appeared in urban areas, notably in Kunming city. The regional mean air temperature series was significantly impacted by urban warming, and the urbanization-induced warming contributed to approximately 32.3–62.9 % of the total regional warming during the past 50 years. Meantime, the urbanization-induced warming trend in winter and spring was more significant than that in summer and autumn. Since 1985, the urban heat island (UHI) intensity has gradually increased. And the urban temperatures always rise faster than rural temperatures on the CYP.     

城市化对深圳气温变化的贡献

采用经均一性检验的深圳及其周围台站的地面温度资料和NCEP／DOEAMIP—ⅡReanalysis（R-2）再分析温度数据,通过鲁棒回归（M估计）对气温趋势进行拟合,分析了1967--2005年和1979—2005年两个时间段城市热岛效应对温度的影响,利用再分析数据和地面观测数据的差异估计了1979年以来城市化对气温增暖的贡献。结果表明,20世纪80年代以来的30a里,深圳城市化对当地气温增暖贡献非常显著：1979年以来,城市热岛效应导致年平均气温增暖0．243℃·（10a）^-1,占深圳总体增暖的36．3％;与再分析资料对比得到的城市化对深圳年平均气温增暖的贡献达到0．315℃·（10a）^-1,大于分析观测资料得到的结果,占总体增暖的47．1％。说明城市化的快速发展是导致深圳城市气候增暖的重要因子之一。     

Trend analysis of long-term temperature time series in the Greater Toronto Area (GTA)

As the majority of the world’s population is living in urban environments, there is growing interest in studying local urban climates. In this paper, for the first time, the long-term trends (31–162 years) of temperature change have been analyzed for the Greater Toronto Area (GTA). Annual and seasonal time series for a number of urban, suburban, and rural weather stations are considered. Non-parametric statistical techniques such as Mann–Kendall test and Theil-Sen slope estimation are used primarily for the assessing of the significance and detection of trends, and the sequential Mann test is used to detect any abrupt climate change. Statistically significant trends for annual mean and minimum temperatures are detected for almost all stations in the GTA. Winter is found to be the most coherent season contributing substantially to the increase in annual minimum temperature. The analyses of the abrupt changes in temperature suggest that the beginning of the increasing trend in Toronto started after the 1920s and then continued to increase to the 1960s. For all stations, there is a significant increase of annual and seasonal (particularly winter) temperatures after the 1980s. In terms of the linkage between urbanization and spatiotemporal thermal patterns, significant linear trends in annual mean and minimum temperature are detected for the period of 1878–1978 for the urban station, Toronto, while for the rural counterparts, the trends are not significant. Also, for all stations in the GTA that are situated in all directions except south of Toronto, substantial temperature change is detected for the periods of 1970–2000 and 1989–2000. It is concluded that the urbanization in the GTA has significantly contributed to the increase of the annual mean temperatures during the past three decades. In addition to urbanization, the influence of local climate, topography, and larger scale warming are incorporated in the analysis of the trends.     

IMPACT OF URBANIZATION IN DIFFERENT REGIONS OF EASTERN CHINA ON PRECIPITATION AND ITS UNCERTAINTY

Climate effect caused by urbanization has been an indispensable anthropogenic factor in the research on regional climate change. Based on daily precipitation data, possible effects of precipitation on the development of three city groups in eastern China are discussed. With three classification methods (TP, PD and MODIS land cover), urban and rural stations are identified. The main findings are as follows. Climate effects caused by urbanization are different from place to place. In 1960 to 2009, the urbanization brought more precipitation to the Yangtze River Delta and Pearl River Delta city groups but had no obvious effect on the precipitation of the Beijing-Tianjin-Tangshan city group. The difference of precipitation is slight between urban and suburban areas during slow period of the urbanization from 1960 to 1979. It is more evident in the rapid period (1980 to 2009) that urbanization has positive effects on precipitation in every city group. The difference of precipitation between urban and rural stations is sensitive to the ways of distinguishing rural from urban area, which may cause uncertainties in 1960 to 1979, while it is very different in 1980 to 2009 in which urbanization favors more precipitation in all city groups and their differences in precipitation are not sensitive to the division methods.     

URBANIZATION EFFECTS ON REGIONAL CLIMATE CHANGE IN THE CASE OF FOUR LARGE CITIES OF TURKEY

The growing interest in urbanization problems is stimulating detailed studies of their effects on local climate change in the developed world. The absence of such studies in developing countries is restricting many decisions to be made and applied by policymakers. In one developing country, Turkey, results of the study of four urban stations and their neighboring rural sites for the 1951-1990 time period reveal that there is a shift towards the warmer side in the frequency distributions of daily minimum and 21.00 hr temperature difference series. This shift is an indication of urban heat island. The maximum urban heat island intensity trend that is obtained from the temperature differences database agrees well with Oke's (1973) formula for European cities. Seasonal analysis of individual 21.00 hr temperature series suggests that the regional warming is strongest in spring and weakest in autumn and winter. Urban warming is detected to be more or less equally distributed over the year wi th a slight increase in the autumn months. The Mann-Kendall trend test is applied to the temperature difference series, and the urban heat island effect is found to be significant in all urban sites. On the other hand, almost no significant urban effect on precipitation can be detected.     

城市化对华北地区最高, 最低气温和日较差变化趋势的影响

利用华北地区255个一般站和国家基本、 基准站1961\_2000年的实测资料, 经过质量检验和均一性订正后, 将所有台站根据人口和台站地理位置分为5个类别, 分析了这5个类别台站和国家基本、 基准站地面平均气温、 最高、 最低气温的年和季节变化趋势以及城市化影响。结果表明： 华北全部台站的年平均气温、 最高、 最低气温均呈增加趋势, 且以最低气温上升最为明显, 导致年平均日较差呈现明显下降。就城市化影响而言, 平均气温、 最低气温变化趋势中城市热岛效应加强因素的影响明显, 但城市化对最高气温趋势影响微弱, 个别台站和季节甚至可能造成降温。在国家基本、 基准站观测的年平均气温和年平均最低气温上升趋势中, 城市化造成的增温分别为0.11℃·(10a)-1和0.20℃·(10a)-1, 对全部增温的贡献率分别达39.3%和52.6%。各类台站的四季平均气温和最低气温序列中城市化影响均造成增温。城市化增温以冬季为最大, 夏季最小。城市化还导致乡村站以外的各类台站日较差减小, 近40年华北地区国家基本、 基准站年平均和秋、 冬季平均气温日较差明显下降均由城市化影响造成的。     

1960—2009年北京地区城市化背景下蒸发皿蒸发量的时空变化

利用1960—2009年北京地区20个气象台站的观测资料,分析了北京城区和郊区蒸发皿蒸发量的季节和年际变化趋势和特点,并探讨了城市化对北京地区局地气候的影响。结果表明:近50 a北京地区蒸发量有明显减小趋势,城区和郊区变化趋势分别为-88.1 mm/10a和-76.0 mm/10a。受城市化影响,北京城区蒸发量的变化主要与降水、日照时数、最低气温、气温日较差和平均风速的变化有关;郊区蒸发量的变化主要受相对湿度、日照时数、平均风速和空气饱和差的变化影响。总体而言,相对湿度、日照时数、最低气温、气温日较差和平均风速的变化对北京地区蒸发量的变化有显著影响。     

A Dynamic Method for Quantifying Natural Warming in Urban Areas

In the study of global warming, one of the main issues is the quantification of the urbanization effect in climate records. Previous studies have contributed much to removing the impact of urbanization from surface air temperature by carefully selecting reference stations. However, due to the insufficient number of stations free from the influence of urbanization and the different criteria used to select reference stations, there are still significant controversies about the intensity of the impact of urbanization on temperature records. This study proposes a dynamic method for quantifying natural warming using information on urbanization from every station acquired from remote sensing (RS) data instead of selecting reference stations. Two different spatial scales were applied to examine the impact of urbanization, but little difference was found, indicating the stability of this method. The results showed a significant difference in original temperature data and the homogenized data—urban warming accounted for approximately 64% in the original temperature warming but only approximately 20% in the homogenized temperature records.     

近48年城市化发展对北京区域气候的影响分析

利用1961～2008年北京12个台站的气候观测资料, 研究分析了北京城区和郊区气温、降水、相对湿度、风速的年际和四季变化趋势及特点, 并探讨了城市化发展对北京区域气候的影响。结果表明: 近半个世纪以来, 平均气温上升明显, 其中尤以冬季最为突出, 而夏季最弱。通过气温变化的年代比较发现气温增加有加快的趋势, 尤其是城市地区, 导致热岛效应不断加强, 特别是1990年代以后增幅更加明显。最高和最低气温在近48年来也都呈上升趋势, 且城市化发展对最低气温的变化影响最大, 其次是平均气温, 对最高气温影响最弱。而降水有减弱的趋势, 尤其是夏季的降水减弱最为明显。城区的风速和湿度都呈减小的趋势, 这与城市化的加剧, 尤其是下垫面的变化有密切的关系。     

多种方法分析城市化对保定气温变化的贡献

文章通过三种方法构造不同的背景气温序列,分析近33a(1979—2011年)城市化对保定气温变化的影响。结果表明:(1)对比保定站与郊区背景站气温资料得到城市热岛效应导致的增暖幅度为0.15℃/10a,城市化贡献率为30.3%。(2)用NCEP/DOE的2m气温再分析资料为背景得到的城市化增温幅度为0.238℃/10a,分离出的城市化贡献率为48.08%。(3)比较城市站与山区背景站资料得出年均气温的城市化增暖幅度为0.216℃/10a,贡献率为43.64%。(4)三种方法计算得出的城市化增温幅度及贡献率各不相同,却一致表明城市化对保定年气温的增暖贡献较为显著。     

基于卫星遥感揭示长三角台站周边城市土地利用扩张及其对气温记录的影响

台站温度记录中的城市化信号对于气候变化研究影响重大并仍存在很大争议,尤其是在经历快速城市化的区域。本研究利用遥感影像分类的方法,提取了1980~2009年期间长江三角洲城市群93个气象台站周边10 km×10 km范围的城市土地利用信息,并按照城市土地利用扩张速率对站点进行分类,研究了1980~2009年期间快速城市化站点、中速城市化站点和慢速城市化站点的年和季节平均温度、最低温度和最高温度变化特征,并分析了快速和中速城市化站点城市化影响和城市化影响贡献率。结果表明:全部93个气象站点周边自20世纪80年代起均经历了城市土地利用扩张过程,全部站点周边的平均城市土地利用扩张速率为1.00% a-1;近30年来,各类型站点年和各季节的平均温度、最低温度和最高温度均表现出增加趋势;城市化效应增强因素对快速城市化站点年平均温度贡献率为35.06%,对年平均最低温度的增温贡献率为34.67%,对年平均最高温度增温贡献率最小,仅为18.42%;城市化效应增强因素对中速城市化站点的影响程度小于快速城市化站点,对平均温度、最低温度和最高温度的贡献率分别为19.35%,22.22%和3.13%。在季节变异方面,长江三角洲区域各类型站点冬季的城市化影响贡献率在平均温度、最低温度和最高温度均表现为最低值。     

Temperature projection in a tropical city using remote sensing and dynamic modeling

Recent temperature projections for urban areas have only been able to reflect the expected change due to greenhouse-induced warming, with little attempt to predict urbanisation effects. This research examines temperature changes due to both global warming and urbanisation independently and applies them differentially to urban and rural areas over a sub-tropical city, Hong Kong. The effect of global warming on temperature is estimated by regressing IPCC data from eight Global Climate Models against the background temperature recorded at a rural climate station. Results suggest a mean background temperature increase of 0.67 °C by 2039. To model temperature changes for different degrees of urbanization, long-term temperature records along with a measureable urbanisation parameter, plot ratio surrounding different automatic weather stations (AWS) were used. Models representing daytime and nighttime respectively were developed, and a logarithmic relationship between the rate of temperature change and plot ratio (degree of urbanisation) is observed. Baseline air temperature patterns over Hong Kong for 2009 were derived from two ASTER thermal satellite images, for summer daytime and nighttime respectively. Dynamic raster modeling was employed to project temperatures to 2039 in 10-year intervals on a per-pixel basis according to the degree of urbanization predicted. Daytime and nighttime temperatures in the highly urbanized areas are expected to rise by ca. 2 °C by 2039. Validation by projecting observed temperature trends at AWS, gave low average RMS errors of 0.19 °C for daytime and 0.14 °C for nighttime, and suggests the reliability of the method.