成都地区夏季城市热岛变化及其与城市发展的关系

利用2000-2010年MODIS地表温度产品影像,结合DMSP/OLS夜间灯光数据,分析了成都地区夏季城市温度场及其城市热岛变化的分布特征及其演变规律。结果表明：随着城市化加快,成都地区夏季热环境发生了较大变化,整个区域以中温区向次高温区转换为主。成都地区热岛效应昼夜变化较大：白天热岛面积不断增大,与周围卫星城热岛连成一体,2000年和2010年城市热岛对区域的增温贡献分别为0.13℃和0.29℃,变化量达0.16℃,夜间并不存在大面积强热岛区。旧城区内城市热岛面积有所增加,但不显著,城市扩展区内热岛的规模显著增大,2010年较2000年新增强热岛区域面积166.43 km²,变化幅度达54%。高城市化水平的成都市地区的日较差相对于周边低城市化水平地区明显减少。同时,城市热岛还与人口的平方根具有很好的正相关关系,成都地区非农业人口规模每增长100万人,热岛效应强度增加0.4℃。     

南京地区城市化对陆地生态系统总初级生产力的影响

以南京地区为研究区域,基于多源遥感数据和降尺度植被生产力数据,分析了2000～2020年南京城市扩张进程及对总初级生产力(Gross Primary Productivity, GPP)直接影响的时空变化,同时分析了气候变化与城市化的间接效应对直接影响的补偿作用。结果表明,南京地区在2000～2020年城区范围出现明显扩张,不透水面的覆盖面积由620.31 km²增长至2020年的1245.66 km²,增加了一倍以上。由于城市化强度提高,土地覆盖变化产生的直接影响导致南京城区GPP下降-345.98 g(C) m^-2 a^-1,而区域气候变化和城市化的间接效应使城区GPP增加298.67 g(C) m^-2 a^-1,抵消了直接效应的86.33%。城区范围内间接影响的增加趋势和贡献率高于郊区,证明城市环境促进了城区剩余植被生长。在全球变暖和城市化继续发展的背景下,了解城市扩张如何影响植被生产力有助于更好地应对全球变化挑战、推动构建生态文明城市,具有重要的现实意...     

福建省晋江市城市热岛强度时空变化特征分析

利用传统的气象站法, 结合空间统计学方法(普通克里金插值法), 对福建省晋江市2010—2014年40个自动气象站逐小时温度资料加以计算处理, 分析了晋江市年、季、昼夜热岛强度时空变化规律。(1)晋江市年、季、昼夜热岛强度都呈带状分布, 等值线呈西南-东北走向, 年、季、昼夜变化趋势显著, 北部热岛强度高于南部。五年间热岛强度持续增强, 但增幅不大, 增速放缓。(2)城市化水平的提高, 会导致热岛强度高值出现季节提前, 故旅游区秋冬季热岛强度高于春夏季, 中心城区和产业经济区夏秋季热岛强度高于冬春季。(3)晋江市热岛效应昼夜空间分布格局差异性大, 夜间热岛强度显著高于白天, 最低值出现在14—16时, 中心城区和产业经济区最低值出现时间较旅游区略推迟, 三个功能区的最高值均出现在凌晨。      

城市化对北京地区气候的影响

利用北京地区20个气象站36年(1970—2005年)的逐日雨量、平均风速和冬季08时平均温度资料,对北京城市化进程中城市气候变化趋势进行了分析。结果表明,(1)36年来热岛效应呈现强度逐渐增强、面积逐渐增大、由单一向多个热岛中心演变的趋势,2000—2005年热岛强度最大达2.11℃,城区冬季的平均增温率为0.298℃/10a。(2)城市化发展使得北京地区降水量呈现不均匀分布态势。20世纪70年代城市西部降水较多,东南部降水少;80年代整个城区处于少雨区;90年代城市西部、南部降水少,东北部是大雨量区。2000年以后降水较少区域自城区逐渐朝东南方向扩展。(3)不断增高、密度不断加大的建筑物对气流的阻滞作用使得城区平均风速呈减少趋势,城区的平均风速70年代是2.49 m.s-1,80年代是2.32 m.s-1,90年代是2.16 m.s-1,2000—2005年是2.28 m.s-1,平均风速递减率为0.05 m.s-1.(10a)-1。(4)人口密度的对数与气温呈线性相关,相关系数为0.65;城区面积与温度呈线性相关,相关系数为0.6387。     

基于MODIS数据的近10年宜昌城市热岛效应时空变化特征

利用2010-2019年宜昌研究区2、5、8月和11月晴空天气的MODIS地表温度产品,结合GIS技术,分析热岛效应昼夜、季节和年际变化特征.结果表明:(1)热岛空间分布受地形地貌影响较大,热岛区主要分布在主城区至东南部平原地带;(2)热岛区和冷岛区面积白天均多于夜间,热岛强度白天强于夜间;(3)夏季热岛区面积达到最大...     

基于Landsat卫星数据的山东临沂市热岛效应研究

利用Landsat卫星数据分别反演了2005年和2014年临沂市的地表温度和不透水层指数，分析了城市化进程对临沂市热岛效应的影响。结果表明，2005年临沂市表现为中等强度的热岛效应，2014年表现为强热岛效应。利用地面站点资料统计分析来看，2005～2014年，临沂市热岛强度总体呈波动增加的趋势,冬季最强，春秋季次之，夏季较弱。分析城市化因子发现，城市经济、人口、用电消耗、城市房屋面积增量等多个因素对城市热岛强度变化的影响，其相关系数分别为0.86、0.82、0.67、0.81，其中房屋面积增量与热岛强度增强密切相关。从不透水层指数分布图的动态变化来看，也说明了城市化进程中城镇建筑和硬化的路面的增多导致了热岛强度的增强。     

西宁城市热岛效应分析

西宁作为青藏高原最大的城市,近年来随着城市化的发展,城市热岛效应及其所带来的影响日益明显。本文利用西宁市城市和郊区气象观测站逐小时气温观测资料,分析了西宁市平均气温、最高气温和最低气温日内、候平均热岛强度变化特征,结果显示:(1)相对于郊区,西宁城区平均气温日内变化幅度较小,16—17时(北京时,下同)表现为弱的冷岛效应,冷岛强度为0.034℃,日出前的06—07时热岛强度表现最强,热岛强度最高可达3.01℃;(2)春季和夏季一天中均为热岛效应,且热岛效应日内变化幅度较小,分别为2.76℃和2.12℃。秋季和冬季在日出前的07—08时热岛强度最强,分别为2.89℃和4.14℃,秋季16—17时和冬季15—17时表现为冷岛效应,最大冷岛强度分别为0.34℃和0.53℃;(3)西宁城区1月第3候热岛强度最强为3.40℃,7月第2候热岛强度最弱为1.07℃。其中白天在1月第3候热岛强度最强为0.88℃,9月第1候最弱为0.13℃,热岛强度年内变幅较小仅为0.75℃,而夜晚在1月第3候最强为5.93℃,7月第2候最弱为1.62℃,热岛强度年内变化幅度达4.30℃;(4)西宁城区候平均最高气温在春季和夏季表现为热岛效应,热岛强度平均为0.58℃,而在秋冬季表现为冷岛效应,冷岛强度分别为1.84℃。候平均最低气温全年均表现为热岛效应,其中夏季相对较弱为3.22℃,冬季表现最强达到5.11℃。     

1981—2015年呼和浩特市夏季热岛效应时空变化特征分析

文章选取1981—2015年呼和浩特市及周边地区气温和地表温度等资料,通过其年际变化趋势,分析了呼和浩特市夏季城市热岛效应的时空变化特征。结果表明:2004—2012年呼和浩特市夏季城市热岛效应明显加剧,其中2010年是热岛效应最强的一年;以最低气温表征的热岛强度更能明显地反映出热岛效应加剧的趋势,热岛强度的变化趋势与月平均最高气温的变化趋势更为一致;在热岛效应加剧的背景下,月平均最高地表温度的变化尤为显著。     

基于MODIS的贵阳城市热岛时空特征分析

为揭示贵阳市城市热岛效应时空变化规律,利用2003—2019年的MODIS地表温度产品(MYD11A2),获取贵阳市长时间序列地表温度,结合3S技术对地表温度进行局地热岛强度计算,划分城市热岛强度等级,并从年代际、年际、季节变化以及日时间尺度对贵阳市城市热岛变化的分布特征及其演变规律进行分析。结果表明:(1)2003—2019年贵阳市城市热岛效应总体呈增强趋势,且在2012年发生突变现象,此后热岛效应更加显著,出现强热岛区,中热岛以上区域面积扩大;(2)贵阳市2003、2004、2005、2008年为热岛强度偏弱年,2016—2019年为热岛强度偏强年,偏弱年和偏强年热岛强度空间分布与突变前后相似,热岛区面积比例整体变化不大,偏强年除弱热岛区面积比例变小外,其他各热岛等级面积均增加;(3)贵阳市城市热岛效应夏季最强,其次是春季和冬季,秋季最弱。就空间分布而言,贵阳市城市热岛区在秋、冬季分布较分散,而在春、夏季分布较为集中;(4)城市热岛区主要集中在主城区,夜晚相比于白天分布更为集中,且热岛效应夜晚强于白天。     

基于FY-3卫星数据的西安市城市热岛特征分析

基于2011—2017年FY-3B/VIRR气象卫星影像数据及同期气象观测数据,应用改进型贝克尔(Becker)"分裂窗"地表温度反演算法计算地表温度,根据土地利用类型数据进行城郊对比,分析了西安市春、夏、秋三个季节城市热岛总面积、强热岛面积和热岛比例指数。结果表明:1)遥感反演温度与气象站点监测数据变化趋势基本一致,三季地表温度基本以西安市城区为中心呈环状递减;2)各季节强热岛面积占比年际变化明显,夏季强热岛面积占比远高于春、秋两季的,是后者的2倍以上;3)春、夏、秋三季强热岛区域主要集中在西安市城区和长安区,临潼区、长安区、鄠邑区、西安市城区夏季热岛面积占总面积的50%以上,周至县、高陵区的较小;4)总热岛比例指数总体上波动较大,年际上2016年的最大;春、夏季2014年的最大,秋季2016年的最大;总体城郊热岛差异2017年的最大,季节性城郊热岛差异表现为春季2016年的最大,夏、秋季2017年的最大,夏季城郊热岛差异明显高于春、秋季的。     

CHARACTERISTICS AND TRENDS OF CLIMATIC EXTREMES IN CHINA DURING 1959–2014

The spatial and temporal variations of daily maximum temperature(Tmax), daily minimum temperature(Tmin), daily maximum precipitation(Pmax) and daily maximum wind speed(WSmax) were examined in China using Mann-Kendall test and linear regression method. The results indicated that for China as a whole, Tmax, Tmin and Pmax had significant increasing trends at rates of 0.15℃ per decade, 0.45℃ per decade and 0.58 mm per decade,respectively, while WSmax had decreased significantly at 1.18 m·s~(-1) per decade during 1959—2014. In all regions of China, Tmin increased and WSmax decreased significantly. Spatially, Tmax increased significantly at most of the stations in South China(SC), northwestern North China(NC), northeastern Northeast China(NEC), eastern Northwest China(NWC) and eastern Southwest China(SWC), and the increasing trends were significant in NC, SC, NWC and SWC on the regional average. Tmin increased significantly at most of the stations in China, with notable increase in NEC, northern and southeastern NC and northwestern and eastern NWC. Pmax showed no significant trend at most of the stations in China, and on the regional average it decreased significantly in NC but increased in SC, NWC and the mid-lower Yangtze River valley(YR). WSmax decreased significantly at the vast majority of stations in China, with remarkable decrease in northern NC, northern and central YR, central and southern SC and in parts of central NEC and western NWC. With global climate change and rapidly economic development, China has become more vulnerable to climatic extremes and meteorological disasters, so more strategies of mitigation and/or adaptation of climatic extremes,such as environmentally-friendly and low-cost energy production systems and the enhancement of engineering defense measures are necessary for government and social publics.     

Could the Recent Taal Volcano Eruption Trigger an El Ni?o and Lead to Eurasian Warming?

正The Taal Volcano in Luzon is one of the most active and dangerous volcanoes of the Philippines. A recent eruption occurred on 12 January 2020(Fig. 1a), and this volcano is still active with the occurrence of volcanic earthquakes. The eruption has become a deep concern worldwide, not only for its damage on local society, but also for potential hazardous consequences on the Earth's climate and environment.     

VARIABILITY OF INTER-ANNUAL RELATIONSHIP BETWEEN INDIAN OCEAN DIPOLE AND HUAXI REGION’S AUTUMN PRECIPITATION

The moving-window correlation analysis was applied to investigate the relationship between autumn Indian Ocean Dipole (IOD) events and the synchronous autumn precipitation in Huaxi region, based on the daily precipitation, sea surface temperature (SST) and atmospheric circulation data from 1960 to 2012. The correlation curves of IOD and the early modulation of Huaxi region’s autumn precipitation indicated a mutational site appeared in the 1970s. During 1960 to 1979, when the IOD was in positive phase in autumn, the circulations changed from a “W” shape to an ”M” shape at 500 hPa in Asia middle-high latitude region. Cold flux got into the Sichuan province with Northwest flow, the positive anomaly of the water vapor flux transported from Western Pacific to Huaxi region strengthened, caused precipitation increase in east Huaxi region. During 1980 to 1999, when the IOD in autumn was positive phase, the atmospheric circulation presented a “W” shape at 500 hPa, the positive anomaly of the water vapor flux transported from Bay of Bengal to Huaxi region strengthened, caused precipitation ascend in west Huaxi region. In summary, the Indian Ocean changed from cold phase to warm phase since the 1970s, caused the instability of the inter-annual relationship between the IOD and the autumn rainfall in Huaxi region.     

ANALYSIS OF “BIMODAL PATTERN” STORM ACTIVITY CHARACTERISTICS OF THE BAY OF BENGAL

Storms that occur at the Bay of Bengal (BoB) are of a bimodal pattern, which is different from that of the other sea areas. By using the NCEP, SST and JTWC data, the causes of the bimodal pattern storm activity of the BoB are diagnosed and analyzed in this paper. The result shows that the seasonal variation of general atmosphere circulation in East Asia has a regulating and controlling impact on the BoB storm activity, and the “bimodal period” of the storm activity corresponds exactly to the seasonal conversion period of atmospheric circulation. The minor wind speed of shear spring and autumn contributed to the storm, which was a crucial factor for the generation and occurrence of the “bimodal pattern” storm activity in the BoB. The analysis on sea surface temperature (SST) shows that the SSTs of all the year around in the BoB area meet the conditions required for the generation of tropical cyclones (TCs). However, the SSTs in the central area of the bay are higher than that of the surrounding areas in spring and autumn, which facilitates the occurrence of a “two-peak” storm activity pattern. The genesis potential index (GPI) quantifies and reflects the environmental conditions for the generation of the BoB storms. For GPI, the intense low-level vortex disturbance in the troposphere and high-humidity atmosphere are the sufficient conditions for storms, while large maximum wind velocity of the ground vortex radius and small vertical wind shear are the necessary conditions of storms.     

LOW-FREQUENCY CIRCULATION AND EXTENDED-RANGE FORECAST IN CONNECTION WITH AUTUMN EXTREME HEAVY RAINFALL PROCESS IN HAINAN

Observed daily precipitation data from the National Meteorological Observatory in Hainan province and daily data from the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis-2 dataset from 1981 to 2014 are used to analyze the relationship between Hainan extreme heavy rainfall processes in autumn (referred to as EHRPs) and 10–30 d low-frequency circulation. Based on the key low-frequency signals and the NCEP Climate Forecast System Version 2 (CFSv2) model forecasting products, a dynamical-statistical method is established for the extended-range forecast of EHRPs. The results suggest that EHRPs have a close relationship with the 10–30 d low-frequency oscillation of 850 hPa zonal wind over Hainan Island and to its north, and that they basically occur during the trough phase of the low-frequency oscillation of zonal wind. The latitudinal propagation of the low-frequency wave train in the middle-high latitudes and the meridional propagation of the low-frequency wave train along the coast of East Asia contribute to the ‘north high (cold), south low (warm)’ pattern near Hainan Island, which results in the zonal wind over Hainan Island and to its north reaching its trough, consequently leading to EHRPs. Considering the link between low-frequency circulation and EHRPs, a low-frequency wave train index (LWTI) is defined and adopted to forecast EHRPs by using NCEP CFSv2 forecasting products. EHRPs are predicted to occur during peak phases of LWTI with value larger than 1 for three or more consecutive forecast days. Hindcast experiments for EHRPs in 2015–2016 indicate that EHRPs can be predicted 8–24 d in advance, with an average period of validity of 16.7 d.     

AN ATTRIBUTION ANALYSIS OF CHANGES IN POTENTIAL EVAPOTRANSPIRATION IN THE BEIJING–TIANJIN–HEBEI REGION UNDER CLIMATE CHANGE

Based on the measurements obtained at 64 national meteorological stations in the Beijing–Tianjin–Hebei (BTH) region between 1970 and 2013, the potential evapotranspiration (ET0) in this region was estimated using the Penman–Monteith equation and its sensitivity to maximum temperature (Tmax), minimum temperature (Tmin), wind speed (Vw), net radiation (Rn) and water vapor pressure (Pwv) was analyzed, respectively. The results are shown as follows. (1) The climatic elements in the BTH region underwent significant changes in the study period. Vw and Rn decreased significantly, whereas Tmin, Tmax and Pwv increased considerably. (2) In the BTH region, ET0 also exhibited a significant decreasing trend, and the sensitivity of ET0 to the climatic elements exhibited seasonal characteristics. Of all the climatic elements, ET0 was most sensitive to Pwv in the fall and winter and Rn in the spring and summer. On the annual scale, ET0 was most sensitive to Pwv, followed by Rn, Vw, Tmax and Tmin. In addition, the sensitivity coefficient of ET0 with respect to Pwv had a negative value for all the areas, indicating that increases in Pwv can prevent ET0 from increasing. (3) The sensitivity of ET0 to Tmin and Tmax was significantly lower than its sensitivity to other climatic elements. However, increases in temperature can lead to changes in Pwv and Rn. The temperature should be considered the key intrinsic climatic element that has caused the "evaporation paradox" phenomenon in the BTH region.     

Revisiting the Concentration Observations and Source Apportionment of Atmospheric Ammonia

正While China’s Air Pollution Prevention and Control Action Plan on particulate matter since 2013 has reduced sulfate significantly, aerosol ammonium nitrate remains high in East China. As the high nitrate abundances are strongly linked with ammonia, reducing ammonia emissions is becoming increasingly important to improve the air quality of China. Although satellite data provide evidence of substantial increases in atmospheric ammonia concentrations over major agricultural regions, long-term surface observation of ammonia concentrations are sparse. In addition, there is still no consensus on     

全球贸易隐含碳变化及其影响分析

基于最新的GTAP8 (Global Trade Analysis Project）数据库,使用投入产出法,分析了2004年到2007年全球贸易变化下南北集团贸易隐含碳变化及对全球碳排放的影响。结果显示,随着发展中国家进出口规模扩张,全球贸易隐含碳流向的重心逐渐向发展中国家转移。2004年到2007年,发达国家高端设备制造业和服务业出口以及发展中国家资源、能源密集型行业及中低端制造业出口的趋势加强,该过程的生产转移导致全球碳排放增长4.15亿t,占研究时段全球贸易隐含碳增量的63%。未来发展中国家的出口隐含碳比重还将进一步提高。贸易变化带来的南北集团隐含碳流动变化对全球应对气候变化行动的影响日益突出,发达国家对此负有重要责任。     

COMPARATIVE ANALYSIS OF VARIOUS DATA OF AIR–SEA TEMPERATURE DIFFERENCE AND ITS VARIATION ACROSS SOUTH CHINA SEA IN THE PAST 35 YEARS

Using the International Comprehensive Ocean-Atmosphere Data Set(ICOADS) and ERA-Interim data, spatial distributions of air-sea temperature difference(ASTD) in the South China Sea(SCS) for the past 35 years are compared,and variations of spatial and temporal distributions of ASTD in this region are addressed using empirical orthogonal function decomposition and wavelet analysis methods. The results indicate that both ICOADS and ERA-Interim data can reflect actual distribution characteristics of ASTD in the SCS, but values of ASTD from the ERA-Interim data are smaller than those of the ICOADS data in the same region. In addition, the ASTD characteristics from the ERA-Interim data are not obvious inshore. A seesaw-type, north-south distribution of ASTD is dominant in the SCS; i.e., a positive peak in the south is associated with a negative peak in the north in November, and a negative peak in the south is accompanied by a positive peak in the north during April and May. Interannual ASTD variations in summer or autumn are decreasing. There is a seesaw-type distribution of ASTD between Beibu Bay and most of the SCS in summer, and the center of large values is in the Nansha Islands area in autumn. The ASTD in the SCS has a strong quasi-3a oscillation period in all seasons, and a quasi-11 a period in winter and spring. The ASTD is positively correlated with the Nio3.4 index in summer and autumn but negatively correlated in spring and winter.     

Retrieval of outgoing longwave radiation from COMS narrowband infrared imagery

Hourly outgoing longwave radiation(OLR) from the geostationary satellite Communication Oceanography Meteorological Satellite(COMS) has been retrieved since June 2010. The COMS OLR retrieval algorithms are based on regression analyses of radiative transfer simulations for spectral functions of COMS infrared channels. This study documents the accuracies of OLRs for future climate applications by making an intercomparison of four OLRs from one single-channel algorithm(OLR12.0using the 12.0 μm channel) and three multiple-channel algorithms(OLR10.8+12.0using the 10.8 and 12.0 μm channels; OLR6.7+10.8using the 6.7 and 10.8 μm channels; and OLR All using the 6.7, 10.8, and 12.0 μm channels). The COMS OLRs from these algorithms were validated with direct measurements of OLR from a broadband radiometer of the Clouds and Earth's Radiant Energy System(CERES) over the full COMS field of view [roughly(50°S–50°N, 70°–170°E)] during April 2011.Validation results show that the root-mean-square errors of COMS OLRs are 5–7 W m-2, which indicates good agreement with CERES OLR over the vast domain. OLR6.7+10.8and OLR All have much smaller errors(～ 6 W m-2) than OLR12.0and OLR10.8+12.0(～ 8 W m-2). Moreover, the small errors of OLR6.7+10.8and OLR All are systematic and can be readily reduced through additional mean bias correction and/or radiance calibration. These results indicate a noteworthy role of the6.7 μm water vapor absorption channel in improving the accuracy of the OLRs. The dependence of the accuracy of COMS OLRs on various surface, atmospheric, and observational conditions is also discussed.