基于多年卫星遥感的江苏省夏季城市热岛特征分析

利用2003—2020年的MODIS土地覆盖类型和地表温度等数据,从地表温度、气温和城市化的角度分析了江苏省夏季城市热岛强度和面积的时空分布和变化趋势。结果表明：近20 a快速的城市化导致了江苏省夏季热岛强度(0.07℃·a^-1)和热岛面积(529 km²·a^-1)整体均呈增加趋势;其中热岛强度前期受城区升温影响,呈明显增强(0.18℃·a^-1),后期受郊区升温影响,呈明显减弱(-0.14℃·a^-1);热岛面积变化主要由弱热岛面积(297 km²·a^-1)和较强热岛面积(192 km²·a^-1)的增长趋势主导,强热岛面积呈前期增长(133 km²·a^-1)和后期减少(185 km²·a^-1)的变化趋势;高温对整个城区的热岛效应影响有限,但对城市核心区的热岛效应影响明显,对应的强热岛面积增加和热岛强度增强。     

乌鲁木齐-昌吉地区城市化对温度的影响及热岛效应分析

利用乌鲁木齐-昌吉地区3个城市气象站和3个郊区气象站1976-2008年的气温观测资料,分析了乌鲁木齐及周边城市发展的热岛效应。结果表明,33年来乌鲁木齐-昌吉地区城市化对城市地面平均气温具有显著影响,气温随年代递增率城市大于农村,城市和郊区年平均气温递增率分别为0.79和0.38℃.(10a)-1;城市气温的极端性趋于弱化,近33年地面气温递增的最主要表现是城市平均最低气温明显上升,城市和郊区年平均最低气温的递增率分别为1.12和0.41℃.(10a)-1;城市气温日较差呈明显的下降趋势,郊区却略呈上升趋势;城市寒冷日数减少的趋势大于农村,城市采暖季最低气温随年代的递增趋势最为显著,采暖季城市和农村平均最低气温的递增率分别是1.46和0.57℃.(10a)-1;年平均热岛强度递增率为0.71℃.(10a)-1,冬季为1.06℃.(10a)-1,秋、春和夏季分别为0.63,0.57和0.46℃.(10a)-1。热岛强度夜间强、白天弱,02:00,08:00,14:00和20:00的平均热岛强度分别为2.9,2.9,0.0和3.0℃,其中02:00和08:00热岛强度递增率分别是1.17和1.13℃.(10a)-1,20:00为0.70℃.(10a)-1,冬季没有逆温的状况下,市区高温区与繁华区相吻合,城区中心的温度比郊区高3~4℃。     

珠三角城市群热岛及其气象影响因子研究

城市群热岛效应的合理评估关系到城市化对区域气候和环境的影响研究。以珠三角城市群为分析对象,并将其划分为东中西三个区,分析1999—2008年20个气象观测站资料,利用实测气温标准差方法定量选取郊区代表站,通过城郊对比方法研究热岛的时空特征及其气象影响因子,结果表明:珠三角平均热岛强度为0.71 ℃,线性增加趋势为0.29 ℃/(10 a)。热岛强度空间结构呈纬向三极子分布,广州、佛山、东莞和深圳等经济发达城市为高强度带,东西两侧逐渐减弱为两个低强度中心。热岛强度秋强(1.06 ℃)春弱(0.39 ℃)的季节变化和夜强(0.91 ℃)昼弱(0.53 ℃)的日变化特征明显。影响热岛出现频率的气象因子依次为低云量、相对湿度、风速和降雨量,并表现为负相关。研究结果对珠三角城市群的发展规划及气象和环境风险区划有良好借鉴意义。      

黑龙江省近50a农业界限温度变化特征分析

利用黑龙江省6个站点的1961-2010年日平均气温资料,利用5 d滑动平均法对该省≥0℃、10℃界限温度进行了分析。结果表明:近50 a来,黑龙江省≥0℃、10℃起始日期均呈提前趋势,分别为平均每10 a提前1.9、1.3 d。≥0℃、10℃终止日期均呈推迟趋势,分别为每10 a推迟1.2、0.6 d。稳定通过≥0℃积温历年平均值为2 961.7℃,倾向率为39.0℃/10a,呈递增趋势;通过≥0℃持续日数历年平均为204 d,倾向率为3.1 d/10a,呈递增趋势。稳定通过≥10℃积温历年平均值为2 515.3℃,倾向率为37.4℃/10a,呈递增趋势;稳定通过≥10℃持续日数历年平均为135 d,倾向率为2.0 d/10a,呈递增趋势。     

珠三角城市集群化发展对热岛强度的影响

利用珠三角城市发展资料及珠三角地区近28年的气温资料,研究了珠三角城市集群化发展指标与城市热岛效应之间的关系。认为:(1)珠三角城市集群化发展指标在2000年前发展缓慢,2000年后,珠三角城市集群化发展指标增长率比2000年前增长了5~9倍;(2)热岛强度增温率2000年前为0.34℃·(10a)~(-1),而2000年后热岛强度增温率为0.69℃·(10a)~(-1),热岛强度增温率增加了1倍。(3)珠三角地区城市热岛强度逐年增强,年内热岛强度雨季和干季变化明显,雨季热岛强度弱而干季热岛强度强,最弱热岛出现在降水充沛的7月,最强热岛出现在天气干燥的12月。(4)采用灰色关联度分析结果显示:城市建成区面积、工业总产值、全年总用电量和常住人口等指标对气温和热岛强度影响明显;根据城市发展指标对气温和热岛强度的关联度,采用灰色模型拟合了城市集群化发展指标对气温和热岛强度的平均拟合相对误差分别为2.7%和7.0%,说明该模型可以较好地拟合城市集群化发展指标对气温和热岛强度的影响。     

北京地区城郊极端温度事件的变化趋势及差异分析

利用北京地区城郊16个气象观测站1979～2008年逐日平均、最高和最低温度的均一化资料,分析了近30年北京地区城、郊区极端温度事件发生频次(强度)的变化趋势,并对比了城郊差异以及城市热岛强度对城郊差异的影响.研究结果显示:从发生频次来看,近30年城区极端低温事件的减小幅度[5.94 d (10 a)-1]高于郊区的减小幅度[-5.28 d (10 a)-1],而极端高温事件的增加幅度在城区[4.33 d (10 a)-1]和郊区[4.42 d (10 a)-1]之间差别不大,定量化的诊断结果进一步证明了城区和郊区在极端温度事件发生频次上的差别很小.从发生强度来看,近30年城区极端温度事件的年平均发生强度明显高于郊区,但在变化趋势上,城区极端低温事件的减弱幅度略高于极端高温事件的增强幅度,相差0.042℃(10 a)-1,而在郊区极端低温事件的减弱幅度却略低于极端高温事件的增强幅度,相差0.052℃(10 a)-1.城郊差异的定量化分析结果表明,极端温度事件在城区强度一般大于郊区强度,城区与郊区强度差值均为正值(除1982年和1985年极端高温事件强度差值为负).热岛强度与极端温度事件城郊差异的相关性统计发现,极端温度事件发生频次和发生强度在城郊之间的差别与热岛强度均没有明显的相关特征,该结果说明城市热岛效应对北京超大城市市区和郊区影响基本一致,其差异性是有限的.     

气候变化对石羊河流域生态环境的影响分析

利用石羊河流域1959—2018年气象、水文和卫星遥感资料,采用线性倾向率、滑动t检验和相关系数(Pearson)等方法,分析石羊河流域内生态环境因素的变化事实及相互关系,得到气候变化对流域生态环境的影响程度。结果表明：石羊河流域气温呈显著上升趋势,增温速度为下游0.42℃·(10 a)^-1>中游0.36℃·(10 a)^-1>上游0.35℃·(10 a)^-1,近10 a增温最显著,较20世纪60年升高了1.67℃。四季气温均呈显著上升趋势,增温速度为冬季>秋季>春季>夏季。降水呈缓慢增加趋势,增幅为上游8.3 mm·(10 a)^-1>中游7.0 mm·(10 a)^-1>下游4.1 mm·(10 a)^-1,近10 a增加最显著,较20世纪60年代增加了17%。四季降水呈弱增加趋势,增加幅度为夏季>春季>秋季>冬季。河流流量基本持平,植被覆盖面积和归一化植被指数(NDVI)显著增大。近20 a流域气候...     

南京城市热岛效应研究

利用4个气象站1961～2005年气温资料,对南京市的城市热岛效应进行了全面、细致的研究。结果表明：1）平均而言,南京市的热岛强度基本在0.5 ℃左右,热岛强度的高值体现在最低气温上,极端情况可能达到6 ℃左右;2）南京城市热岛效应具有明显的季节变化和日变化特征,夏半年要强于冬半年,夜间强于白天;3）随着城市规模的发展,南京市的城市热岛效应为增强趋势,用年平均气温计算获得的热岛强度增幅为0.109 ℃·(10 a)-1。     

1971—2010年京津冀大城市热岛效应多时间尺度分析

利用1971—2010年均一化的京津冀区域逐日气温数据与质量控制后的2011年自动站逐时气温数据,分析了北京、天津和石家庄热岛效应的多尺度时间变化特征。结果表明,三个城市平均、最高和最低气温的热岛效应呈非对称性特征,最强为最低气温的热岛效应,其次为平均气温的热岛效应,最弱为最高气温的热岛效应。北京平均气温的热岛效应最强,其次为天津,石家庄相对较弱,石家庄平均气温的热岛效应近40年呈显著上升趋势,每10年达0.13℃。石家庄最高气温的热岛效应最强,其次为北京,最小为天津,近40年北京最高气温的热岛效应呈缓慢上升趋势,每10年增加0.06℃,石家庄变化不明显,天津呈微弱下降趋势。最低气温的热岛在北京最强,其次为天津,最小为石家庄,近40年最低气温热岛效应天津呈明显上升趋势,每10年增加0.18℃,其次为石家庄,北京呈微弱下降趋势。三个城市的平均气温、最低气温的热岛效应季节变化通常表现为夏季较弱,冬季最强。三个城市最高气温的热岛效应季节变化差异较大,北京10月热岛效应最弱,其他月份变化不大;天津热岛效应6月最弱,在1或12月最强;石家庄4和5月热岛效应最强,10月热岛效应最弱。由2011年自动站数据得到的平均气温热岛效应与1971—2010年的40年平均得到的平均气温的热岛效应季节变化具有类似的规律。2011年自动站热岛效应在一天中表现为白天热岛强度较低,而夜间热岛强度较高。     

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。     

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.