1951—2017年鞍山市气温变化特征及城市热岛变化

利用建站以来鞍山站和海城乡村站的一日四次观测数据和逐日平均、最低和最高气温资料,对1951-2017年鞍山市年、四季和各月平均气温和极端气温变化特征及其变率进行了分析,并对鞍山城市热岛变化进行探讨。结果表明：1951-2017年鞍山市年平均最低气温的递增趋势最强、平均气温次之、平均最高气温最弱,且均通过显著性检验。1951-2017年鞍山市年极端最高气温变化呈弱递减趋势,1951-1987年（突变前）呈递减趋势、1988-2017年（突变后）为递增趋势。1951-2017年鞍山市年极端最低气温呈显著递增趋势,1951-1987年（突变前）较整个阶段递增趋势更强,1988-2017年（突变后）呈递减趋势;突变前后极端最高和极端最低气温呈反相变化特征。1958-2017年鞍山市年最低气温的城市热岛强度最大、平均气温次之,最高气温最小、递增趋势最弱;秋、冬季鞍山城市热岛强度较其他季节更强,热岛指数递增显著;在每日4次定时气温观测中,14时鞍山市热岛强度最小,热岛指数呈递减趋势,其余时次均呈显著递增趋势,其中,02时鞍山热岛强度最强;鞍山市平均气温变化呈显著增暖趋势,城市热岛强度和热岛指数均呈显著递增,夜间递增尤为突出,说明鞍山城市热岛的显著增强是鞍山市气候变暖的一个主要原因。     

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。     

近15年北京夏季城市热岛特征及其演变

根据北京地区20个地面气象观测台站1990-2004年7月的气温资料，分析了最近15年来北京夏季城市热岛的最新特征和变化趋势，也分析了城市热岛与气温，城郊地表温度差与地表温度，气温和地表温度间的关系。结果表明：北京夏季夜间出现了强热岛，郊区城市也出现了热岛现象，但白天城市热岛相对夜间不明显。夜间城市热岛强度呈逐年增强趋势，但白天这种趋势不明显。夜间城市热岛与气温呈正相关，气温高的年份，城市热岛强度相对也大；夜间城郊地表温差与地表温度呈正相关，地表温度越高，城郊地表温差越大；夜间，气温与地表温度呈正相关，气温越高，地表温度也高。白天，这些相关相对夜间来说不那么明显。研究成果对北京城市发展规划和高温灾害的防治有一定的科学参考价值。     

兰州市近50年城市热岛强度变化特征

利用1956-2005年兰州市日平均气温、日最高气温和日最低气温,分析了近50年兰州市城市热岛效应变化,并利用城区和郊区3种气温的倾向率计算了城市热岛强度倾向率和热岛增温贡献率。结果表明：1956-2005年兰州市3种气温的城郊差均呈逐年上升趋势,平均气温、最高气温和最低气温的倾向率分别为每10年0.371℃、0.169℃和0.654℃,其中,最低气温的城郊差上升最明显。近50年兰州市增温主要发生在后25年（1981-2005年）,前25年除城区最低气温外基本上以降温为主。后25年中,城区年平均气温、最高气温和最低气温倾向率分别为每10年0.789℃、0.997℃和0.625℃,郊区则相应为每10年0.493℃、0.790℃和0.077℃,其中最高气温增温最显著,最低气温增温最少;以年平均、最高和最低气温表示的城市热岛强度的倾向率分别为每10年0.395℃、0.188℃和0.674℃,热岛效应对城区增温的贡献率分别达到87.0%、49.6%和100%。冬季城市和郊区的平均气温和最低气温倾向率最大,但热岛增温贡献率最大的是春、夏季气温,而不是冬季气温;这可能主要与兰州市冬季严重的空气污染有关, 因为其对城市热岛有一定的抑制作用。20世纪80年代以后兰州市热岛效应有增强的趋势,但平均气温和最高气温的热岛增温贡献率除个别季节外有所下降。     

海口城市化对热岛效应的影响

随着全球城市化快速发展、城市化水平逐渐提高,城市气候问题日益突出,城市热岛效应的形成机理也成为当前研究的热点。基于海口市2010—2015年社会经济、气象和Landsat卫星遥感数据资料,分析了海口市城市热岛强度变化和城市化发展对城市热岛效应的影响。结果表明,海口市的热岛强度逐渐增强,范围逐渐扩大。城市热岛强度具有明显的季节变化,春季最高,夏季和秋季逐次之,冬季最低。城市热岛强度与归一化建筑指数、人口密度和国内生产总值呈显著正相关,和归一化植被指数呈显著负相关,都通过了信度0.01的显著性检验。城市扩大植被面积在一定程度上有助于缓解城市热岛效应。     

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。     

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℃。     

顺德热岛强度变化及其与城市化发展的关系

根据顺德、鹤山国家气象观测站1984—2013年的气温资料,采用城郊对比法,分析了顺德城区热岛强度的变化特征,初步探讨了热岛强度与城市化发展的关系。结果表明,顺德的热岛强度基本在0.5℃左右,热岛强度的高值体现在平均气温和最低气温上;热岛强度具有明显的季节变化和月变化特征,冬季最强,达0.6℃,夏季最弱,仅为0.3℃,12月最大,达0.7℃,4、5月最小,只有0.3℃;年代际变化上热岛强度呈显著增加趋势,年平均气温计算的热岛强度增幅为0.014℃/年。     

拉萨市城市热岛效应分析研究

利用拉萨、墨竹工卡、尼木建站以来的多年历史资料和近两年新建的区域自动站、8个城市热岛效应自动气象站资料分析拉萨城市热岛强度日、季、年变化,时空分布及其可能的影响因子。分析表明:拉萨城市热岛强度呈显著的逐年增强趋势,在1978~2011年间平均每10年增加0.24℃;多年热岛强度冬季最强(2.0℃),其次是春季(1.8℃)和秋季(1.7℃),夏季强度最小(1.6℃);拉萨城市高温中心主要在城市中心,气温分布沿着高值区向两侧呈递减状态,郊外的气温比城区平均低0.9℃左右,夜间热岛效应强度明显高于白天。随着城市化进程的不断增强,大量改变的下垫面状况,不断增多的城市建筑群,骤增的人类活动和能源消耗,导致城市热岛强度不断增强。      

基于自动气象站资料的宜昌城市热岛分析

利用23个自动气象站2009—2018年逐小时气温资料,分析了宜昌城市热岛效应的时空演变,结果显示:(1)近10 a平均热岛强度为1.4℃,呈-0.172℃/10 a的缓慢减弱趋势。近10a夏季平均热岛强度为1.5℃,呈0.017℃/10 a的缓慢增强趋势。(2)热岛强度日变化是早晨到中午迅速减弱,午后至傍晚逐渐加强,夜间达到一天中最大值且保持稳定。(3)热岛强度年变化的谷点是1月,2—10月呈"台阶"状上升至峰值,每个"台阶"宽度约为3个月,11月—次年1月持续下降至谷点。热岛强度以夏季和秋季较强,冬季和春季较弱。(4)热岛强度的日、季节和年变化在时间上总体滞后于气温的变化;日、月最高气温时热岛弱,最低气温时热岛强。可能是城市下垫面热容量较大的"热滞效应"所致。(5)热岛强度高值区与城市核心区空间分布一致,高值区凸伸方向和趋势与城市建设发展方向高度一致。(6)近5 a热岛强度面积无明显变化,但城市中央区域热岛强度等级有所增强。     

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.     

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.     

IMPACT OF ATMOSPHERIC LOW-FREQUENCY OSCILLATION ON THE IMMIGRATION OF NILAPARVATA LUGENS(STL) IN HUNAN AND JIANGXI PROVINCES

Various features of the atmospheric environment affect the number of migratory insects, besides their initial population. However, little is known about the impact of atmospheric low-frequency oscillation(10 to 90 days) on insect migration. A case study was conducted to ascertain the influence of low-frequency atmospheric oscillation on the immigration of brown planthopper, Nilaparvata lugens(Stl), in Hunan and Jiangxi provinces. The results showed the following:(1) The number of immigrating N. lugens from April to June of 2007 through 2016 mainly exhibited a periodic oscillation of 10 to 20 days.(2) The 10-20 d low-frequency number of immigrating N. lugens was significantly correlated with a low-frequency wind field and a geopotential height field at 850 h Pa.(3) During the peak phase of immigration, southwest or south winds served as a driving force and carried N. lugens populations northward, and when in the back of the trough and the front of the ridge, the downward airflow created a favorable condition for N. lugens to land in the study area. In conclusion, the northward migration of N. lugens was influenced by a low-frequency atmospheric circulation based on the analysis of dynamics. This study was the first research connecting atmospheric low-frequency oscillation to insect migration.     

A COMPARATIVE ANALYSIS OF ATMOSPHERIC AND OCEANIC CONDITIONS BEFORE THE OCCURRENCE OF TWO TYPES OF EL NIO EVENTS

The atmospheric and oceanic conditions before the onset of EP El Ni?o and CP El Ni?o in nearly 30 years are compared and analyzed by using 850 hPa wind, 20℃ isotherm depth, sea surface temperature and the Wheeler and Hendon index. The results are as follows: In the western equatorial Pacific, the occurrence of the anomalously strong westerly winds of the EP El Ni?o is earlier than that of the CP El Ni?o. Its intensity is far stronger than that of the CP El Ni?o. Two months before the El Ni?o, the anomaly westerly winds of the EP El Ni?o have extended to the eastern Pacific region, while the westerly wind anomaly of the CP El Ni?o can only extend to the west of the dateline three months before the El Ni?o and later stay there. Unlike the EP El Ni?o, the CP El Ni?o is always associated with easterly wind anomaly in the eastern equatorial Pacific before its onset. The thermocline depth anomaly of the EP El Ni?o can significantly move eastward and deepen. In addition, we also find that the evolution of thermocline is ahead of the development of the sea surface temperature for the EP El Ni?o. The strong MJO activity of the EP El Ni?o in the western and central Pacific is earlier than that of the CP El Ni?o. Measured by the standard deviation of the zonal wind square, the intensity of MJO activity of the EP El Ni?o is significantly greater than that of the CP El Ni?o before the onset of El Ni?o.     

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.     

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.     

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