一次阴雨条件下河北中南部气溶胶的参数特征分析

利用2009年9月8日华北中南部上空的飞机探测资料,分析了石家庄市和邯郸市区附近大气气溶胶的粒子数浓度、直径、尺度谱分布等时空变化特征。分析表明,降水天气条件下,气溶胶粒子平均数浓度约为137.6个/cm3,平均直径约为0.26μm。气溶胶主要集中于2 000 m以下的对流层低层,气溶胶浓度总体上随高度增加而降低;雨后阴天轻雾天气条件下,气溶胶粒子平均数浓度约为164.7个/cm3,平均直径约为0.16μm。气溶胶在逆温层下累积现象明显,云内气溶胶数浓度明显减少。气溶胶粒子浓度水平变化受下垫面、云区分布等局地因子影响较大。石家庄600 m和6 600 m气溶胶粒子谱呈单峰分布,3 000 m粒子谱呈双峰分布。邯郸6 400 m粒子谱宽较窄,呈单峰分布。     

山东地区秋季飞机观测气溶胶特征的初步分析

综合分析了2006年秋季在山东省进行的0.5—8.0μm范围内的大气气溶胶飞机观测的0—4500m气溶胶数浓度垂直分布,初步讨论了气溶胶与温度的关系,并分析了对气溶胶粒子谱的垂直分布情况。结果显示,气溶胶数浓度随高度呈递减趋势,在逆温层附近气溶胶有累计现象;受城市环境的影响,同一区域城市上空或者城市的下风方气溶胶粒子平均浓度都大于上风方;气溶胶粒子谱受不同天气背景的影响,出现不同类型的谱型,随高度的变化,谱型也有很大的变化。     

石家庄秋季大气气溶胶物理特征分析

利用１９９０年秋季在石家庄地区不同天气条件下飞机观测对流层低层（距地面４０００ｍ以下高度）大气气溶胶的观测资料，分析了气溶胶粒子数密度、质量浓度水平和垂直分布特征及其日变化。结果表明，晴空下，石家庄地区气溶胶源于本地，地面质量浓度为０．１５×１０－９—０．８５×１０－９·ｃｍ－３，高度４０００ｍ以下谱分布特征值逆温层影响气溶胶粒子的向上输送，使其在送温层上下出现不连续分布；气溶胶的日变化表现为上午数密度大于下午，但下午粒子谱变宽；城市效应影响气溶胶粒子分布，城市上空气溶胶粒子数密度比郊区高１５％－３０％。     

石家庄地区夏季气溶胶飞机探测资料分析

利用石家庄地区2005年6月21日的一次晴空飞机探测资料,分析了气溶胶粒子的垂直分布特征及粒子谱分布特征,并初步讨论了气象因子对气溶胶分布的影响。结果表明,边界层内气溶胶平均数浓度达到4902cm-3,主要是由霾造成的。高空风场对气溶胶浓度的分布有着重要影响,风速较大的情况下,气溶胶在该层的水平输送较为活跃,出现气溶胶浓度低值带;城市的地理位置以及城市热岛效应也影响气溶胶粒子的分布,同一高度上往往市区内气溶胶的浓度比郊区要高。气溶胶粒子谱呈单峰分布,高度越高,粒子数浓度变化越小;低层尺度谱最宽,中高层较窄。利用幂函数N(D)=AD-B可以很好的对不同高度的气溶胶粒子谱进行拟合。     

衡水湖湿地气溶胶分布的飞机观测

利用机载粒子探测系统PMS（particle measurement system）对华北衡水湖湿地进行了一次晴空气溶胶飞机探测,研究结果表明：衡水湖上空气溶胶粒子比城市、城镇上空气溶胶粒子小。在低层,衡水湖上空气溶胶数密度比衡水市、枣强镇大;在高层,城市、城镇气溶胶数密度比衡水湖大许多。衡水湖地区气溶胶粒子直径绝大多数为0．1-0．25μm,直径为0．25—3．0μm的气溶胶粒子非常少。衡水湖上空与城市、城镇上空气溶胶特征和垂直分布不同。     

一次霾条件下石家庄上空气溶胶的观测研究

利用2010年9月1日石家庄市区一次飞机探测的气溶胶资料,分析了石家庄市区上空大气气溶胶的数浓度与直径的垂直、水平分布特征及粒子谱分布。结果表明:600—3000 m高度范围内,气溶胶粒子平均数浓度为1443.1个/cm~3,粒子平均直径为0.194μm。3000—6900 m高度范围,气溶胶粒子平均数浓度为95.3个/cm3,粒子平均直径为0.192μm。气溶胶数浓度随着高度增加而迅速减少,受逆温层与云区分布的影响,数浓度曲线呈现一定程度的波动。由于探测当天高空风的影响,粒子数浓度明显比其他霾天气条件下的研究结果要低。云中,气溶胶数浓度与粒子平均直径数呈负相关性。云层对气溶胶的垂直分布影响较大。气溶胶粒子谱覆盖了0.10~1.05μm的尺度范围,粒子主要集中在0.1~0.3μm的范围内。600 m、1200 m、1800 m和3000 m的气溶胶粒子谱呈双峰分布,粒子谱谱型较为相似,4500 m和6900 m粒子谱呈单峰分布。气溶胶粒子尺度谱峰值随高度增加而减少,谱变窄。气溶胶粒子浓度水平变化幅度远小于垂直方向上的变化幅度,受天气条件及下垫面、云区等局地影响因子的影响较大。     

对流层低层晴空大气气溶胶粒子的观测分布

根据1987年冬季人工增雪飞机(机上装有FSSP-100前向散射粒子谱仪)在新疆不同地区获得的大气气溶胶粒子(尺度0.5-8μm)资料,分析研究了对流层低层晴空大气气溶胶粒子的浓度,尺度谱及垂直分布特征.     

珠江三角洲地区大气气溶胶特征的飞机观测分析

利用2010年11月6日在珠江三角洲的佛山、江门等地区上空进行的一次飞机探测数据,初步分析气溶胶粒子的垂直和水平分布特征。结果表明,气溶胶粒子在不同的高度有较大的差异,自下而上存在着累积层、递减层和增加层,在1 033 m以下的大气边界层存在气溶胶粒子的累积,气溶胶粒子最小浓度为1 151.15/cm3,高度1 033 m;最大浓度为7 307.38/cm3,高度627 m;平均浓度5 775.63/cm3,平均直径0.212 μm,最大直径0.219 μm,最小直径0.189 μm。在1 033 m以上,气溶胶粒子浓度随高度增加而递减,但在逆温层附近气溶胶粒子的浓度出现了随高度增加而增加的现象。在江门鹤山上空3 800 m的高度层平飞时段,气溶胶粒子数浓度平均为19.74/cm3,变化范围1.97～53.65/cm3。对不同高度粒子谱分析表明,其谱型为多峰型,且高度越高,谱宽越窄,大粒子基本集中在1 000 m高度以下。      

石家庄地区2005年秋季污染气溶胶飞机观测资料分析

利用河北省2005年10月份的3次气溶胶飞机观测资料和宏观天气资料,综合分析石家庄地区不同天气条件下气溶胶的垂直分布和尺度谱分布特征。分析结果表明:气溶胶浓度的分布与大气环境情况密切相关。气溶胶数浓度最大值的变化范围是103~104cm-3,平均数浓度为103cm-3,粒子平均直径为0.120~0.150μm;21日近地面有霾,相对湿度为58%,近地面气溶胶浓度较17和29日略低,但粒子平均直径(0.165μm)比其余两次要大,可见相对湿度较大,大气中水汽含量较多,有利于小粒子凝结水汽,使粒子直径增大;逆温层结下,粒子在逆温层下累积,无逆温时数浓度最大值出现在近地面附近。气溶胶粒子谱呈单峰分布。     

基于航测的珠三角气溶胶垂直分布及活化特性

2017年9月14—27日在珠江三角洲地区开展了6个架次飞机观测试验。利用飞行获取的气溶胶、云凝结核、云滴及常规气象探头观测资料,结合天气形势、气象条件及气团后向轨迹分析,研究了珠江三角洲地区深圳气溶胶数浓度及其谱的垂直分布特征,配合不同过饱和度条件下云凝结核浓度观测,分析了气溶胶活化特性。结果表明:在不同天气条件下,深圳低层气溶胶数浓度变化范围为500~9000 cm-3;边界层内气溶胶分布相对均匀,谱型随高度变化与气象条件相关。将6个架次气溶胶观测资料根据数浓度及谱型分为3种类型:类型Ⅰ为海洋型气溶胶,数浓度小,粒子尺度大,谱型呈双峰分布;类型Ⅲ为大陆型气溶胶,数浓度高,粒子尺度小,谱宽较宽且呈三峰分布;类型Ⅱ为海洋大陆影响型气溶胶,即受海洋和大陆共同影响,数浓度低于类型Ⅲ高于类型Ⅰ,谱型为双峰分布。拟合了包含海洋型及大陆型气溶胶的3个架次近地面云凝结核活化谱,计算了气溶胶在不同过饱和度条件下的活化效率。     

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.     

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.     

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.     

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.     

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正AIMS AND SCOPE Atmospheric and Oceanic Science Letters (AOSL) publishes short research letters on all disciplines of the atmosphere sciences and physical oceanography. Contributions from all over the world are welcome.SUBMISSIONAll submitted