福州市PM2.5、PM2.5/PM10分布特征及与气象条件关系的初步分析

利用福州市PM2.5、PM10和气象资料,分析PM2.5、PM2.5/PM10的分布特征及与气象条件的关系。结果表明:福州市细粒子污染程度较轻,春季PM2.5和PM2.5/PM10值均是四季中最高的,其次是冬季,夏季最低;影响PM2.5浓度出现高值的天气系统有:暖区辐合与高空槽前、大陆高压后部和暖区降水三种系统,其中暖区降水天气形势下的PM2.5平均浓度最高,超标率为25.5%;影响PM2.5浓度出现低值的天气系统有:冷高压脊、高压底部和高空槽后,副热带高压及边缘,台风(热带辐合带)及外围系统,在后两种天气系统影响下的PM2.5平均浓度最低,超标率为0;剔除因降水、雾等低能见度个例,PM2.5浓度与能见度的相关系数为-0.626,冬春季的相关系数是夏秋季的1.4倍;PM2.5浓度与单一气象要素(如温度、相对湿度、风速等)相关性不明显,但不同季节、不同气象要素变化的组合对PM2.5浓度有直接影响。      

武汉大气能见度与PM2.5浓度及相对湿度关系的非线性分析及能见度预报

武汉作为中部地区高湿度代表城市,大气污染严重,霾天气多发,但有关该地区大气能见度与PM2.5浓度及相对湿度(RH)的定量关系尚不明确。利用2014年9月—2015年3月武汉地区逐时能见度、相对湿度及颗粒物质量浓度观测数据,研究分析了武汉大气能见度与PM2.5浓度及相对湿度的关系,并进行能见度非线性预报初探,得到以下结论:武汉霾时数发生比例高,霾的发生和加重是能见度降低的主要原因;能见度降低伴随大量细粒子产生和累积,这是武汉大气能见度恶化的重要诱因。细颗粒物浓度与相对湿度共同影响和制约大气能见度变化,高湿高浓度时能见度显著下降,湿情景下(RH≥40%),能见度恶化主要是由湿度增高诱使细颗粒物粒径吸湿增长导致其散射效率增大造成的。当RH >90%时,能见度随湿度升高成线性递减,相对湿度每升高1%,武汉平均能见度降低0.568 km。而干情景下(RH2.5质量浓度升高。在城市大气细粒子污染背景下,能见度与相对湿度成非线性关系,这主要与PM2.5对能见度的影响及吸湿性颗粒物的散射效率变化有关。PM2.5浓度与能见度成幂函数非线性关系,80%≤RH2.5浓度对能见度的影响敏感阈值是随着湿度升高而减小的,干情景下能见度10 km对应的PM2.5浓度阈值为70 μg/m3,湿情景下该阈值为18—55 μg/m3。当PM2.5质量浓度低于约40 μg/m3时,继续降低PM2.5可显著提高武汉大气能见度。预报试验表明,基于神经网络方法建立大气能见度非线性预报模型是可行的,预报能见度相关系数为0.86,均方根误差为1.9 km,能见度≤10 km的TS评分为0.92。网络模型具有较高预报性能,对霾的判别有较高准确性,为衔接区域环境气象数值预报模式,建立大气能见度精细化动力统计模型提供参考依据。      

2005—2017年白云机场能见度变化特征及其与影响因子关系研究

利用广州白云机场2005-2017年的大气能见度、相对湿度、风速、气温等要素的逐时观测资料,结合花都花东站2012-2017年PM2.5浓度的逐时观测数据,分析了近年来白云机场能见度的变化特征,探究了能见度与气象要素、大气污染物之间的关系。结果表明:2005-2017年白云机场能见度呈逐年增大趋势,低能见度出现次数总体呈减少趋势。2-4月是机场低能见度时期,7月能见度最大。能见度日变化显著,最低能见度通常出现在清晨,午后明显好转。白云机场能见度与相对湿度、PM2.5浓度呈负相关关系,与风速、气温成正相关关系,其中PM2.5浓度对能见度的影响最明显。当相对湿度小于80%时,能见度下降得较为缓慢;而当相对湿度超过80%时,能见度急剧降低。相对湿度越大,出现低能见度所需的PM2.5浓度值就越小。地面风速在0~4 m·s-1时,相对湿度越大,能见度随风速的增长趋势越显著。     

重庆能见度特征分析及其与颗粒物浓度和气象影响因子的关系

利用重庆地区能见度及温、压、湿、风等气象资料和大气颗粒物浓度数据,对重庆能见度特征及其影响因子进行分析,采用神经网络方法建立能见度预报模型,分析比较了引入PM2.5浓度因子对预报模型的影响效果。发现：重庆地区能见度分布呈现西低东高以及长江沿线较低的分布特征;雾发生时的平均能见度低于降水时能见度也远低于剔除雨、雾后的能见度,表明低能见度受大气中水汽影响更大;雾在冬季比例明显增加,使得平均能见度在冬季明显降低,而6月和10月降水增多是导致这两个月平均能见度出现明显降低的重要原因;能见度日变化呈现单峰型,雾和降水高发时段与平均能见度低值区重叠,是造成夜间能见度低的一个重要原因;大气湿度、温度及颗粒物浓度都是影响能见度的重要因子,当相对湿度小于70%时能见度随PM2.5增加明显降低,当相对湿度大于70%时PM2.5对能见度的影响降低;在能见度的客观预报模型中引入PM2.5浓度因子的预报效果好于不引入该因子的效果,特别是秋冬季的预报效果改善明显。     

一次重污染过程及其边界层气象特征量分析

针对2013年12月14~25日出现的区域性重污染过程,采用Hysplit后推气团轨迹模式分析了污染形成源,利用污染中心邢台的探空、地面数据计算了大气稳定度、混合层高度、逆温等气象特征量,并对混合层高度、相对湿度、能见度与PM2.5浓度进行了相关分析。结果表明:此次重污染以局地排放为主要形成源,河北省中南部地区大气层结偏稳定,逆温层厚(平均230 m)、强度大(平均2.34℃/100 m)、混合层高度低(平均618 m)是影响污染程度的重要因素;PM2.5浓度与混合层高度呈现负相关(R=-0.80),与能见度呈指数相关(R=-0.77),与相对湿度呈弱的正相关(R=0.62)。     

一次持续性雾霾天气过程的阶段性特征及影响因子分析

应用常规与非常规气象观测资料及PM2.5浓度监测资料,对2013年1月20~24日山西区域一次持续性雾霾天气过程进行分析。研究发现：（1）本次雾霾天气过程具有明显的阶段性特征。2013年1月20日14时至23日11时,由于相对湿度的变化导致了3次轻雾转大雾过程;23日14~20时,由于PM2.5浓度的增大经历了1次轻雾转霾的天气过程。（2）地面弱的气压场和较小的风速以及PM2.5浓度的上升和相对湿度的增大为本次持续性雾霾天气过程的形成和发展提供了有利条件。（3）边界层逆温的存在是雾霾低能见度过程形成的必要条件,边界层有逆温层而不出现雾霾天气的条件是：相对湿度〈50%,PM2.5日均值浓度〈75μg·m-3;逆温层下相对湿度的大小是区别雾和霾天气的指标。（4）相对湿度和PM2.5是决定能见度大小的关键因子,其对能见度的影响体现出明显的阶段性特征,当相对湿度〈90%时,PM2.5浓度对能见度的作用强于相对湿度,是影响能见度变化的主要因子,但随着相对湿度的增大,其对能见度的影响相对增强,当能见度降至1 km以下时,相对湿度成为影响能见度变化的主要因子。     

德州能见度与PM2.5、PM10和相对湿度的关系

为研究德州大气能见度与水汽和气溶胶的关系,利用2013年逐小时能见度、相对湿度、PM2.5和PM10浓度资料,对三者与能见度的关系进行分析。结果表明：能见度与相对湿度的线性相关最好,与PM2.5浓度的相关性次之;随着相对湿度、PM2.5和PM10浓度的增加,能见度明显降低。大气能见度与相对湿度、PM2.5和PM10浓度非线性相关系数明显高于线性相关系数。利用PM2.5和PM10浓度和相对湿度数据计算得到了非线性大气能见度拟合公式,经验证,该公式能较好地模拟德州大气能见度。     

乌鲁木齐一次重污染过程及其边界层特征量分析

针对2020年1月5—17日乌鲁木齐出现的重污染天气，利用乌鲁木齐的探空站资料和地面常规气象数据计算了最大混合层高度、平均风速、逆温特性、边界层通风量、能见度、相对湿度等，对最大混合层高度、能见度、相对湿度与PM_2.5质量浓度进行了相关性分析，并利用Hysplit后向气团轨迹模式分析污染形成源。结果表明：此次重污染天气过程大气层结较为稳定，主要表现为逆温层厚(平均577 m)、逆温强度大(平均1.7℃/100 m)、最大混合层高度低(平均400 m)；边界层通风量对局地空气质量影响显著；PM_2.5质量浓度与相对湿度呈弱的正相关，与能见度呈指数相关；Hysplit后向气团轨迹模式分析得出此次污染过程以局地排放为主要形成源。     

浙江宁波地区能见度变化特征和成因

利用浙江宁波7个县(市)区的能见度、雾、霾、风速、相对湿度等气象资料和细颗粒物PM_(2.5)浓度数据,运用统计分析、后向轨迹模拟及聚类分析等方法研究了宁波地区能见度的时空分布特征及其影响因素。结果表明:1980—2013年,宁波地区能见度总体呈由西北到东南逐渐转好的空间分布特征,且中南部呈逐年下降态势,而北部则呈上升趋势,这与风速和相对湿度减少有关,但不同区域其主要影响因子存在差异。能见度和PM_(2.5)浓度均有明显的季节和日变化特征,且二者呈明显反位相,相关系数为-0.532,其中冬季PM_(2.5)浓度最高,能见度最低,夏季反之;13:00—17:00为PM_(2.5)浓度谷值、能见度峰值,01:00—08:00为PM_(2.5)浓度峰值、能见度谷值。气团输送轨迹分析表明,宁波地区共有来自5个方位的6类轨迹气团,其中西北方向的轨迹4对该区PM_(2.5)浓度影响最大,偏东方向的轨迹6对PM_(2.5)浓度影响最小,能见度最好,而对能见度影响最大的是来自西北方向的轨迹2和偏西方向的轨迹3。     

北京大气能见度的主要影响因子

利用北京市道面自动气象站、国家级自动气象站等多种观测数据分析北京地区2007—2015年能见度及其主要影响因子, 并挑选两次典型低能见度事件过程进行详细分析。从空间分布看, 北京西北地区能见度明显高于中心城区和东南大部地区。从时间分布看, 北京地区平均能见度最大值出现在5月, 最小值出现在7月; 日间的最低值多出现在06:00(北京时, 下同)左右, 冬季略向后推迟; 最高值多出现在16:00前后, 冬季略有提前。整体而言, 2007—2015年北京地区发生低能见度事件的概率为62.14%, 且发生低能见度的事件集中于1~5 km, 霾事件中干霾、湿霾的发生频率分别为86.13%和13.87%。能见度的主要影响因子为相对湿度、风速和PM_2.5浓度。其中, 能见度与风速呈正相关, 与相对湿度和PM_2.5浓度呈反相关。需要指出的是, 当相对湿度增加至80%, 能见度受PM_2.5浓度的影响程度在下降, 而主要受相对湿度的影响。基于所选个例, 当北京地区出现湿霾事件时, 能见度的恶化程度远高于干霾事件, 且PM_2.5浓度需比干霾事件时下降得更低才能有效改善能见度。     

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.     

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.     

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.     

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。     

Analysis of Atmospheric Boundary Layer Height Characteristics over the Arctic Ocean Using the Aircraft and GPS Soundings

正ERRATUM to: Atmospheric and Oceanic Science Letters, 4(2011), 124-130 On page 126 of the printed edition (Issue 2, Volume 4), Fig. 2 was a wrong figure because the contact author made mistake giving the wrong one. The corrected edition has been updated on our website. The editorial office is sincerely sorry for any     

Index to Vol.31

正AN Junling;see LI Ying et al.;(5),1221—1232AN Junling;see QU Yu et al.;(4),787-800AN Junling;see WANG Feng et al.;(6),1331-1342Ania POLOMSKA-HARLICK;see Jieshun ZHU et al.;(4),743-754Baek-Min KIM;see Seong-Joong KIM et al.;(4),863-878BAI Tao;see LI Gang et al.;(1),66-84BAO Qing;see YANG Jing et al.;(5),1147—1156BEI Naifang;     

Information for Contributors

正Journal of Meteorological Research is an international academic journal in atmospheric sciences edited and published by Acta Meteorologica Sinica Press,sponsored by the Chinese Meteorological Society.It has been acting as a bridge of academic exchange between Chinese and foreign meteorologists and aiming at introduction of the current advancements in atmospheric sciences in China.The journal columns include Articles.Note and Correspondence,and research letters.Contributions from all over the world are welcome.