2013年初江苏连续性雾-霾天气的特征分析

利用FNL资料、污染物颗粒浓度资料以及常规气象资料对2013年1月12—16日江苏地区的连续性雾 霾天气过程的环流形势、地面气象要素特征、大气边界层结构及大气污染状况等进行了分析。结果表明：高空形势变化平稳、中低层的暖平流配合稳定少动的地面气压场为雾 霾天气的发生提供了有利的环流形势;持续变化较小的气压梯度和较低的风速以及相对湿度的增大和PM2.5、PM10的浓度的变化为雾 霾形成和发展提供了条件;雾 霾期间低层都存在不同程度的逆温现象,混合层高度与AQI呈反相关关系,当混合层高度越低,AQI就越高,污染就越严重,能见度就越差;相对湿度的升高和PM2.5在污染物颗粒中的富集,是导致能见度下降和持续污染的首要原因,而强冷空气带来的大风降温是污染物颗粒被快速清除的重要动力机制;影响南京的污染物来源为：黄海、安徽地区、北方污染物的输送和本地的局地污染。     

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。     

2013年1—2月华北雾、霾天气边界层特征对比分析

利用地面观测资料、中国气象局PM2.5质量浓度数据、L波段探空秒数据等,对华北地区三个大城市(北京、石家庄和太原)的雾、霾及晴天天气的地面风场特征及PM2.5浓度分布情况进行了统计分析。同时分析了典型雾、霾天气过程中的边界层气象要素垂直结构及逆温层特征,并与晴天过程做了对比。通过对不同强度雾、霾天气过程的边界层动力、热力学结构差异的讨论,发现逆温强度与雾、霾天气的能见度有负相关关系,并对雾、霾天气的发生有一定的预报指示意义。     

2020年江苏泰州一次持续性雾-霾过程特征和成因分析

2020年1月12—15日江苏泰州发生了一次较强的雾〖CD*2〗霾过程，利用常规气象观测资料、NCEP再分析资料（1°×1°）及空气质量资料等，对此次过程的演变特征、成因、气团后向轨迹特征进行了分析，结果表明：此次过程具有日变化特征，霾期间对应的PM2.5和PM10浓度、空气质量指数相较于雾略高，这与大雾造成的湿沉降有关。此次东路冷空气对泰州影响较弱，前期易造成污染物在本地聚集。夜间至清晨相对湿度90%以上，风小，弱的垂直交换为雾的形成提供了较好的热、动力条件。白天相对湿度减小至80%，风速增至2 m〖DK〗·s-1，此时大气污染物浓度较高，雾转换为霾。13日900 hPa以上暖平流增强，边界层内逆温和90%以上相对湿度的存在，使得雾和霾均加强至最强。此外，分析气团的后向轨迹特征发现，霾天气期间500 m以下气团稳定少动。14日500 m以上清洁气团向低空补充，利于污染物的扩散，霾减轻。15日傍晚，风力增强并伴有降水出现，雾〖CD*2〗霾过程结束。     

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。      

苏州市能见度与影响因子关系研究

利用2009年6月—2010年5月苏州市气象局霾监测点颗粒物浓度、能见度、相对湿度、风速、风向、气温等观测资料,分析了苏州能见度变化特征,建立了能见度和影响因子的统计模型,研究了能见度和气象因子及颗粒物浓度的关系。结果表明：苏州市能见度有明显的季节变化,春季能见度最好,秋季能见度最低;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;PM10、PM2.5、黑碳浓度值和相对湿度与能见度都呈反相关关系,但黑碳对能见度的影响不如PM10和PM2.5对能见度的影响明显;风速与能见度呈正相关关系,在东南、南东南风向时能见度值最高。     

霾观测判识标准定量化对雾霾观测记录的影响

为研究霾观测判识标准定量化对雾霾观测记录的影响,选取2006—2012年湖北省18个基准站、基本站和一般站三类国家级地面气象观测站的资料,对已记录和按照相对湿度判识标准统计的雾、轻雾和霾天数进行分析,结果表明:判识标准定量化将使霾的观测记录明显增多,轻雾和雾观测记录略有减少,霾和轻雾观测记录将更趋合理,就湖北省而言,相对湿度在80%~95%之间,应以轻雾和雾为主;通过定时观测时次的能见度、相对湿度,以及日天气现象记录,可以得到历年按照相对湿度判识标准统计的霾和轻雾天数,实现对历史资料序列的订正,形成判识标准改变前后均一化的月年资料序列。判识标准定量化后,不能机械的硬套判识指标,观测员仍需熟练掌握轻雾和霾以及其他视程障碍现象的成因和特征,避免相对湿度在霾观测判识标准上下波动、轻雾处于消散过程阶段,轻雾与霾的频繁转记。     

天津雾和霾自动观测与人工观测的对比评估

为适应地面气象观测业务调整方向,提高新型自动气象站观测资料的质量及可用性,研究中对天津地区10个地面气象站1951—2014年历年2月人工观测及2014年2月自动观测和人工观测的轻雾、雾、霾现象进行对比评估。结果表明:天津地区历年2月轻雾的平均日数为10 d,雾和霾均为2 d,轻雾和霾同期出现的日数占有天气现象的7.4%,而雾和霾同期出现日数仅占0.7%;平行观测期的对比分析得到人工观测轻雾日数比自动观测多11 d,雾日数和霾日数均比自动观测少6 d,其中,轻雾和雾的判别差异集中出现在每日08:00(北京时,下同),霾则基本出现在每日08:00,14:00,17:00,20:00;通过对比自动观测和人工观测的能见度数据发现,二者相对偏差达25.1%,能见度小于15.0 km时,自动观测的能见度有60%~76%数值偏小,特别是08:00和20:00, 因此,在相对湿度满足条件的情况下,能见度的判别误差是导致自动观测与人工观测轻雾、雾、霾现象判别差异的重要原因。     

2018年1月青岛市一次重度污染雾—霾天气成因分析

利用中国国家地面站逐小时气象观测资料、中国环境监测总站空气质量逐时监测数据、ECMWF 0.125°（纬度）×0.125°（经度）再分析资料及青岛市八关山自动站常规要素逐小时数据,对2018年1月15~22日青岛市一次重度污染雾—霾天气过程的特征及其影响因子进行分析。结果表明:PM10为首要污染物,污染过程中青岛市48 h 输入污染源前期主要为北方干冷气团与江淮湿空气在山东半岛北部汇聚堆积,后期则主要包括山东省内局地大气污染物排放。雾—霾期间,500 hPa中高纬地区受乌拉尔山阻塞高压和中西伯利亚冷低压控制,宽广的东亚横槽稳定维持,青岛上空以平直西风气流为主,地面等压线稀疏,风速小;随着横槽转竖,纬向型环流转为经向型,冷空气大举南下,风速急增,降雪发生,雾—霾迅速消散。在静稳的大气环流背景下,当近地逆温层内弱风或持续吹陆风,对流层低层上升和下沉运动较弱,水汽条件较好时,有利于雾—霾维持。综合分析雾—霾各阶段PM2.5浓度和相对湿度与能见度间的关系发现,霾阶段两因子影响力相当;雾阶段能见度主要受相对湿度的影响;静稳条件下PM2.5浓度累积增加是影响雾、霾混合阶段能见度的主要因子。     

2014年10月京津冀地区一次PM2.5污染过程的数值模拟

近年来我国东部尤其是华北地区的PM2.5污染逐年加重,引起广泛关注。本文利用WRF Chem模拟了2014年10月京津冀地区一次PM2.5重度污染过程,研究造成此次过程的天气形势、污染物的时空分布特征以及一次、二次PM2.5对总浓度的贡献率,并对污染最严重当日的PM2.5垂直分布进行详细分析。结果表明：造成本次污染过程的是弱高压控制下的静稳天气系统,地面主导风向为南风,垂直方向上有逆温层,抑制了污染物垂直方向上的扩散。发生污染时,PM2.5的高浓度主要分布在北京南部、天津北部与河北接壤的区域,二次PM2.5的贡献率大于一次PM2.5,在清洁大气中则一次PM2.5的贡献更大。垂直方向上,PM2.5中的一次颗粒物只在近地面有高浓度中心,1.2~1.6 km的上空高值区以二次生成的颗粒物为主,是由前体物上升到高空后再通过氧化反应生成的,当这部分颗粒物随着边界层落回近地面时会加重污染。随着时间的变化,污染物的分布高度和边界层高度呈明显的正相关。     

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.     

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.     

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