京津塘高速公路秋冬雾气象要素与环流特征

利用京津塘高速公路2007年10—12月沿路自动气象站风、温、湿及能见度连续观测资料,结合气象台站地面观测及NCEP再分析资料,分析了雾过程中的大尺度环流背景及气象要素分布特征。分析表明局地路段类型雾天气主要出现在上层为下沉气流同时地面为弱气压场的环流条件下;全路段类型雾过程主要出现在对流层低层弱西风槽前的暖平流区、地面冷锋前弱气压场中。2007年10—12月各月雾发生时近地面温度范围分别为9～13℃,4～7℃和-6～1℃;近地面相对湿度一般大于90%。相对湿度为85%～90%时,也有500～1000 m低能见度天气发生。雾发生时近地面风向不定,风速一般小于2 m·s~(-1);当风速大于5 m·s~(-1)时,雾存在的概率极低。文中还给出了各路段雾生消时间、持续时段及雾天气出现次序的一般特征。     

2013年初春一次平流雾过程对江苏交通的影响分析

2013年3月18—19日江苏省一次平流雾天气具有突发性强、影响范围广、强度大、持续时间长等特点。利用江苏省高速公路自动气象监测站(AWM)数据、FNL数据和常规气象资料,对其成因进行分析,并评价其对交通及预报服务质量的影响。结果表明:高中低层的暖平流和入海变性冷高压为平流雾发生发展提供了有利的环流形势;持续变化较小的气压梯度、相对湿度的陡增、地面弱冷空气产生的温差和在偏东风风速达6 m·s-1时,平流雾即可快速生成;较低的混合层高度和逆温存在是低能见度形成的必要条件,能见度越低时混合层高度也就越低;近地层的冷平流和中高层的暖平流形成平流逆温,同时配合近地面的弱上升运动,有利于雾的形成和维持。根据江苏省交通气象台关于雾的预报服务发布流程规范和预报质量评价,本次雾过程中对高速公路、高架桥和长江航道的预报服务准确、及时,服务质量良好,有效地避免了交通事故的发生。     

贵州区域性辐射大雾特征与形成条件

通过对1971-2008年贵州省08:00能见度资料及地面天气图的普查,选取382次区域性辐射大雾天气过程,分析了贵州区域性辐射大雾的时空特征.并利用1999-2008年93次辐射雾08:00地面和高空天气图,进行天气环流条件分析;并进一步利用地面站及高空资料,研究了形成辐射雾的气象条件.研究表明,贵州区域性辐射大雾主要集中在仲秋到隆冬时段,呈现“东多西少”的分布特征,均压场是区域性辐射大雾的地面环流条件,区域性辐射大雾的四种高空环流条件为西北气流、西南气流、副热带高压、平直西风气流.地面风速小、湿度大、夜间辐射降温显著及近地层有逆温、整层“上干下湿”是形成区域性辐射雾的气象条件.     

辽宁沿海高速公路浓雾气候特征及气象影响因子

利用2005—2018年辽宁沿海高速公路沿线气象站点观测资料和NCEP再分析资料,对辽宁沿海高速公路浓雾气候特征及其与各相关气象要素的关系进行分析,并探讨了利于浓雾发生的环流特征和影响因子。结果表明：辽宁沿海高速公路年均浓雾日数由西至东呈现高—低—高的分布特点,同时,辽东沿海高速公路沿线各站年均浓雾日数差异较小,且存在明显的自东向西的下降趋势;辽西沿线高速公路各站差异最大,受到局地的影响最强。沿海高速公路年均浓雾日数具有明显的月变化与季节变化特征,全年有两个浓雾出现的集中时段,分别为2—3月和10—11月;秋季浓雾日数占全年的比率最高。秋季沿海高速公路浓雾以0—200 m的强浓雾为主;温度为10—15℃,相对湿度大于98%,风速为0—3 m·s^-1,风向为偏东北风时,浓雾出现的概率最大。辽宁秋季沿海地区受副热带高压影响较小,受东亚大槽等中高纬度纬向环流和极涡的影响较大,纬向环流和极涡越强（弱）,辽宁沿海地区浓雾日数越多（少）;辽宁沿海地区浓雾的水汽一部分来源于辽宁东部山区,一部分来源于渤海、黄海北部。辽宁沿海地区秋季浓雾并非以海雾为主,而以辐射雾、锋面雾居多,同时辽东沿海地区有来自辽东山区的平流雾。     

郑州机场能见度变化特征及雾的成因分析

能见度是影响飞机能否正常起降的重要气象条件。通过对能见度的变化特征研究,可以得出能见度在不同季节、不同的天气条件下出现的时间段和持续时间的变化特征。低能见度现象主要是由大雾引起的,分析雾的成因对了解和解释低能见度现象及其变化规律具有重大意义。根据郑州机场实际情况,采用13小时人工观测的数据格式,利用郑州机场1998-2002年的观测资料对郑州机场的能见度进行了统计分析。统计结果表明,郑州机场低能见度现象97%是由雾引起的,其中辐射雾和平流雾引起的低能见度现象占76%,是造成低能见度现象的主要的雾的类型。在影响郑州机场能见度的四种类型的雾中,辐射雾和平流雾发生的频率高,平流雾影响持续时间长,融雪雾对能见度的影响最大。逆温层和低层丰富的水汽是辐射雾和平流雾形成的条件,在今后对雾的预测中,应首先考虑这两个因素。     

四川高速公路封道强浓雾特征及其成因分析

利用2006—2013年四川高速公路强浓雾封道资料及气象资料,分析了造成四川高速公路封道的强浓雾特征,并通过天气环流条件和气象要素特征分析,研究了形成封道强浓雾的气象成因。结果表明:四川高速公路强浓雾封道主要出现在11月至次年1月,主要在清晨05:00—08:00开始,08:00—11:00结束,持续时间一般为0~9h。均压场是封道强浓雾的地面环流条件,低层为高压环流控制,高空环流条件为西北气流型和平直西风气流型。夜间辐射降温明显,地面到近地层风速弱、湿度大及存在逆温层,有利于封道强浓雾的出现。     

一次平流辐射雾的边界层特征及雾水离子组分研究

为了研究北京城市浓雾生成机理以及雾水的污染情况,2006年12月11-12日,在北京南郊北京市观象台(39°56'N、116°17'E)对水平能见度在100m以内的浓雾进行了观测,并分析了这次浓雾形成的天气条件,对所采集的雾水进行了离子组分分析.结果显示:这是一次平流辐射雾,雾层厚约150m,能见度小于100m;在高空槽前、稳定边界层中,近地面正相对涡度区内有气流辐合和暖湿平流,日落之后地面降温迅速,有利于雾的生成;地面偏南风配合近地层暖平流,有利于增加雾的浓度;浓雾的形成发展时段内伴随着大气五级重污染事件.与1999年北京的雾水采样比较:pH值上升,电导率下降,阴离子浓度普遍下降,阳离子浓度有所上升.研究表明,近年来北京城市所采取的治理措施,减轻了浓雾及其雾水中的污染.     

WRF模式对沪宁高速公路浓雾的模拟与检验研究

统计表明,发生在沪宁高速公路的大雾以辐射雾最多,而以平流雾形成浓雾的可能性最大。利用WRF模式3.0版本优选微物理过程和陆面过程方案,对2006年6月—2009年5月发生在沪宁高速公路能见度低于500 m的大雾,按照成因分为辐射雾和平流雾进行数值模拟,并利用实测资料进行检验,验证WRF模式对大雾的模拟预报能力。结果表明,模式对平流浓雾天气的模拟效果较好,模拟预报准确率较高,但未能模拟出辐射浓雾天气。      

2018年8月22日宁夏北部局地浓雾天气形成机制分析

利用宁夏972个地面自动站的10 m风场、2 m温度及露点温度,银川、大武口、平罗、贺兰4个常规地面观测站的能见度、温度及相对湿度逐时观测资料和欧洲中期天气预报中心（ECMWF）ERA-Interim逐6 h再分析资料（0.125°×0.125°）,对2018年8月22日宁夏北部局地突发浓雾天气过程的环流形势、逆温结构及其热力、动力条件和形成维持机制进行分析。结果表明：8月22日宁夏北部局地浓雾发生在地面冷高压、高空暖脊及近地面微风的静稳天气条件下;较为深厚的暖平流和近地面冷空气侵入所形成的稳定大气层结,是大雾形成的必要条件;弱上升运动使混合层扩展至840 hPa左右,是该地区雾的发展和维持的重要原因。在本次过程中,深厚的弱水汽辐合较水汽自身的饱和与否更为重要,是大武口站浓雾形成的关键性因素。浓雾呈现平流-辐射雾特征,地面热通量在过程前期促进浓雾的发生,后期对浓雾起到抑制作用。     

雾的成因及其危害

雾是自然界的一种常见天气现象,它是由地表蒸发出来的水分子受冷空气影响凝聚而成的小水滴或冰晶汇集而成,其水平能见度在1000m以下。当水平能见度在50～200m之间时,称为浓雾。根据成因的不同,雾一般可分为辐射雾、平流雾、蒸汽雾、上坡雾、锋面雾等。陆地上最常见的是辐射雾。这种雾是空气因辐射冷却达到过饱和而形成的,主要发生在晴朗、微风、近地面、水汽比较充沛的夜间或早晨。这时,天空无云阻挡,地面热量迅速向外辐射出去,近地面层的空气温度迅速下降。如果空气中水汽较多,就会很快达到过饱和而凝结成雾。平流雾则是当温暖潮湿的空气流…     

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