冷空气影响下的黄东海海雾特征分析

根据历史观测资料研究分析了我国黄海和东海沿海在冷空气影响下发生海雾的气候规律和海雾形成的海洋、气象条件,发现冷空气条件下的成雾主要发生在冬春季节,其中半数以上为浓雾过程,冷空气条件下成雾次数约占总雾次的15%,成雾时以弱冷空气过程为主,风向偏北,风速一般小于8 m/s,成雾的相对湿度条件有昼夜之分,夜间发生的雾大多数出现在空气处于或接近饱和状态之下,而白天发生雾时相对湿度条件限制要低一些。成雾时以气海温差在2.0 ℃以内时所占的比例最多,但当气温低于海温2.0 ℃以上时的海雾仍占15%的比例,它高于一般海雾发生时对应的海气温差值所占的百分比。东海海域的冷空气雾其近海面边界层大气普遍有逆温或近于等温情况,而黄海北部海域有逆温或等温的情况比较少。以冷空气影响下成雾最多的小洋山站为例,海雾维持时间大多小于2小时,约有19%的海雾维持时间大于4小时。当冷空气影响下海上出现雾时,临近陆地上的能见度一般都比较好,这与相邻沿海陆地区域一般并不形成有利的成雾条件有关。     

宁波海雾特征和预报着眼点

本文用1971—2011年石浦站资料及NCEP再分析资料,统计分析宁波各种强度海雾特征和合成分析其出现的天气背景。统计表明：海雾多发生于4—6月,主要出现在23时至次日11时,其中23时至次日02时最多,11时后消散。风力在2~3级的西南或东北风有利于海雾的发生。相对湿度在90%~95%,本站气压在990~1002 hPa时,海雾发生概率随着湿度的增加及气压的减小而增加,但对于能见度≤50 m的强浓雾来说,相对湿度和本站气压范围分别为92%~95%和990~999 hPa,且强浓雾随湿度及气压的增加而增加。宁波海雾通常出现在江淮气旋、冷空气影响前和梅雨锋中低涡东移前。合成分析表明：锋面雾一般形成于系统过境前2～3 d,局地上空西南暖湿气流影响时;或静止锋南侧,局地上空风速较小,且前期有充足水汽汇聚并导致湿层增厚;平流雾形成时上空位于西南涡前部,长时间西南暖湿气流输送,形成一定厚度和范围的湿度层,在该天气背景下,下垫面的气 海温差维持在0~1.5℃左右,露点 海表温差在-0.5~0℃上下。浓雾（强浓雾）的形成需在稳定的大气层结下,长时间深厚的暖湿气流里,同时来自北方的冷海流不断注入宁波沿海。此外,雾的强度与暖平流及海表冷平流的强度有较大关系。这些对宁波海雾及其强度的预报有较好指导作用。     

近56a洛阳地区雾和霾气候特征及其气象要素分析

利用1961—2016年洛阳9个县(市)地面气象观测站的雾、霾日数及相关气象要素资料,采用统计学方法分析了洛阳地区雾和霾日数的时空分布特征及影响其产生的气象要素特征。结果表明:近56a来洛阳市平均年雾日数在20世纪80和90年代较多,21世纪初开始逐渐减少,但在2015—2016年明显增加;平均年霾日数以2013—2016年最多;雾和霾日数在冬季最多,夏季最少。2000—2016年洛阳市雾日数自北向南逐渐减少,霾日数则在西部多、东部少,全区霾日数较1981—2010年明显增加。对雾、霾日气象要素的分析表明,相对湿度越大雾出现的频率越高、能见度越低,浓雾发生时相对湿度一般都在90%以上;中度和重度霾发生时相对湿度主要集中在50%~79%。雾发生时气温主要在-4.0~4.0℃之间,中度和重度霾发生时,气温分别集中在0~15.0℃和0~8.0℃,轻微和轻度霾发生时气温分布范围较大,以0~10.0℃较为集中。雾和霾出现时风速大部分在3.0m·s^-1及以下,并且主要是来自东北、东东北风向区域。     

北京城市浓雾特征及其与交通预报服务的关系

使用2007—2010 年北京地区18 个道面自动气象站能见度在1000 m 以下时的气象资料及同期北京管界内高速公路交通资料,对北京城市浓雾特征及其与交通预报服务的关系进行了探讨。结果表明: 1) 北京管界内高速公路封闭90%以上因浓雾引起。2) 浓雾具有明显的日变化和年变化,高发、低发时段分别在05—09 时和12—18 时,浓雾主要集中在9—12 月,6、7 月最少。3) 空间分布上,浓雾频次东南高,城区低,80%以上的浓雾出现在大兴和通州两区。4) 浓雾变化具有突发性和“象鼻形”先期振荡特征。5) 浓雾期间能见度变化与气象要素关系密切,近地面偏南风和偏东风最有利浓雾生成发展,西北风最有利浓雾消散;风速减小,气温下降,湿度增大,能见度降低,有利浓雾生成和发展;风速增大,气温升高,湿度减小,能见度上升,有利浓雾减弱消散;湿度减小滞后于能见度上升;浓雾维持阶段,各要素变化很小。     

榆林市雾的变化特征及地面气象条件分析

利用榆林市12个国家气象观测站2016—2020年逐小时地面观测资料,统计分析了榆林地区雾的变化特征及地面气象条件。结果表明：(1)榆林地区各等级雾中强浓雾出现时数最多,特强浓雾鲜少出现;各等级雾都呈现显著的季节变化和日变化特征,多出现于秋季,10月最多,日变化呈单峰型,07:00前后达到峰值。(2)雾整体呈现“东多西少”的空间分布,大雾和浓雾主要出现在东南部的吴堡、绥德、清涧等地,西部的定边、靖边出现最少,强浓雾和特强浓雾主要出现在东南部的绥德、米脂等地,北部的府谷次之。(3)大雾和浓雾天气过程持续时间短,大多为1 h,强浓雾一旦生成,很难在短时间内消散;雾主要在夜间到凌晨生成,在日出后消散,强浓雾的生成和消散时段均比大雾和浓雾偏早且集中。(4)雾强度越强,对应地面相对湿度越高,温度露点差越低,气温和露点温度的降幅越大,风速越小;雾在地面各风向均可出现,但较盛行东南风和西北风。(5)强浓雾由于发生时数多、持续时间长,是榆林市影响最严重的大雾天气,95%强浓雾出现条件为相对湿度大于95%和温度露点差小于1℃,风速基本小于2 m/s,这对强浓雾的预报具有很好的指示意义。     

山东区域性辐射雾时空分布及地面气象要素特征分析

选取2016—2019年共61次山东区域性辐射雾天气过程,利用山东122个国家级气象观测站逐小时观测资料,对其时空分布及地面气象要素特征进行分析。结果表明：1）山东辐射雾具有显著的季节和日变化特征,主要发生在10月—次年2月,持续性大雾主要发生在1月和12月,一天中20时以后大雾频次增加,02—08时为雾最集中的时段,07时前后达到峰值,下午一般无强浓雾出现。2）辐射雾空间分布呈现明显“西多东少”格局,主要出现在鲁西北和鲁西南地区,山区和半岛沿海地区较少,强浓雾和特强浓雾主要分布在德州、聊城及菏泽等地。3）区域性辐射雾发生时,地面无突出风向,北风略占优势,风速多在3 m·s-1以下;各等级雾形成前气温和露点温度均存在不同程度的下降,20时气温与次日最低气温温差在2～6 ℃、14时地面露点与最低能见度时刻地面露点的温差在1～5 ℃时最有利于辐射雾的发生;随着辐射雾强度的增强,对温度露点差和地面相对湿度的要求越来越高,出现大雾时的温度露点差主要在2 ℃以下,相对湿度大于90%;出现浓雾、强浓雾和特强浓雾时的温度露点差小于1 ℃,相对湿度大于95%。     

大连海雾特征及形成机理初步分析

利用2000～2010年逐3 h一次的常规报文资料和2.5°×2.5°的NCEP月平均场再分析资料,统计分析大连海雾发生时各种大气环境要素特征,确定有利于海雾生成的环境要素条件,并以此讨论海雾的成因和性质。同时,统计分析了大连海雾的年际变化与季节特征,对造成大连海雾异常偏多与偏少时的环流形势与水汽条件进行对比,分析有利于海雾生消的环流形势和海雾的水汽来源,以及海雾的性质成因。结果表明,大连海雾多发于春夏2季,其中尤以5～7月为海雾多发期,而在秋冬季很少发生。海雾主要出现于下半夜至上午前(从02点到11点),其中清晨05～08时最多,其消散一般在上午日出之后。风速在2～8 m/s之间的偏东风或偏南风最有利于大连海雾的发生。当预报海雾发生时,T-Td>0.6℃时,判断能见度>300 m;T-Td>1.1℃时,能见度一般>500 m;T-Td>2.1℃时,能见度>800 m。海雾在1 008 hPa时发生频次达到一个峰值,当气压<995 hPa和>1 030 hPa时,基本上没有海雾的生成。大连海雾多为平流雾,海雾的年际变化是大气环流变化的结果,海雾发生频数与副高西侧的偏南季风气流相关,当副高增强时,西南季风气流可以直接将热带洋面的水汽输送至大连地区,这样的平流水汽遇到冷的下垫面时,在大连海域形成海雾。     

下垫面热力作用对黄海春季海雾的影响——观测与数值试验

利用海上浮标站、高分辨率数字式探空仪等多种观测手段和中尺度模式WRF,对2008年5月2—3日黄海发生的一次海雾过程进行了观测分析和数值模拟。观测表明,出现海雾时,气温明显下降,气海温差(海表面以上2 m气温减海表面以下1m水温)减小,不足0.5℃,浓雾时,甚至出现海温(SST)高于气温的现象。较强的湍流活动出现在大气边界层低层150 m以下。反映了低层大气稳定性减弱,可能有利于海雾的维持。海雾消散阶段,海气温差明显加大,湍流强度减弱,湍流发展高度升高。海雾过程中,可能存在动量下传的局地海-气相互作用机制,SST的升高可使雾中能见度好转。数值模拟的结果与观测基本一致,雾区内的气海温差明显小于雾区外,敏感性试验进一步表明:100 m以下气层稳定性和湍流发展条件对SST的变化敏感。SST的变化对稳定度的影响和对雾区范围的影响与近海面的水汽含量有关:在湿度较小(q0.5 g/kg)的薄海雾区,SST增加1℃,稳定度明显减弱(θ_v/z≤0.01 K/m),海雾面积缩小;SST下降1℃,稳定度增加(θ_v/z≥0.07 K/m),薄海雾面积增大。在湿度较大(q0.6 g/kg)的浓海雾区,SST的变化对静力稳定度的影响不大,海雾仍然维持。因此,当海气温差减小,甚至出现SST高于气温时,如果仍然有海雾,则一般是水汽含量比较大的浓海雾。该结果有助于对海雾形成机制的认识。     

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。     

引入积温效应预测夏季西安市电力气象负荷

利用2010—2012年6—8月西安市逐日电力负荷资料及对应时段地面观测站数据,分析了高温天气过程中日最大电力负荷的变化特征。结果发现,3年间西安地区共发生晴热天气过程5次,闷热天气过程4次,其中晴热天气过程发生在6月,闷热天气过程发生在7、8月,且闷热天气过程的电力负荷增长更加明显;利用日最高气温变化跟踪气象负荷的变化发现,日最高气温33℃为西安市气象负荷初始气温敏感点,35℃为强气温敏感点,38℃为极强气温敏感点;引入积温累积效应,建立了多元回归的电力气象负荷预测模型,经2013年夏季模型应用检验表明,日最大电力负荷预测平均误差为6.0%,能较好的模拟电力负荷的实际变化,对西安市夏季电力气象服务工作有指导意义。     

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.