一次长江三角洲飑线的综合分析

该文利用多种气象资料（包括常规观测、卫星云图、自动气象站、多普勒气象雷达以及风廓线仪资料），综合分析了2002年8月24日发生在长江三角洲的一次飑线过程。发现该飑线产生于一个中尺度对流系统（MCS）当中，地面冷锋、副高边缘的高能水汽输送带与高空小槽配合，使该MCS得以发展和加强，副高南撤和下游有利的动力和层结条件使得MCS中的雷暴群发展为飑线，并迅速东移南压，产生了大范围雷雨大风天气。多普勒雷达、自动站及风廓线仪的资料还很好地揭示了该飑线的发生、发展、爆发过程及其回波和风场的空间结构特点。     

山东省中西部飑线过程个例分析

利用常规观测资料、自动站观测资料和NCEP1°×1°再分析资料、雷达探测等资料对2007年7月11日山东中西部发生的一次飑线过程进行了综合诊断分析。结果表明：飑线发生在高空低涡后部横槽前上千冷下暖湿的不稳定层结中,高空急流和地面切变线对不稳定能量的释放有触发作用;飑线是在低空增温增湿及对流层中层干侵入的作用下形成的,并在强风速垂直切变条件下发展成熟,边界层弱的水汽输送和能量积聚是这次过程的能量来源。     

浙江西南部一次大暴雨过程分析

利用常规气象观测资料、浙江省区域自动站观测资料、NCEP1°×1°逐6 h再分析资料,对2019年6月6日发生在浙江省西南部地区的一次大暴雨过程进行了诊断分析。结果表明:该过程是以北方高空冷槽侵袭南支槽槽前和副热带高压西北侧的暖湿空气为背景,在低空急流和低空切变线的配合下产生的,强降水落区主要位于地面辐合线附近,此处有利于暖湿气流被强迫抬升形成对流系统;强降水发生前,浙江西南部地区上空形成了不稳定的大气层结,强降水发生时,水汽供应充足,上升运动较明显;欧洲中心高分辨率数值预报对该过程的降水量预报出现了较明显偏差,主要原因在于数值预报场上南支槽东移速度和低层切变线南压速度均慢于实况,且700 hPa上的急流强度小于实况。     

黄淮流域一次飑线天气的数值模拟与分析

利用1°×1°NCEP再分析资料和探空资料,对2009年6月3日发生在黄淮流域的强飑线天气过程进行诊断分析,并采用WRF模式进行天气过程模拟和进一步研究。结果表明：本次飑线天气是东北冷涡后部横槽引导冷空气南下与南方暖湿气流相遇引发的。地面干线附近是雷暴和飑线的高发区。这次飑线天气发生在高空急流减弱之际、低空急流建立之前。高低空急流的U、V风分量变化对飑线有一定的指示意义。不同阶段的飑线降水和大风出现位置不同。     

利用微波成像仪资料反演台风Aere(2004)降水水平结构

2005年6月华南出现大范围持续性暴雨过程,造成巨大损失。利用常规气象资料、卫星云图TBB资料及T213分析场资料,对此次持续性暴雨过程的成因进行了分析,结果发现:这次暴雨过程充足稳定的水汽主要源自印度洋,这与“94.6”等以往华南暴雨水汽主要来自于南海不同。高低空急流与切变线是这次强降雨过程的触发系统,低空急流输送了丰沛的暖湿空气,维持了低空对流不稳定形势。冷暖气流在切变线南侧、低空急流左侧交汇,产生强烈辐合上升运动,触发了强降水。对流云系上MCS的不断生消是造成强降雨持续的直接原因。本次过程存在一次高空急流的变化,高空由西北急流转为西南急流,切变线的变化趋势与这一变化过程相呼应;这一特征也是暴雨过程得以维持的重要原因。     

福建省中南部一次强飑线过程分析

利用常规气象资料、自动观测站资料和多普勒雷达等资料,综合分析了2005年3月22日发生在福建省中南部地区的一次飑线天气过程。结果表明:福建处于上干冷、下暖湿的不稳定大气层结中,南支槽和冷锋的逼近触发了不稳定能量的释放和风暴的发生。强风暴发生在高空急流出口区左侧辐散和地面冷锋前侧辐合重叠区。多普勒雷达资料很好地揭示了该飑线的发展、演变和移动特征。速度场的分析可以较早获得飑线东移中将发展加强的信息,对短时临近预报有指导意义。     

一次强对流天气的成因及环境参数特征分析

本文利用观探测资料、NCEP/NCAR再分析资料、雷达资料等,对2018年3月4日广西、湖南、江西一次区域性雷暴大风、冰雹、飑线等强对流天气进行分析,结果表明：高低空急流耦合,700hPa暖中心,850hPa强暖湿低空急流+暖脊+切变线,地面暖低压倒槽+辐合线+冷锋,上述系统是此次强对流天气的触发者和组织者;极端温差及水汽分布形成异常热力不稳定和位势不稳定;中低层强垂直风切变形成的动力不稳定使飑线组织化发展且长时间维持;弓形飑线与中低层风向夹角大,在西南急流引导下,飑线以60～120km·h-1速度向东北加速移动。在强低层风切变下,冷池能够触发其前沿空气产生较强上升运动,有利于飑线发展和维持。大风发生前10～30min,中层存在大风速核明显下降现象。     

一次中气旋冰雹天气过程的诊断分析

对2002年9月27日发生在山东省境内的一次冰雹天气过程进行了中小尺度和雷达资料分析。结果表明:华北冷性低槽的东移南压,并配合低空切变线和地面冷锋的共同影响是这次过程的直接大尺度影响系统;高空冷平流、地面暖平流,在对流层中低层形成了大范围上冷下暖的不稳定层结;低层中尺度低压环流的扰动,并与高空急流南侧的辐散区耦合,产生强烈的上升运动;雷达回波分析也发现,这次过程具有典型的小型超级单体风暴特征,存在并维持尺度较小的中气旋结构。     

2013年7月辽宁省降水异常物理机制研究

利用MICAPS常规资料和NCEP再分析资料,对2013年7月辽宁省降水异常物理机制进行了研究。结果表明:2013年7月辽宁省降水偏多发生在异常环流背景下,乌拉尔山高压脊和贝加尔湖低压槽强度大于常年,冷空气偏强且路径偏南;东亚40°—50°N处在纬向强锋区中,有利于气旋生成发展;副热带高压脊线比常年偏北2个纬度,西北侧暖湿气流活跃。7月中高纬地区有3次明显冷空气向南侵入至40°N,与中低纬北上至40°N及以北的暖湿气流交绥形成暴雨,影响系统分别为华北气旋、蒙古气旋冷锋和副热带高压西侧辐合线,不同影响系统暴雨过程的物理机制存在差异。3次暴雨过程中,华北气旋暴雨水汽供应最充沛,水汽源地不仅有西太平洋、南海、东海和黄海,还有孟加拉湾;暴雨区水汽主要由副热带高压外围西南或偏南气流向北输送,东海北部和黄海是水汽汇合及输送量最大的区域。高空急流受贝加尔湖低槽强度影响,不同影响系统高空急流演变和强度不同,低空急流分布与强度及高空辐散区、低空辐合区相对高、低空急流轴分布的位置也不同;高、低空急流耦合发展及高空辐散区、低空辐合区叠置产生的强垂直上升运动造成了水汽强烈辐合,其中华北气旋暴雨水汽辐合最强,水汽辐合层顶达850hPa,蒙古气旋冷锋和副热带高压西侧辐合线暴雨水汽辐合顶在900hPa附近及以下。热力分析表明,3次暴雨过程环境大气中层均有干冷空气侵入,增加了降水对流的不稳定性。     

景德镇地区一次早春飑线天气过程分析及数值模拟

利用常规高空、地面、雷达观测资料和FNL1°×1°再分析资料,应用天气学方法和数值模拟方法对2016年4月3日景德镇地区一次早春飑线天气过程进行了分析。结果表明:高空冷涡低槽引导的冷空气与西南暖湿气流强烈对峙是此次飑线过程的环流背景。高低空急流耦合作用加强了大气的垂直上升运动和锋面的次级环流,造成赣北地区上空大气具备较强的动力不稳定。回波强度超过55 dBz的低质心强对流云体是导致景德镇地区出现5 min降水量达14.3 mm强降水的重要原因。飑线的快速移动和近地面超20 m/s的大风速核可预示下游测站有大风出现。飑线前部辐合明显,上升运动剧烈,有利于强回波的发展。冷池的强度变化、持续时间与此次飑线的维持有关。     

粤西北一次冬季暴雨和雨转雨夹雪天气的分析

利用常规资料、NCEP 1°×1°再分析资料和连州双偏振雷达资料,对2018年1月8日粤西北暴雨和雨转雨夹雪天气过程进行分析。结果表明:副高增强、南支槽东移和切变线南压是该次暴雨形成的主要机制,西南急流提供动力条件和水汽条件,东北气流加大了风的垂直切变。强冷空气锋面形成低层冷垫,配合850～700 hPa逆温层,上暖下冷的层结有利于雨转雨夹雪。雨夹雪时零速度线呈反S型,并有零度层亮带和"牛眼"型结构特征。双偏振雷达参量Z_(DR)、K_(DP)能够判别出强回波的降水粒子形态,但不能识别雨转雨夹雪的粒子相态的变化。协相关系数能对融化层进行识别,HCL有助于快速定位降水粒子的相态。     

近10年严重影响云浮市台风的特征

通过对云浮市2009—2018年致灾严重(直接经济损失达到1 000万元以上)的台风资料进行统计分析,结果表明:对云浮市致灾严重的台风其生成源地多为西北太平洋。移动路径为西北太平洋西北行或者西行的台风、南海的北行台风。登陆地点在珠江口以西,特别是在江门地区附近。登陆时强度达到台风级别。登陆月份在8和9月。台风影响云浮市时的最大风力点多出现在新兴县和罗定市。台风影响云浮市24和48 h最大雨量点均出现在新兴县和罗定市。     

云浮高温天气及其环流形势统计与分析

为加深对云浮高温天气特征的认识,对云浮地区1981—2010年高温天气及其与副高、热带气旋之间关系进行统计分析。结果表明:云浮地区年高温天气大体呈增加趋势,测站局地环境不一致导致各测站高温天气年变化的并不一致。云浮地区高温天气主要出现在6—8月,7月最多,8月次之。云浮地区高温环流形势可分为4类:副高型、台风Ⅰ型、台风Ⅱ型和其它型。500 hPa位势高度(台风强度)与云浮地区台风I型(台风Ⅱ型)高温的关系不明显。500 hPa位势高度较高有利于台风Ⅱ型、副高型、其它型高温的发生发展。500 hPa位势高度大值中心位于测站以北(以西)有利于台风II型(其它型)高温发生发展,位于测站以东时副高型高温较多,位于测站东南则不利于高温天气发生发展。台风中心位于测站东北、东、东南三个方位,台风中心与测站距离600~1 600 km,台风强度在TS及以上时,有利于台风I型高温的发生发展。台风中心位于测站东方方位,台风中心与测站距离1 600~2 200 km,有利于台风Ⅱ型高温的发生发展。     

广东地区大风拟合的适用性研究

根据广东省电白、珠海、惠来、云浮、韶关和梅县6个气象站的历史最大风速资料,分别用极值Ⅰ型分布、皮尔逊Ⅲ型分布和韦布尔分布3种方法进行拟合分析。拟合的结果表明,极值Ⅰ型分布与皮尔逊Ⅲ型分布都能较好地拟合出最大风速的频率分布,韦布尔分布拟合效果较差;内陆地区极值Ⅰ型分布和皮尔逊Ⅲ型分布得到的结果相近,而沿海地区由于风速波动性较大,极值Ⅰ型分布拟合的重现期风速要大于皮尔逊Ⅲ型分布。但在各种工程的实际拟合应用中,仍然需要根据具体的情况采取合适的拟合方法。     

强弱天气尺度强迫下广东短时强降水时空特征分析

利用2010—2019年广东区域自动站逐时雨量定义短时强降水日,采用500 hPa和700 hPa广东区域日平均垂直速度来客观衡量天气尺度强迫,并对年均和强/弱天气尺度强迫下的短时强降水进行时空分布特征分析,结果表明:广东区域的短时强降水主要发生在4—9月,发生频次具有准双峰的日变化;粤西是短时强降水最频发区;茂名山区的短时强降水主要发生在白天,弱天气尺度强迫下占比达80%以上;频发次中心位于珠江三角洲,持续1小时以上的短时强降水占该地发生频次75%。强天气尺度强迫下短时强降水4—6月最多,弱天气尺度强迫下则7月达到峰值。弱天气尺度强迫下,仅历时1小时的短时强降水在粤北河源-梅州北部山区、粤东莲花山脉附近有次中心;历时2小时及以上的相对集中在粤西、珠江三角洲北部和粤东惠州-汕尾一带;3月肇庆-云浮和珠江口附近弱天气尺度个例占比高;7月粤北占比高;早晨07时在粤西阳江沿海有孤立的高频中心。      

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.     

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.