沿海地区一次中尺度对流系统闪电活动及降水结构

利用TRMM卫星的测雨雷达,微波成像仪,闪电成像仪等探测数据,研究了2010年8月5日发生在江苏北部一次中尺度对流系统(MCS)的降水结构和闪电活动之间的关系.结果表明:MCS在发展阶段,对流云降水面积与层状云降水区相当;在减弱阶段,层状云降水区面积远大于对流云降水区.MCS的生命史中,大部分闪电发生在对流云区,仅有少数闪电发生在层状云区,在减弱阶段闪电多发生在对流云和层云的过渡区中.发生闪电的层云和对流云降水垂直廓线表明:在MCS的发展成熟和减弱中在4 km高度,层云降水率都达到最大值;在对流云降水区中发生闪电主要与对流云上空含丰富的冰相粒子和对流云发展厚度(顶高达17 km)有关.研究还表明闪电数目最大值一般回波强度在35～45 dBz之间,并非回波越强闪电越多.闪电主要发生在40～50 dBz之间,且明显向强回波区趋近,这对我们利用雷达回波预警闪电落区具有一定的参考意义.     

2008年8月1~2日滁州特大暴雨双多普勒雷达三维风场反演试验的初步结果

受“凤凰”低压和冷空气共同影响, 2008年8月1~2日安徽省东部和江苏西部部分地区出现大雨, 局部地区暴雨到特大暴雨。滁州和全椒24 h雨量分别为429 mm和414 mm, 此次特大暴雨具有局地性和降水强度大的特点。使用南京和马鞍山双多普勒雷达时间同步观测资料, 对此次暴雨的三维风场进行反演, 在此基础上, 研究了暴雨的三维风场结构。由雷达回波分析可知, 此次暴雨是由β中尺度对流系统造成的, 在β中尺度对流系统内部还有γ中尺度对流单体, 对流单体发展非常旺盛。中低层切变线自西向东移入降水区后, 在该地区停留较长时间, 加之有充足的水汽供应, 造成了局地特大暴雨。在垂直剖面内, 对流系统发展旺盛, 强降水区上空回波较强且对应着较强的上升气流区, 而在强回波中心区的两侧均有下沉气流。当切变线减弱并移出降水区后, 强降水停止。     

一次飑线过程的雷达观测和数值模拟分析

利用NCEP再分析资料、国家级自动气象站降水资料、武汉探空和多普勒雷达回波资料,借助WRF模式,对2011年7月26日发生在湖北的一次飑线过程进行环境场分析和数值模拟研究。结果表明:此次飑线发生在弱的垂直风切变和强对流不稳定环境下。飑线形成阶段,系统内存在左、右2条强对流回波带。对不断发展增强的左支回波带进一步模拟发现:初期,环境风垂直切变较弱,飑线前部强不稳定能量是飑线新生单体不断发展加强的主要原因;此后,不稳定能量逐渐释放,垂直于飑线系统水平动量的垂直逆梯度输送使得与飑线发展方向平行的对流层低层风垂直切变增强,为飑线发展提供动力条件。在飑线发展过程中,新生单体不断在对流区前沿触发加强以及对流单体合并与增长使得飑线系统得以长时间维持,而成熟单体减弱为后方的层状云降水区,正是单体的生消交替保证飑线系统向前传播。     

大气探测资料在中尺度暴雨中的分析和应用

使用近几年强化气象业务观测网建设所获得的大气探测资料,包括每小时1次的自动雨量站资料、逐时的GOES-9卫星红外云图TBB资料、多普勒雷达反射率因子、径向速度及回波顶高资料,并结合NCEP/NCAR再分析资料,对2003年6月29—30日淮河流域大暴雨过程进行了中尺度观测研究。分析表明:高时空分辨率的大气探测资料能较好地描述暴雨过程的中尺度特征;同时,停滞在淮河一带的梅雨锋和切变线为此次大暴雨发生提供了有利的背景条件;暴雨过程期间,淮河流域梅雨锋云系上共有11个β-中尺度对流云团发生,它们是暴雨的直接制造者;此次大暴雨过程主要由2次中尺度强降雨时段组成,中尺度雨团的源地集中在安徽西北部,雨团的发生与β-中尺度对流云团活动有密切关系;雷达回波的分析显示,此次暴雨是混合云降水所致,在层状云降水区中有许多对流云回波,对流回波区和径向速度场所反映的中尺度辐合线与中尺度对流系统的演变有密切的关系。     

华北一次强对流天气系统的地闪时空演变特征分析

利用地面雷电探测网,多普勒天气雷达和常规天气资料,分析了2005年8月1日发生在山东北部的一次具有前部对流线,后部大范围层状云降水(LLTS)的典型中尺度对流系统(MCS)的闪电活动演变特征。结果表明:整个过程中负地闪占主导地位,最高频数达到260次/5min;与负地闪比较,正地闪呈现不活跃状态。负地闪主要落在>40 dBz的强回波区内部及其边缘区域,而正地闪则分布在前部云砧和后部层状云降水区内。对地闪位置与回波强度的进一步对比分析发现,45~55 dBz的回波是最有利于地闪发生的区域,回波强度低于这一区域,随着回波强度的增大,地闪活动呈递增趋势,地闪频数在50~55 dBz的回波区域内达到峰值,>55 dBz的回波区域内地闪频数明显降低。     

黄土高原一次γ中尺度致洪大暴雨环境场特征分析

为了提高对黄土高原γ中尺度致洪暴雨预报和预警能力,利用NCEP 1°×1°逐6 h再分析资料、常规观测资料、多普勒天气雷达资料等,对2015年7月18日黄土高原发生的一次γ中尺度致洪暴雨进行了诊断分析。结果表明:700~200 h Pa深厚低涡和低层切变是这次暴雨的主要影响系统;暴雨发生前暴雨区大气层结对流不稳定增强和对流有效位能的增长为强天气的发生提供了有利条件;暴雨发生前地面图上生成的湿焓高能中心、850 h Pa和700 h Pa等压面上生成的对流涡度矢量垂直分量高值中心和暴雨落区形成很好的对应关系;线状中尺度对流系统中β中尺度对流云团的发展加强对强降水有直接影响;线状中尺度对流系统在雷达回波图上体现为多个对流单体组成的带状回波,影响暴雨区的对流单体回波中心强度50 d BZ,径向速度场分析表明γ中尺度气旋性辐合的生成和维持为暴雨的持续提供了动力条件。     

湖北一次飑线过程的观测分析及数值模拟

用武汉新一代多普勒天气雷达(CINRAD)9层体扫模式观测资料、常规和地面加密观测资料、以及NCEP一日4次的1°×1°再分析资料,采用中尺度非静力模式(WRF)对2007年5月31日湖北飑线过程进行观测分析及数值模拟研究。结果表明,雷达回波显示出飑线前方强而窄的回波带、过渡带、后方宽广的次强层状回波区特征;新单体在对流区前沿周期性地产生,成熟单体减弱为后面的弱回波区,在不断的生消交替过程中系统向前传播。数值模拟表明,在飑线前方上空是强而窄的上升气流,后方中层偏上是一支宽广的从前向后(由南向北)斜上升气流,下方是从后向前(由北向南)的斜下沉气流;飑线低空有两支入流:前方偏南气流和后方下沉入流,高空出流一部分向北倾斜上升,另一部分翻转向南。飑线系统内气流沿着湿而高θse值带进入和上升,在干而低θse值区下沉。低层风切变和飑线后部冷丘的作用是造成飑线垂直结构的可能原因。飑线结构的数值模拟与雷达观测结构基本一致,其特征与美国经典飑线概念模型(TS型:拖曳层状)类似。     

飞机人工增雨催化作业云系结构特征分析

利用ＧＭＳ－５卫星云图资料，配合雷达，探空、Ｍ－ＬＤＡＲＳ闪电定位探测系统观测资料及常规天气资料，对１９９７年３月１３日飞机人工增雨催化作业云的宏观结构特征及其演变规律作了综合分析。结果表明，卫星云图上逼点云系的主要降水云是以片絮状回波结构为主的层状云降水区，云内含水量充沛，适合于飞机人工增雨作业。在云系东侧边及尾部，不断生成有中尺度对流回波系统，不仅造成了局地较强降水，而且产生了雷暴天气。     

一次后向传播强对流暴雨过程的综合分析

利用多普勒雷达、风廓线雷达以及NCEP0.5°×0.5°再分析资料,对2013年6月24日发生在浙江北部、造成杭州严重城市内涝的一次局地大暴雨过程进行了分析,结果表明,大尺度天气背景非常有利于强对流天气过程发生;特殊的传播路径是造成局地大暴雨的主要原因;对流降水系统质心低,40~55dBz强度的回波是造成强降水的主要因子,边界层辐合带触发的线状风暴具有明显的突发性,强回波集中在近地面层,并长时间的停滞是单点大暴雨发生的重要原因。     

滇缅脊前一次弱对流形成的局地大暴雨过程分析

利用常规观测资料、加密自动站资料、NCEP 1°×1°每6 h再分析资料和多普勒雷达资料,用尺度分离和物理量诊断分析方法,对2005年8月7日发生在云南新平平掌的局地大暴雨进行综合分析,结果表明:低层700 hPa滇缅脊前哀牢山沿线切变线内生成的中尺度气旋,是产生局地强降水的主要天气系统;局地大暴雨发生在低层辐合、中高层辐散的弱对流环境中,低层局地强水汽辐合为此次大暴雨提供了水汽条件;局地大暴雨发生前垂直螺旋度低层为辐合上升,强降水发生在辐合上升运动减弱期;大暴雨发生在对流云团温度梯度迅速增大的位置,多普勒雷达回波强度和回波顶高均无强对流特征;局地大暴雨发生地有逆风区形成,不断南下补充的新对流单体,使得β中尺度回波长时间维持,是导致局地大暴雨发生的重要原因。     

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