2021年黑龙江两次超级单体龙卷过程多尺度特征

2021年6月1日和6月9日黑龙江省哈尔滨尚志市及阿城区和齐齐哈尔梅里斯区分别发生双龙卷事件。利用常规气象观测、多普勒天气雷达等资料对比分析二者的多尺度特征。结果表明:两次龙卷均发生在东北冷涡的东南象限，高空急流出口区左侧，中低层偏南气流有利于暖湿气流输送和垂直运动发展。6月1日和6月9日分别以短时强降水和雷暴大风天气为主，6月1日水汽条件、垂直运动、0~1 km高度垂直风切变和抬升凝结高度更有利于产生强龙卷，且中尺度气旋维持时间更长。干线与地面辐合线为中尺度触发机制。雷暴冷池出流与中尺度暖锋形成的伪冷锋有利于龙卷的发展和维持。龙卷出现在地面伪冷锋与干线交界处的湿区一侧，冷池前沿，龙卷母云为超级单体。暖湿气流产生的入流缺口是钩状回波发展的前兆，中等到高强度的中尺度气旋在3 km高度产生并发展，5~10 min后触地，当钩状回波与中尺度气旋同时出现时龙卷产生。     

江西三类致灾大风天气活动与回波特征分析

使用常规天气资料、灾情资料、自动气象站、卫星云图和雷达回波等资料,对江西出现的灾害性大风天气进行分析,结果表明：江西致灾大风天气主要有三种类型。（1）与飑线回波带和超级单体等雷达回波系统相伴随的雷雨大风天气,同时还伴随强雷电、强降水、冰雹和龙卷等灾害性天气;（2）与冷锋雷暴回波带和冷空气大风相伴随的混合大风天气,具有雷雨大风天气和冷空气大风天气活动的特征;（3）由雷暴下沉气流触发、中高空动能下传和气压梯度风共同作用产生的无降水致灾大风天气,没有降水、雷电等天气现象伴随。     

四川盆地一次极端大风天气过程成因及预报着眼点分析

利用常规观测资料、FY-2E卫星云图、多普勒雷达产品、闪电定位资料、自动气象站资料等,分析了2015年4月4日傍晚到夜间发生在四川盆地的极端大风天气过程。分析指出:本次雷暴大风过程是由冷锋对暖湿气团的强迫抬升及干冷空气进入暖湿区域触发形成.中空干层、大的温度直减率、高低空急流耦合区、低层温度脊附近是利于极端雷暴大风出现的潜势区域。该区域为雷暴形成提供了条件不稳定、水汽、动力抬升等有利环境条件。冷空气首先从盆地西北部中低层入侵,在低层切变线上触发生成了一系列雷暴单体,在最有利于对流发展的潜势区域迅速发展。潜势区域中线状回波北段的中尺度涡旋环流、前侧入流和后侧入流的相互作用形成单体弓形回波,该弓形回波具有比普通雷暴更高的反射率因子、垂直液态含水量.根据雷达回波演变特征推断,本次极端大风是由单体弓形回波带来的湿下击暴流所导致。弓形回波中高反射率因子的高度连续下降意味着下沉气流伴随降水粒子下降,干空气被夹卷进入下沉气流使得雨滴被迅速蒸发,大大加强了下沉气流强度,因而显著增加了大风强度。分析还指出:通过分析对流发展背景条件,确定最有利对流发展的潜势区域,关注该区域中回波的生成、形态特点、演变特征,可提前预警大风天气。     

2016年9月通辽市一次龙卷过程的观测分析

利用常规观测、多普勒雷达、NCEP再分析等资料对2016年9月24日通辽市库伦旗龙卷发生的环境条件和雷达回波特征进行分析,结果表明:此次龙卷过程发生在高空槽前、中高层急流北侧、低空急流左侧和地面气旋暖区一侧,是由超级单体引发的;干线和地面冷锋是强对流发生的直接触发机制,龙卷发生在干线附近靠湿区一侧;基本反射率因子图上呈现入流缺口和钩状回波,反射率垂直剖面图上存在低层弱回波和中高层回波悬垂,大于55 dBz回波高度超过11 km中气旋生成后强度有增大的过程,有利于龙卷天气产生。     

一次南支槽引发德宏州强对流天气成因分析

利用常规气象观测资料、静止气象卫星云图资料和多普勒雷达探测资料,对2013年5月3日一次南支槽引发云南德宏州发生雷暴大风和冰雹强对流天气过程的特征、中尺度环境场及成因进行了分析,结果表明:5月3日在南支槽天气背景下德宏区域内为对流不稳定,具上干下湿的不稳定层结,有强的垂直风切变;在干线和中尺度辐合线的触发下产生了这次强天气过程。高分辨率卫星云图能够清楚的监测MCS的发生发展,雷达监测提高了时空分辨率,监测到速度模糊、弓形回波、三体散射、后侧"V"型缺口、有界弱回波区等指示冰雹、大风等强对流天气的雷达回波特征。     

一次飑线过程中龙卷及飑锋生成的中尺度分析

对1983年9月4日发生在陕西中部一次灾害性强风暴过程的天气形势、雷达回波、卫星云图、地面中尺度风场资料及灾情进行了综合分析研究,结果表明:此次灾害性强风暴是一次龙卷过程;龙卷出现在冷锋飑线带状回波尾部,呈典型的弓状回波（环状回波）;在卫星云图上表现为南北云系交绥处发展旺盛的中尺度涡旋云团,呈新月状;龙卷发生在地面“人”字形辐合线交点后部强西北风中;龙卷是由地面两条冷锋的共同作用造成的;飑锋回波出现在龙卷雷暴后部,表现为两条平行的线状回波,与经典理论有不同之处。     

一次龙卷风天气的特征分析

利用河南濮阳CINRDA/SB多普勒雷达探测资料,结合常规天气图资料、地面加密自动站资料等,对2009年7月16日发生在河南濮阳的龙卷天气过程进行诊断分析,结果表明:这次龙卷天气过程发生在副热带高压边缘西北侧、低空急流左前方的暖切变线附近;龙卷发生前大气环境具有较大的对流不稳定能量,低层存在大的风垂直切变和丰富的水汽;多普勒雷达反射率因子图上表现为移动的弓形回波北段强烈发展形成钩状回波,龙卷生成于钩状回波弱回波区附近。径向速度图上表现为在大范围入流风场中出现伴有辐合的γ中尺度气旋式涡旋,涡旋进一步发展加强导致其中央龙卷涡旋的产生,产生龙卷风天气。另外,强回波、低回波顶高、低层强垂直风切变都是这次龙卷过程中多普勒雷达产品特征。     

河北保定"7.9"致灾雷暴大风环境场与风暴特征

利用常规观测资料、地面加密观测资料、雷达产品、卫星云图以及NCEP/NCAR逐日6 h再分析资料,对2017年7月9日保定区域性雷暴大风的环境条件和风暴特征进行分析。结果表明:本次区域性雷暴大风过程发生在高空西北偏西气流中,强温度直减率、较强的低空垂直风切变、低层丰富能量的聚集是雷暴大风爆发的前提条件,地面冷锋、干侵入和地面中尺度辐合线为触发机制。地面冷锋前部分散的对流云团在地面中尺度辐合线附近合并为有组织的带状回波。第1阶段和第2阶段10级以上雷暴大风发生在雷暴云的成熟期,第1阶段雷暴大风的径向速度为中气旋型,中气旋首先在中层出现,之后分别向低空和高空伸展,随着中气旋底部高度降低到2. 2 km,雷暴大风发生;第2阶段雷暴大风的径向速度主要为低空(1. 0 km)雷暴云后侧强的入流气流造成的大风区型;第3阶段10级以上雷暴大风出现在雷暴云的消亡期,为雷暴云前侧强出流气流形成的雷暴大风。     

通辽市一次冰雹天气中尺度分析

利用常规观测资料、ERA(0.25°×0.25°)再分析资料、通辽多普勒雷达（CINRAD/CB型）探测资料和卫星云图（FY-4A）资料,对2022年6月20日通辽市冰雹天气进行成因分析。结果表明：500 hPa冷涡底部短波扰动和低层低涡切变环境中雹暴云团发展,低层适当的水汽条件、较大的对流有效位能、中高层干冷空气叠加在低层暖湿空气上形成了对流不稳定层结、较强垂直风切变和地面干线的触发作用下不稳定能量释放。对流有效位能（CAPE）、K指数、SI、总指数（TT）等参数均达到强对流天气阈值。两个尺度较小的雹暴云团均沿着环境引导气流方向自西北向东南移动。反射率因子剖面图上,呈中高层回波悬垂,低层弱回波区、回波墙、假尖顶回波等特征。移动较快的“W”形弓形回波有明显的前侧入流缺口和后侧入流缺口。前侧入流缺口有强的上升气流,有利于冰雹的增长,后侧入流缺口表明有强的下沉气流,可能引起雷暴大风。垂直累计液态水含量跃增并维持较高值。雷达产品特征均较好地反映发生冰雹天气。     

辽宁营口2019-08-16龙卷过程双偏振雷达特征分析

利用MICAPS、自动站和双偏振雷达资料,分析营口2019年8月16日龙卷天气过程。发现此次龙卷天气在高空低涡的天气背景下发生,高层冷平流与低层暖平流叠加,积累了充分的不稳定能量,为龙卷的发生提供了潜势;温度层结曲线与露点温度曲线呈“X”型,有利于雷暴大风生成。雷达图上南北两条窄带回波相遇是雷暴的触发条件;产生龙卷的雷暴单体强回波区域向下延伸指示了雷暴的发展情况,反射率图上高层强回波悬垂、低层弱回波区、钩状回波预示着该风暴为强风暴;径向速度产品图上表征气旋式旋转的正负速度对的发展变化可以指示龙卷的位置和强度,05°仰角上辐散区可以确定地面大风的发生时间和位置;相关系数CC产品、差分反射率ZDR产品、差分相移率KDP产品等偏振量有利于确定龙卷的影响范围;粒子分类产品对冰雹落地时间有较好的指示。     

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.     

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.     

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.     

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     

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.     

Information for Authors

正AIMS AND SCOPE Atmospheric and Oceanic Science Letters (AOSL) publishes short research letters on all disciplines of the atmosphere sciences and physical oceanography. Contributions from all over the world are welcome.SUBMISSIONAll submitted     

Information for Authors

AIMS AND SCOPE Atmospheric and Oceanic Science Letters （AOSL） pub- lishes short research letters on all disciplines of the atmos- phere sciences and physical oceanography. Contributions from all over the world are welcome.