一次梅雨锋特大暴雨中尺度气旋和MCS的分析

利用自动气象站、多普勒雷达、FY4A、ECMWF模式、NCEP再分析资料,对2020年7月17—19日特大暴雨过程进行分析。结果表明：特大暴雨出现在安徽大别山附近和庐江两地,是中尺度气旋扰动环境下准静止的中尺度对流系统(MCS)以及MCS中准静止的涡旋状单体所产生。特大暴雨在高能量、强不稳定背景下,由中部和东部的中尺度气旋传播所致。中尺度气旋传播过程中单体不断新生、合并增强且移动缓慢,配合急流、辐合、干侵入、垂直环流等因素对组织化的MCS发展演变起到相当作用。低层切变线南侧到华南的西南急流,将水汽输送到安徽并在此有强烈辐合;高空、低空和超低空都存在急流,高低空急流耦合加剧MCS的强烈发展;地面辐合线是前期MCS的触发机制,伴随干冷空气的入侵,加大了大气的斜压性和MCS的对流不稳定;梅雨锋南北两侧都有垂直环流圈,即对流与高空急流之间通过对流加热在高空急流入口处产生热成风调整,维持梅雨锋的发展演变,强的上升下沉运动促进MCS的加强和降水的连续发生;大别山地形抬升和上游狭管效应是两地特大暴雨诱因。     

一次副热带高压边缘突发性暴雨的锋生及水汽特征分析

针对2010年7月31日夜间山西西南部一次业务模式出现较大预报偏差的西太平洋副热带高压(下称副高)边缘突发性暴雨天气过程,利用常规和降水加密观测资料、FY-2E卫星TBB数据以及中尺度模式WRF高分辨率数值模拟结果,诊断分析了暴雨的发生发展、锋生及锋生过程中的水汽演变特征。结果表明:此次突发性暴雨是由高空槽后干冷空气推动副高边缘暖湿气流所导致的一次锋生型强降水,β中尺度对流系统(meso-βcircular convective system,MβCCS)是造成暴雨的直接影响系统,低层β中尺度涡旋的形成和发展为MβCCS的维持提供了有利的水汽辐合条件,地面冷锋及其附近中尺度辐合线是对流触发因子。锋生诊断表明,低层辐合、中层辐散的垂直结构导致对流层低层水平锋生、中层水平锋消,而低层强烈的上升运动使得强不稳定层结高度升高,从而引起对流层中层强垂直锋生发展,垂直锋生与水平锋生同时产生,且垂直锋生较水平锋生大一个量级,中低层强锋生和次级环流圈的出现与强降水的发生时间和位置对应较好,比较而言,倾斜项对总锋生贡献最大,辐合项贡献最小。中低层锋生的加强有利于低层水汽的辐合抬升,锋生过程中深厚的水汽饱和层的出现以及水汽含量向高空的凸起,对局地强降水的预报有明显的指示意义。另外,高空冷空气的强度、移动路径以及MβCCS的发展对判断此类强降水的发生和暴雨落区具有重要作用。     

梅雨锋云带内α-中尺度对流系统周边水汽风的分析

应用准静止卫星水汽图像导出的风 (简称为水汽风 )分析东亚梅雨锋云带内中尺度对流系统 (MCS)在对流层上层的流出通道。结果表明梅雨锋云带内MCS有二类流出通道。一类MCS在对流层上层呈现为一个中尺度反气旋。MCS的东部有一支中尺度高空急流 ,这支中尺度高空急流向东流出后转向南 ,流入 2 0°N附近的南亚东风急流内 ,是MCS在对流层上层的主要流出通道。另一类MCS发生在中纬度西风急流的南侧。中纬度西风与MCS南部的偏东北风构成一个反气旋环流带。MCS前方的流出通道 (中尺度高空急流 )是中纬度西风急流的一个中尺度分支。梅雨锋云带内垂直方向水平风速切变小于 1m/ (s·10 0hPa) ,垂直方向“不通风”有利于云带内MCS的维持。初步分析验证了以前数值模拟得到的中尺度高空急流及其流出通道。     

一次长江中下游梅雨锋暴雨过程的诊断分析

利用NCEP 1°×1°再分析资料、FY-2C卫星云顶亮温(TBB)和中尺度模式WRF输出的15 km高分辨率资料,对2008年影响浙皖赣地区的一次梅雨锋暴雨过程进行了诊断分析.结果表明,青藏高原东侧西风槽和副热带高压之间的相互作用、对流层中低层切变线的维持以及低涡东移、发展是暴雨发生的天气尺度背景.TBB数据显示,在切变线附近不断有中尺度对流云团生成并东移、发展.与暴雨区相对应,在低空西南急流左侧存在多个β中尺度强水汽通量辐合中心,高空西风急流人口区右侧排列着一系列的辐散中心,表明该地区存在较强的水汽辐合上升运动.对流层低层高温高湿、中高层冷空气侵入,导致大气层结处于极不稳定状态.湿位涡的分布与中心位置对暴雨落区及强度具有较好地指示意义.暴雨区附近对流层高、低层都存在较明显的位涡水平平流,导致位涡扰动不断地自上游向下游地区移动.锋区前暖区的对流层中低层存在强垂直位涡柱,引发气旋性环流的发展,从而促进了辐合上升运动.     

准静止锋背景下的贵州两次暴雨天气过程对比分析

该文利用常规探空资料、地面观测资料及NCEP1.0°×1.0°再分析资料,对2014年6月9日08时—10日08时(简称9日,下同)和6月26日08时—27日08时(简称26日,下同)贵州出现的两次暴雨过程进行对比分析,结果表明:①两次暴雨均集中分布在20时准静止锋附近及其偏南一侧,跨越纬度约1°,其分布与环流垂直结构有较好的对应关系。②9日暴雨落区主要集中在贵州西南部,呈团状分布,降水时段比较集中;26日暴雨落区位于贵州南部一线,呈不连续的带状分布,降水时段偏长;9日08时准静止锋位于滇东,26日08时准静止锋位于贵州东北部,结合两次暴雨落区与准静止锋位置变化,暴雨落区与滇黔准静止锋摆动有极大的关系。③9日暴雨的水汽主要来源于孟加拉湾西南气流;26日暴雨的水汽受孟加拉湾偏西气流和副高外围西南气流共同作用。9日暴雨位于反气旋底后部东南气流与偏西气流交汇处,26日暴雨发生在低涡前部偏西南气流与偏南气流的交汇处。④9日暴雨垂直上升运动大值中心位于贵州西南部,26日暴雨垂直上升运动大值中心分别位于贵州西南部和东南部,暴雨落区与垂直上升运动大值中心有较好的对应关系;9日暴雨在贵州西南部上空存在低层辐合—中高层辐散—高层辐合的配置,26日暴雨在贵州东南部上空存在低层辐合—中高层辐散—高层辐合的配置,高、低空抽吸作用对暴雨发生提供了有利条件。     

冷空气对台风“海葵”(1211)倒槽特大暴雨作用分析

针对2012年8月10日发生在台风"海葵"(1211)减弱低压倒槽顶部的特大暴雨过程,利用加密自动气象站、卫星云图、NCEP再分析资料,结合中尺度数值模式的模拟结果,分析了这次特大暴雨期间的中尺度对流系统演变特征及形成机理。研究表明,东北冷涡后部南下的冷空气为特大暴雨的发生提供了有利的热动力条件,促进了降水的发展。冷空气主体偏北,仅从对流层中层侵入低压倒槽北部,而对流层低层并无明显冷空气影响,使暴雨区上空形成冷平流叠置于暖平流之上的温度平流垂直分布结构,促进这一地区对流不稳定层结的建立和发展。冷空气与低压倒槽内辐合上升的暖湿空气对峙于对流层中层,引起中层锋生,锋生效应使风场辐合加强,进一步促进锋生。两者相互作用促进暴雨区及附近的中小尺度对流系统发展,在暴雨区上空强迫出一支对流尺度的强上升气流,加强低层水汽向上输送,使暴雨区上空水汽辐合层迅速增厚,从而引发局地特大暴雨天气发生。     

一次滇黔准静止锋大暴雨天气过程的物理量场特征分析

利用NCEP/NCAR逐日4次再分析网格点资料,对2006-06-05滇黔准静止锋大暴雨天气过程中主要影响系统、各种物理量场特征进行诊断分析,结果表明:500hPa小波动移出、地面静止锋锋生是此次暴雨过程的触发机制;静止锋系统较浅薄,产生的对流性运动仅达700hPa高度;强降雨带位于静止锋锋区附近;锋生函数对大降水的落区及降水时段具有很好的指示意义。     

一次梅雨锋暴雨中尺度系统发展的动力机制分析

应用常规资料、TBB资料和NCEP分析资料,对2007年7月25日发生在湘黔边境的一次梅雨锋大暴雨天气过程进行了分析.结果表明:深厚的高空低槽和副热带高压稳定维持,有利于冷暖空气的辐合和梅雨锋的长时间维持.梅雨锋上不断有中小尺度对流系统产生,这些中小尺度对流系统在受到大尺度强迫作用和梅雨锋自身的强迫抬升作用而发展增强并长时间维持,在暴雨区形成强烈的降水.暴雨区上空具有低层辐合、高层辐散的结构特征,低层的辐合使得涡度往中上层输送,这种耦合形势有利于垂直上升运动和暴雨的维持.积云对流释放的凝结潜热加热对流层中上层大气,引起梅雨锋锋生,维持和促进了垂直上升运动和对流活动.     

贵州一次辐合线锋生极端暴雨过程的中尺度特征分析

利用地面常规观测资料及加密自动站观测资料、FY-2G卫星云图、多普勒天气雷达产品和ERA5再分析资料,对2021年5月10日贵州东部和北部的一次辐合线锋生极端暴雨过程中尺度特征进行分析,初步探讨其形成机制。结果表明：此次极端暴雨过程发生在低涡切变背景下,低层强盛的南风为中尺度对流系统发生发展输送了充足的水汽和不稳定能量,地面辐合线及锋生提供了触发条件,暴雨区主要位于云团云顶亮温低值中心西侧或南侧梯度大值区,并沿地面辐合线呈东西向带状分布,最强降水发生在对流云团合并阶段。辐合线锋生作用在其西侧频繁触发对流单体,新生对流单体沿地面辐合线东移发展,持续影响贵州东部和北部地区。在降水最强的两个阶段,雷达回波呈现暖云和悬垂结构特征。地面辐合线及其锋生、上游降水带来的降温增压以及持续增强的南风有利于暴雨区水汽辐合增强,而垂直方向上纬向、经向中尺度次级环流上升支正好位于特大暴雨中心附近,有利于中尺度对流系统维持和增强。     

2011年1月湖南罕见持续性暴雪天气成因分析

应用常规观测资料和NCEP再分析资料,对2011年1月湖南发生的罕见大范围持续性暴雪天气过程进行了详细分析。结果表明：乌拉尔山阻塞高压和孟加拉湾南支槽稳定维持,“南低北高”环流形势有利于冷暖气流在长江中下游地区一带汇合,是持续性暴雪发生的大尺度环流背景;700hPa西南急流的建立和加强为暴雪区带来源源不断的水汽供应和不稳定能量,持续而强盛的水汽输送和水汽辐合对暴雪维持和加强至关重要;青藏高原有两次明显的正涡度向东传播至我国东部地区,正涡度东传有利于垂直上升运动维持和加强;暴雪期间湖南上空维持较强的锋生区,准静止锋稳定少动,锋区强度逐渐增强,其最强阶段与暴雪最强阶段一致,而高空急流和锋面的耦合加强了湖南区域的上升运动,是暴雪天气持续的主要原因;锋前干冷空气在对流层中层形成的干层加强了暴雪过程的对流性不稳定,而锋后干冷空气作为“冷垫”锲入暖湿气流下方,促进锋生和暖湿空气的抬升和凝结,是不稳定能量释放的触发机制。     

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.     

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     

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.     

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;