西安东部一次局地短时强降水天气过程分析

利用常规观测资料,NCEP1°×1°再分析资料和卫星云图、多普勒雷达、微波辐射计等多源数据,对2019年8月9日西安东部发生的一次局地短时强降水天气过程进行较为全面的中尺度特征分析。结果表明,小尺度的地面辐合和地形抬升是该次短时强降水的触发及加强条件;台风外围的偏东气流为强降水提供了充足的水汽和不稳定能量,且前期大气层结显示出较强的对流不稳定,有利于短时强降水触发后较大能量的释放并提升降水效率。短时强降水发生阶段监测到明显的干冷空气侵入过程,干冷空气可触发新对流,加强不稳定层结,加快水滴蒸发以增加潜热,从而加强了短时强降水。雷达反射率图上显示西安东部位于蓝田上、下游的对流单体在蓝田县附近形成对峙,并不断合并加强,是造成该地较强短时强降水的主要原因之一。     

巢湖地区一次梅雨期强对流暴雨中尺度特征分析

利用地面气象观测资料、ERA5再分析资料、FY-2E卫星和多普勒雷达资料,对2011年7月17日发生在巢湖地区的一次强对流暴雨过程进行诊断分析。结果显示:500hPa深槽、850hPa切变线及地面低压是此次暴雨过程的天气尺度影响系统,强降水发生在湿层和暖云层深厚、较低的抬升凝结高度、中等强度对流不稳定及弱垂直风切变条件下;FY-2E卫星云图分析表明,此次强降水过程主要是多个中尺度对流系统在巢湖合并所致,短时强降水落区主要落在中尺度对流系统TBB等值线密集区附近,TBB中心强度越强,TBB等值线梯度越大,对应的1h降水量越强;多普勒雷达分析揭示,短时强降水发生在两个对流回波合并期间,对流风暴移动缓慢,大于45dBz强回波均在6km以下,呈低层强烈气旋式辐合、高层辐散特征;地面中尺度辐合线是此次风暴的触发因子;湿位涡诊断结果表明,600hPa以下对流不稳定,600hPa以上对称不稳定,有利于暴雨和中尺度系统的发生发展。     

榆林一次短时突发性暴雨中尺度特征及成因分析

利用NECP 1 °×1 °间隔6 h再分析资料、卫星TBB资料、榆林多普勒雷达以及本地加密观测资料,对2017年7月23日榆林城区短时突发性暴雨成因及中尺度特征进行诊断分析,结果表明:此次强降水是在西太平洋副热带高压控制下产生的,副高外围中低层西南暖湿气流带来了水汽和不稳定能量;卫星云图和雷达上表现为中β尺度对流雨团和多个γ尺度强对流雨团;0~6 km中等强度的垂直风切变,对流不稳定能量和中低层强辐合,为短时暴雨的产生提供有利的环境场;地面图上干线触发了暴雨的产生。中尺度辐合的维持,使得飑线附近不断触发新的对流雨团,tBB＜－60 ℃区域与短时暴雨落区有较好的对应关系。分级最优Z-I反演降水估测产品能更好地反映中尺度对流性降水的量级,对预报员判别短时强降水具有指示作用。     

商洛一次局地暴雨诊断分析

利用常规观测资料、NCEP 1°×1°再分析资料、FY2E卫星资料、商洛多普勒雷达资料,从环流背景、水汽、动力条件和不稳定机制等方面对2014年7月28日发生在商洛局地性较强的一次短时暴雨过程进行分析。结果表明:这次短时暴雨过程天气的影响系统主要为短波槽、副热带高压与热低压。低层850hPa副高西侧暖湿气流北上为暴雨发生发展提供了有利的水汽条件。对流层中高层涡旋运动增强带动低层上升运动发展加强,为对流天气的进一步发展提供了动力条件。短波槽后西北干冷气流与低层偏南暖湿气流形成不稳定层结,加之中低层对流不稳定层结加强,CAPE值及低层湿度显著增大,抬升凝结高度与自由对流高度降低,因此在较低的抬升条件下,触发了此次对流性天气。卫星云图和雷达图上表现为中尺度系统,生命期短,发生发展速度快。强降水主要发生在对流云团强中心西北侧TBB梯度大值区。     

西北气流下乌鲁木齐短时强降水中小尺度特征个例分析

利用乌鲁木齐多普勒天气雷达、风廓线雷达、GPS/MET水汽探测仪以及FY—2E/G卫星、区域加密自动气象站资料和GFS/NCEP 0.5°×0.5°逐6 h再分析资料,对2015年6月9日18:30—20:00出现在乌鲁木齐的短时强降水过程进行分析,重点分析了强降水过程的环境场和中小尺度特征。结果表明:该短时强降水过程有4个降水集中时段,每个时段约为10~15 min。降水发生在高压脊前低槽后部的西北气流控制之下,700 h Paβ中尺度西北急流上γ尺度对流单体是短时强降水直接影响系统。该降水过程水汽来自于乌鲁木齐周围并在2~3 h内快速集中。对流不稳定潜势从午后14 h开始发展,到降水开始仅4.5 h。沿西北低空急流出现多个γ中尺度对流单体以"列车效应"形式依次影响乌鲁木齐造成短时强降水,对流单体组合反射率最强达45~50 d Bz,生命史仅15~20 min。降水发生在局地新生中尺度对流云团西南侧云顶亮温TBB梯度最大处,TBB最低达-44℃,对流云团生命史2~3 h。     

一次突发性强降水过程成因分析

利用常规观测资料、自动站、卫星云图、雷达回波等资料对2006年6月18日龙岩强降水过程进行成因分析。结果表明:有利的大尺度环流、充足的水汽条件和较强的上升运动,同时低层有冷空气入侵激发此次强降水的产生。强降水是由有利的中尺度地形中局地发展起来的中小尺度系统产生的。新一代天气雷达资料分析表明,对流单体有明显的典型的液态强降水系统特征。雷达资料风场反演表明风速辐合、切变等小尺度系统是产生短时强降水的成因。     

郑州市两次短时强降水过程的环境条件和中尺度特征对比

为了探求不同天气影响系统和垂直风切变下中小尺度系统造成的城市短时强降水过程的预报预警特征,以2007年8月2日和2008年7月11日发生在郑州市的两次短时强降水过程为例,利用常规观测资料以及河南省区域自动站、雷达探测资料等,对其大尺度环境条件和中尺度特征进行了对比分析。结果表明:以露点锋为触发机制的强降水超级单体和以锋区造成边界层辐合线为触发机制的混合性降水回波,虽然其雷达回波表现形式不同,但在地面中小尺度系统的作用下,都产生了1~2 h雨量达100 mm·h-1左右的短时强降水;地面辐合中心和高温高湿中心为短时强降水提供了动力抬升、热力不稳定能量和水汽条件;不同的0—6 km和0—2 km高度垂直风切变导致不同的对流回波形式,产生相同强度的短时强降水;短时强降水的降水效率不仅与云中降水粒子的大小有关,还与其数密度有关,即降水强度既与降水回波强度有关,也与其降水云中的滴谱分布有关;两次短时强降水过程分属于强对流型和热带降水型。结合地面加密站观测资料中小尺度分析与雷达探测产品分析,可对此类短时强降水发生提前预警。     

自贡一次短时强降雨过程的多尺度诊断

利用常规天气观测资料、ERA5的0.5°×0.5°再分析资料、地面自动站加密资料和卫星云图产品,对2020年8月12日四川省自贡市短时强降雨天气过程产生的原因和多尺度特征进行研究。结果表明：高空低槽与中低层辐合系统结合低空急流是本次暴雨天气过程的大尺度环流系统。低空急流为强降雨区提供了充足的水汽和能量;辐合上升动力作用增强、水汽含量的迅速增长、不稳定能量的增加,为对流性强降雨提供了条件;强烈发展的两个对流云团合并加强,形成强的中β尺度MCC,强降雨区位于MCC云顶亮温最低值中心附近,云顶亮温最低值达到-82℃;地面的中小尺度辐合线在短时强降雨中起到了对对流系统触发和加强的作用。     

“8·16”辽宁特大暴雨多尺度特征分析

利用常规观测资料和区域自动气象站、多普勒雷达、风廓线雷达、地基GPS水汽观测仪等非常规观测资料以及NCEP(1°×1°)再分析资料,对辽宁省清原县2013年8月16日特大暴雨过程的多尺度对流系统特征进行分析。结果表明:低涡切变线和东北低压是本次暴雨过程的主要影响系统。700 h Pa与地面之间假相当位温差达43 K,表明大气强烈的对流性不稳定结构。850 h Pa辽宁大部分地区比湿达14 g·kg~(-1),比湿大值区存在明显的水汽通量辐合,沈阳站监测到的大气可降水量达55 mm,可见本次过程水汽充沛。5次雷达回波依次经过清原地区形成"列车效应",导致该地区特大暴雨。地面辐合线触发的对流单体受其两侧风场的强弱影响,中低层西南风的加强有利于加大新生单体的垂直风切变和水汽条件。短时强降水导致的冷池与其周边暖气流交汇可能触发新的对流单体。在地形影响下,中-β尺度云团和α云系合并过程中的微物理作用可能是导致强降水的主要原因之一。     

“0713"山西短时强降水天气的潜势及触发条件分析

利用常规观测资料、NCEP 1°×1°再分析资料、FY-2G卫星逐时TBB资料、多普勒雷达及自动站资料,对2018年7月13日夜间出现在山西东南部的短时强降水天气进行了潜势及触发特征分析。结果表明:副高外围的强劲西南气流为本次短时强降水过程提供了充沛的水汽条件;"上干冷下暖湿"的层结结构与"高层冷平流、低层暖平流"的温度差动平流提供了强对流发生发展所需的能量条件;上升运动的形成和维持有利于不稳定能量的释放和增强。地面β中尺度辐合线发展为β中尺度涡旋,激发β中尺度对流云团的合并与加强;大于等于35 dBZ的β中尺度带状回波中镶嵌的γ中尺度对流单体,在500 hPa西南气流的引导下,形成高度组织化的多单体线状回波缓慢移动是形成局地短历时强降水的直接原因。     

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.