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1.
利用常规气象资料、中尺度自动站观测资料、NCEP 1°×1°分辨率再分析资料以及多普勒雷达资料等,对2012年6月21—23日汕尾地区连续性强降水过程进行了分析。结果表明:低层辐合、高层辐散、中尺度切变以及中层气旋性环流的相互配合触发了该次特大暴雨过程;前期不稳定能量的积累为强降水的发生提供了十分有利的条件;垂直上升运动有利于水汽的输送,低层辐合、高层辐散的形势场配置有利于上升运动的维持和水汽的抬升;地面中尺度辐合线的移动演变对强降水的持续时间和降水落区有较好的指示作用;中低层垂直风切变的增大、速度场的辐合有利于强单体风暴的形成和发展;南海夏季风随台风活动的演变对于预报暴雨的发生时间和强度有较大的指示作用。  相似文献   

2.
湖北梅雨期暴雨的中尺度系统及其模拟分析   总被引:20,自引:15,他引:5  
利用武汉多普勒雷达和武汉暴雨所AREM模式资料,分析了湖北省2005年梅雨期的一次暴雨过程。结果表明,暴雨发生在条状回波带变宽的时候,位于2 km上空切变线附近的中尺度气旋中,表现为强对流单体回波;强降水发生时,对流系统中有两个强上升运动中心,分别位于300 hPa和600hPa附近,低层辐合、高层辐散的分布对上升运动的维持是有利的;环境风场并不能很好地控制中尺度对流系统的移动方向,中尺度对流系统向低层涡度增加的地方移动;暴雨形成过程可概括为低层切变线东移诱发出地面低压,产生垂直上升运动迅速增加,配合丰沛的水汽输送和高不稳定能量释放。  相似文献   

3.
利用常规气象资料、AREM模式输出资料,对发生在2005年梅雨期湖北的一次暴雨过程进行了中尺度数值模拟分析。分析结果表明,强降水发生时,在对应的中尺度对流系统中存在两个分别位于300hPa和600hPa附近的强上升运动中心,低层辐合、高层辐散的单模态分布是上升运动得以维持的重要条件;环境风场并不能控制中尺度对流系统的移动方向,中尺度对流系统向低层涡度增加的地方移动;强降水形成可概括为低层切变线东移诱发地面低压发展、引起垂直上升运动迅速增加、触发低层水汽的垂直输送和高不稳定能量强烈释放等过程。  相似文献   

4.
利用常规观测资料、FY-2E卫星观测的TBB资料,对2015年8月19日发生在林芝地区的一次暴雨过程进行天气分析,并利用中尺度数值模式WRF的模拟结果分析此次暴雨过程中尺度系统的结构特征。结果表明,此次暴雨过程发生在高原低涡切变的环流形势下,伴随辐合线发展的线状对流系统是此次暴雨发生的主要原因。WRF模式可较好地模拟出暴雨过程的环流形势和降水的落区、量级。西南风引导的暖湿气流为暴雨的发生、发展提供充沛的水汽条件;对中尺度结构的分析表明,低层辐合、高层辐散的结构以及在降水区存在的正涡度伴随强烈的上升运动为此次暴雨过程提供了有利的动力条件,假相当位温的分布能够为暴雨提供有利的热力条件,垂直螺旋度低层正中心的配置反映出大气的不稳定分布,有利于中尺度对流系统的发展与维持。  相似文献   

5.
河南特强暴雨β中尺度流场发展机理的数值模拟研究   总被引:2,自引:2,他引:2  
采用宇如聪等研制开发的η坐标有限区域中尺度暴雨数值预报模式AREM,对2004年7月16—17日发生在河南的一次特大暴雨过程进行了数值模拟。模拟结果表明:凝结潜热促使对流层中层大气在β中尺度水平范围的气柱内得到加热,中高层大气的等压面抬高并形成β中尺度高压,中低层大气的等压面降低并形成β中尺度低压,上下层的共同作用促进了垂直运动的迅速发展。当上升运动强烈发展时,在其四周有明显的补偿下沉气流出现:在强上升运动南侧,对流层高层辐散气流向南回流导致对流层高层出现中尺度垂直环流圈,它的下沉支融入上升运动区南侧的补偿下沉气流中,并将高空的水平动量带到对流层低层形成一支新的β中尺度急流;在强上升运动北侧,对流层低层发展出了一支中尺度垂直环流圈,其下沉支向南的辐散气流与低层西南暖湿气流汇合,形成β中尺度辐合线,加强了暴雨区上空低层的辐合;在强上升运动东侧,对流层低层也有一支中尺度垂直环流发展,其下沉支中向西的辐散气流使该区域原来较为一致的西南气流出现向东的偏转,从而在西南气流中形成气旋性弯曲,更进一步加强了β中尺度辐合线上的辐合。对流层低层非地转涡度的强烈发展是β中尺度气旋形成的重要原因。最后给出了强暴雨β中尺度流场发展机理的三维空间示意图。  相似文献   

6.
利用NCEP 1°×1°格距逐6 h再分析资料、FY-2F逐时云顶亮温(TBB)资料、国家气象站常规探空和地面气象观测资料、湖北省区域气象自动站资料,对2019年5月25日湖北省东部一次大暴雨过程进行诊断分析。结果表明:500 hPa中高纬低槽不断分裂南下,盆地低槽稳定维持,中低层低涡扰动,切变线和低空急流维持,是本次大暴雨的有利天气背景;有西南向的水汽输送通道并在暴雨区强烈辐合,水汽辐合中心位于900~950 hPa,500 hPa以下整层温度露点差都在4℃以下;暴雨区在150 hPa以下为正平均涡度;400 hPa以上为正平均散度,其下为负平均散度,最强降水时段高层辐散低层辐合的配置明显向对流层下层压缩,高层负涡度低层正涡度的配置催生了高层辐散低层辐合的散度配置,有利于垂直上升运动加强;暴雨区上升运动从1 000 hPa延伸到200 h Pa,整层以上升运动为主,在最强降水时段上升运动中心明显下移;有明显的上冷下暖层结结构,形成低层暖平流高层冷平流的温度平流配置,有利于产生对流不稳定;降水云顶亮温TBB≤-50℃区域与降水区对应,近似圆形的中尺度对流系统对湖北东部强降水十分有利。  相似文献   

7.
利用常规观测、地面逐时降水、NCEP再分析资料和卫星雷达资料,对2008年7月22日发生在鄂西北襄樊的特大暴雨过程从对流层高层一直到地面的天气形势特征进行了较为系统的分析,结果表明,对流层高层稳定的辐散系统、近地层稳定的辐合系统以及中低层发展深厚的西南低涡、不断加强的低空急流是造成这次特大暴雨的主要影响系统.重点分析了200 hPa强辐散中心形成的原因及其在降水中心上空稳定、停滞、加强的机制,认为高空急流右后侧的风速辐散区与西风槽和南亚高压反气旋环流之间的风向开口区两种辐散作用的叠加是造成强降水中心上空强辐散中心的主要原因,而高层西风槽在东移过程中突然停滞并加深,从而导致强辐散中心一度稳定、停滞则是强降水持续发展的重要机制.在近地层,由一个已经发展的对流云团外围出现的强偏北下沉冷出流沿浅薄地形河谷区侵入襄樊附近,当偏南暖湿气流不断加强北进时,一方面受到冷出流的横向阻挡,另一方面又受到大巴山地形的纵向阻挡,两种阻挡作用交汇于襄樊上空,使低层出现强辐合中心并稳定维持,在高层强辐散的共同作用下出现深厚的上升运动.地面低压倒槽和准静止锋的稳定维持以及边界层内大气斜压性的增强也有利于中尺度对流系统在该区域的维持和发展.中低层发展深厚的西南低涡和不断加强的低空急流为强降水中心输送了充足水汽,从西南低涡的东北侧不断分裂出β中尺度对流云团和强回波单体,并沿低层切变线移动到襄樊上空后叠加在高空强辐散、低层强辐合的有利动力作用下而得到进一步发展,并最终形成特大暴雨.  相似文献   

8.
利用中尺度数值模式MM5模拟产品和CINRAD/SC多普勒天气雷达资料,对2005年9月20日一次鲁南地区大范围的切变线暴雨过程进行分析,表明,稳定的大尺度环流背景下的纬向切变线是产生暴雨的天气尺度系统,切变线上多个中小尺度气旋性涡旋使降水强度增大,造成局部特大暴雨;对流层中低层稳定维持的西南气流为强降水提供了水汽和不稳定能量,并造成大气层结对流性不稳定,也使降水得以持续;强降水区上空存在正涡度柱、散度柱、上升运动柱,涡度和上升运动柱中在高、低层各存在一个大值中心,散度场低空辐合高空辐散明显,当低层上升运动中心降低到850hPa以下和涡度、散度柱发生倾斜时,雨强则迅速减小。  相似文献   

9.
利用非静力中尺度数值模式WRF并结合NCEP-FNL分析资料、常规气象观测资料、FY-2F卫星TBB数据以及CM ORPH降水资料,对2014年6月29日至7月1日的一次高原横切变线过程进行了数值模拟并分析了其演变过程中降水、热力、水汽和动力的结构特征。结果表明,WRF模式较成功地模拟了此次高原切变线过程的降水量和落区。在高原切变线活动期间,不同阶段结构特征存在明显差异。切变线附近通常对应TBB-20℃的云区;随着切变线的发展,TBB值降低,在云区内有多个TBB-60℃的对流活动中心,对应主要降水期;在切变线减弱阶段,TBB值升高,降水趋于结束。高原切变线存在"南暖北冷"的热力结构,在切变线发展维持阶段呈现高层稳定、低层不稳定的垂直分布特征;高原切变线也是水汽的聚集带,水汽通量散度的转变对高原切变线的发展具有一定指示作用。在切变线初生阶段和维持、发展阶段,垂直方向上存在正涡度中心和辐合中心,呈现对流层低层正涡度和高位涡中心相耦合的动力结构;气旋式切变有利于高原切变线上正涡度的维持;散度场上的低层辐合、高层辐散的结构特征有利于切变线上垂直上升运动的发展;高原切变线上的辐合带先于正涡度带开始减弱、消失是高原切变线减弱的一种特征信号。  相似文献   

10.
一次陕西关中强暴雨中尺度系统特征分析   总被引:2,自引:0,他引:2  
应用高分辨率中尺度数值模式WRF模拟了2007年8月8-9日陕西关中强暴雨过程,根据模式输出结果对强暴雨中尺度对流系统(MCS)的发生、发展规律、形成原因和三维结构,特别是暴雨过程中3个大暴雨中心的β中尺度对流系统(MβCS)的细微结构包括三维流场、动力和热力结构进行了分析。结果表明,此次强暴雨过程与一个α中尺度低涡的生成密切相关,其内部强烈发展的MβCS直接产生了岐山、礼泉、高陵3个强暴雨中心的对流降水;MβCS在850,700和500 hPa上分别表现为辐合(涡旋)系统、西北—东南向暖式切变线和阶梯槽。高空西风急流入口区右侧的动力强迫是对流层高层暴雨区辐散形成和加强的原因,动力强迫引起的非地转风是暴雨形成的原因之一;中空阶梯槽携带的干冷空气从后方流入雨团起到了对流不稳定的加强作用;低层和地面不同方向的风和风速形成的中尺度辐合以及中尺度西南急流和东南急流触发了强降水的发生,强降水的发生又激发了中尺度急流扰动,中尺度急流扰动对暴雨维持和加强起到了反馈作用;秦岭山脉的屏障作用和关中喇叭口地形的动力抬升作用有助于关中强暴雨的发生和加强。产生3个强暴雨中心的MβCS有不同的流场、动力、热力垂直结构:中低层不同方向和不同层次的气流流入β中尺度降水云塔,在不同高度上形成了不同的垂直环流支,云塔中的上升气流一直伸展到200 hPa(或150 hPa)后向东南、东北流出;歧山暴雨中心450 hPa以上为强辐散,450 hPa以下暴雨中心南侧为弱辐散和辐合、北侧为辐合和弱辐散,垂直上升运动先向南、后向北倾斜直至对流层顶;相当位温呈双高能中心形成的双重位势不稳定层结结构,温度则表现为中层两个暖中心、上下层冷中心的特征;礼泉和高陵暴雨中心为整层强上升运动柱与强散度柱和正涡度柱耦合,礼泉上升运动柱存在一个高、低层冷而中上层暖的特征,具有类似于地面气压场的鞍形结构,即中低层不稳定、中高层稳定、中层为中性的层结结构;高陵暴雨中心南缘550 hPa以下是高能量和温度离差锋区,其上空400 hPa以下为近饱和水汽柱。  相似文献   

11.
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.  相似文献   

12.
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.  相似文献   

13.
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.  相似文献   

14.
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.  相似文献   

15.
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.  相似文献   

16.
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  相似文献   

17.
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.  相似文献   

18.
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  相似文献   

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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;  相似文献   

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