两次强降水过程雨滴谱特征及差异

利用寿县观测站内的Parsivel激光雨滴谱仪结合观测站雨量数据及雷达基数据,分析了发生在2015年6月26—30日梅雨期间和2015年8月7—10日超强台风"苏迪罗"影响期间2次强降水过程的雨滴谱结构特征及其差异,拟合了雨强与雷达反射率因子之间的关系。结果表明:雨强的大小直接影响雨滴谱的特征参量,且随着雨强增大而增大;梅雨锋暴雨中1.0mm直径≤1.5mm的粒子所占比例最多,雨强贡献率最大;台风雨中0.75mm直径≤1.0mm的粒子所占比例最多,但1.0mm直径≤1.25mm的粒子对雨强的贡献最大,说明较大粒子对强降水的贡献较大。     

2017年冬季长沙一次重度霾污染天气过程气象成因分析

利用空气质量监测资料、常规气象资料,根据气象条件的水平和垂直扩散能力,以及地面湿度和动力条件等分析了2017年1月27—29日长沙地区这次严重空气污染事件的污染特征。结果表明:污染发生时段,南支槽不断加深东移,槽前势力强盛的西南气流将孟加拉湾一带的水汽向长沙地区输送,进一步增加了该地区的空气湿度。同时,持续东移的脊前暖平流对长沙中低层大气增温有显著影响,为稳定的大气层结创造了有利条件。长沙处于弱高压的底后部,受大范围的弱鞍型场及均压场控制,地面有暖倒槽发展,且由于高压较弱,导致地面和低空的风速较小,不利于污染物的水平扩散,同时有利于夜间地面的辐射降温。稳定的大气环流形势为霾天气和严重污染提供了持续稳定的大气环境场,逆温结构和稳定温度层结在一定程度上减弱了大气在垂直方向上的湍流交换和热力对流,大气中的污染颗粒不易扩散,为此次污染事件的维持、加剧提供了重要的气象条件。长沙地区处在罗霄山脉和雪峰山脉之间的湘江故地,受周边地形阻挡的影响,污染物在下沉气流的控制下聚集到长沙地区后,很难通过水平输送离开,这也是造成此次霾污染的原因之一。     

《巴黎协定》实施细则适应议题焦点解析及后续中国应对措施

适应是《联合国气候变化框架公约》及其《巴黎协定》下的重要谈判内容。2018年12月举行的第24次缔约方大会（COP24）就适应议题后续实施方案达成了共识,为全球气候治理带来新的机遇和挑战。中国在未来全球气候治理中,如何借助新成果推动国内适应工作稳步发展,积极发挥中国作用,是新形势下亟需考虑的重要问题。基于此,本文梳理了适应议题的焦点问题、各集团和缔约方的立场观点,展望了2019—2025年适应相关议题主要工作安排,并对此提出了中国未来适应领域完成相关工作需要考虑的应对措施建议,包括：(1)深入分析国际信息报告体系与国内信息的联系,梳理国内适应工作亮点,为构建高质量报告奠定基础;(2)构建跨部门跨地区协作机制,加强信息搜集与完善,有效提高数据和信息统计功能;(3)强化气候变化适应技术、规范、标准等科学研究的作用,为制定政策规定时纳入相应技术要求、提高政策规定等需求提供科学性和可操作性的服务。     

A Numerical Investigation on Microphysical Properties of Clouds and Precipitation over the Tibetan Plateau in Summer 2014

In order to improve our understanding of microphysical properties of clouds and precipitation over the Tibetan Plateau (TP), six cloud and precipitation processes with different intensities during the Third Tibetan Plateau Atmospheric Science Experiment (TIPEX-Ⅲ) from 3 July to 25 July 2014 in Naqu region of the TP are investigated by using the high-resolution mesoscale Weather Research and Forecasting (WRF) model. The results show unique properties of summertime clouds and precipitation processes over the TP. The initiation process of clouds is closely associated with strong solar radiative heating in the daytime, and summertime clouds and precipitation show an obvious diurnal variation. Generally, convective clouds would transform into stratiform clouds with an obvious bright band and often produce strong rainfall in midnight. The maximum cloud top can reach more than 15 km above sea level and the velocity of updraft ranges from 10 to 40 m s-1. The simulations show high amount of supercooled water content primarily located between 0 and -20℃ layer in all the six cases. Ice crystals mainly form above the level of -20℃ and even appear above the level of -40℃ within strong convective clouds. Rainwater mostly appears below the melting layer, indicating that its formation mainly depends on the melting process of precipitable ice particles. Snow and graupel particles have the characteristics of high content and deep vertical distribution, showing that the ice phase process is very active in the development of clouds and precipitation. The conversion and formation of hydrometeors and precipitation over the plateau exhibit obvious characteristics. Surface precipitation is mainly formed by the melting of graupel particles. Although the warm cloud microphysical process has less direct contribution to the formation of surface precipitation, it is important for the formation of supercooled raindrops, which are essential for the formation of graupel embryos through heterogeneous freezing process. The growth of graupel particles mainly relies on the riming process with supercooled cloud water and aggregation of snow particles.     

SIMULATION OF TROPICAL CYCLONES OVER THE WESTERN NORTH PACIFIC AND LANDFALLING IN CHINA BY REGCM4

This study evaluates the performance of the regional climate model RegCM4 in simulating tropical cyclone (TC) activities over the Western North Pacific (WNP) and their landfalling in China. The model is driven by ERA-Interim boundary conditions at a grid spacing of 25 km, with the simulation period as 1991–2010. Results show that RegCM4 performs well in capturing the main structural features of observed TCs, and in simulating the genesis number and annual cycle of the genesis. The model reproduces the general pattern of the observed TC tracks and occurrence frequency. However, significant underestimation of the occurrence frequency as well as the TC intensity is found. Number of the landfalling TCs over China is also much less than the observed. Bias of the model in reproducing the large-scale circulation pattern and steering flow may contribute to the underestimated landfalling TC numbers.     

The Relationship between Deterministic and Ensemble Mean Forecast Errors Revealed by Global and Local Attractor Radii

It has been demonstrated that ensemble mean forecasts, in the context of the sample mean, have higher forecasting skill than deterministic(or single) forecasts. However, few studies have focused on quantifying the relationship between their forecast errors, especially in individual prediction cases. Clarification of the characteristics of deterministic and ensemble mean forecasts from the perspective of attractors of dynamical systems has also rarely been involved. In this paper, two attractor statistics—namely, the global and local attractor radii(GAR and LAR, respectively)—are applied to reveal the relationship between deterministic and ensemble mean forecast errors. The practical forecast experiments are implemented in a perfect model scenario with the Lorenz96 model as the numerical results for verification. The sample mean errors of deterministic and ensemble mean forecasts can be expressed by GAR and LAR, respectively, and their ratio is found to approach2~(1/2) with lead time. Meanwhile, the LAR can provide the expected ratio of the ensemble mean and deterministic forecast errors in individual cases.     

利用FY-2F快速扫描资料分析对流初生阶段的云顶物理量特征

基于FY-2F静止气象卫星提供的2015年5—9月的高分辨率数据,通过温度阈值法识别出深、浅对流后,分析和比较了深、浅对流在对流初生(convective initiation,CI)至发展阶段中云顶高度、云顶快速降温率(cloud top cooling rate,CTC)以及多通道差值等云顶物理量特征的变化异同。结果表明:深、浅对流在CI阶段的云顶物理量特征具有相似变化特征,即云顶高度均在短时间内快速上升,CTC值均先减小后增大;深、浅对流差异表现为深(浅)对流云顶上升高度能(不能)超越水汽层高度;深对流CTC最低值较浅对流CTC最低值更低。基于CI阶段深、浅对流的CTC最低值的差异,通过个例验证,表明利用深、浅对流CTC最低值的差异,可以在识别出CI的基础,判断出CI是否发展成为深对流,从而能提前做出预警。     

2018年一次罕见早春飑线大风过程演变和机理分析

2018年3月4—5日,华南、江南等地发生了一次大范围强对流过程,发生时间早,落区范围广,多地伴有雷暴大风、冰雹、短时强降水等剧烈对流天气,尤其飑线在江西境内造成了严重大风灾害。基于大气环流和雷达回波发展演变特征,将该次过程分为初始、发展和减弱三个阶段：初始阶段西风槽前西南急流造成的低压倒槽为强对流提供大尺度触发条件;发展阶段对流活动位于槽前暖区中,飑线在江西造成极端大风;入夜后,冷锋南下,对流进入减弱阶段。环境场及对流参数诊断表明江西中北部低层高温高湿,中层干冷,温度垂直递减率大,有利于产生雷暴大风。南昌探空长时间序列分析表明温湿要素气候态异常,与历史同期比,低层明显偏暖偏湿,中层偏干,有利于极端对流天气发生。综合多源观测资料和雷达资料分析中小尺度特征,本次江西飑线过程特点及成因包括：（1）受引导气流和前向传播共同作用,飑线移动速度快。（2）自动站分析显示飑锋后雷暴高压强,与锋前暖低压作用造成强密度流,有利于产生大范围直线型大风;（3）通过对比飑线弓状回波南北段回波结构差异表明,飑线后侧中层干后向入流促使降水粒子相变,剧烈降温形成的强下沉运动(下击暴流)是导致极端大风的主要原因,后部层云区下沉气流增强雷暴高压加之动量下传作用对雷暴大风有增幅作用。     

基于镜像图的LRC和CRC偏差结合的人脸识别

为了提高人脸识别率及更好地显示人脸特征,本文提出了一种基于镜像图的LRC和CRC偏差结合的人脸识别方法.该方法首先生成一种镜像人脸,再通过融合原始人脸和镜像人脸形成新的混合训练样本,最后利用LRC和CRC偏差结合进行人脸识别.新方法增加了训练样本的数目,克服了由于光照和姿态等外部因素带来的影响.实验结果表明,镜像图与LRC和CRC偏差结合的人脸识别方法提高了人脸识别的准确性.     

2016—2017年贵州大雾时空分布及气象要素演变分析

利用2016—2017年自动站逐小时观测资料,统计分析了贵州大雾天气的时空分布特征;同时,结合天气图资料分析筛选了锋面大雾个例31 d和辐射大雾个例17 d,对比分析大雾生消过程中风、温、湿等气象要素演变特点。结果表明：(1)贵州大雾在秋末到初春较为频发;一天中夜间02—09时是大雾频发时段,07时达到峰值。(2)贵州自西向东有4个多雾区,分别为西南部区域、中部区域、东部边缘区域和北部局部区域。(3)锋面大雾主要出现在贵州中西部,范围最广时可达20个县站左右,持续时长可达10~13 h,单站可持续60 h以上。辐射大雾以贵州中东部地区出现较多,范围最广时可接近40个县站,远比锋面大雾范围广,持续时间相对较短。(4)大雾期间,10 min平均风速为0~3 m?s-1,相对湿度为97%~100%,温度露点差为0~0.5℃;辐射大雾初期或形成前气温呈下降状态,消散期升温较明显,地气温差呈现由负到正或由低到高的变化趋势,反映出近地层大气由较为稳定的逆温环境向不稳定环境变化的过程;锋面大雾初期的降温和后期的升温现象并不突出,地气温差也没有特定的变化规律,仅有部分个例与锋面大雾情况一致。