高时空分辨率三维风场在强对流天气临近预报中的融合应用研究

以业务应用为目标,开展高时、空分辨率三维风场在强对流天气临近预报中的融合应用研究。运用北京快速更新多尺度分析和预报系统集成子系统（RMAPS-IN,Rapid-refresh Multi-scale Analysis and Prediction System-Integration）,对雷达四维变分分析系统（VDRAS）30 min临近预报的高时、空分辨率三维风场作为数据源与自动气象站风场观测进行快速融合处理。结果表明,以VDRAS临近预报风场取代数值模式预报场作为融合初猜场后形成的分析结果对于风场有明显的改善:（1）长时间序列客观检验结果表明,地面10 m高风场U/V分量绝对误差分别为0.05和0.06 m/s。实时融合对未来预报的影响随着预报时效的延长,U/V分量的绝对误差不断增大。（2）对于11个强对流个例,地面10 m高风场风速均方根误差降低0.3 m/s,风向均方根误差降低13°;边界层三维风场,风速均方根误差降低0.8 m/s,风向均方根误差降低10°。平原站点融合以后风速、风向预报效果有较大改善,山区站点融合以后改善相对较小。（3）通过对2017年7月20日暴雨和7月7日雷暴大风个例的详细分析,发现融合基于雷达资料四维变分同化获得的高分辨率临近预报风场对各对流系统中的中尺度结构特征给出了更加细致准确的描述。      

人工智能在冰雹识别及临近预报中的初步应用

基于广东10部S波段多普勒天气雷达的三维拼图资料,利用机器学习技术开发了一种冰雹识别和临近预报的人工智能算法。算法设计时以雷达回波反射率的垂直和水平扫描数据为基础训练集,将冰雹云的雷达反射率扫描数据作为正样本,将其他雷达反射率扫描数据作为负样本,通过贝叶斯分类法对正、负样本数据集进行机器学习,训练人工智能识别冰雹云内在规律的能力。训练时以广东省2008-2013和2015-2016年的数据作为训练集,使用了2014年广东省12次冰雹过程的数据做检验。对比检验的结果表明,人工智能法比传统的概念模型法击中率高9个百分点。研究结果表明了人工智能对冰雹这类非线性强天气过程具有较强的识别能力。      

基于深度学习的天气雷达回波序列外推及效果分析

天气雷达探测资料是进行强对流天气临近预报的主要参考数据。针对传统雷达回波外推方法中存在资料信息利用率不足和外推时效有限的问题,文中利用神经网络进行雷达回波的外推、利用预测神经网络模型进行2 h以内的回波变化预报。回波外推问题的关键是回波时、空序列预测问题,该网络具有解决时间记忆问题的长、短时记忆单元（Long Short-Term Memory,LSTM）和提取空间特征的卷积模块。应用福建、江苏和河南多年的雷达探测资料构造训练和测试数据集。为消除降水的不平衡和提高对强回波的预报准确率,网络采用带权重的损失函数进行训练。对光流法和预测神经网络进行测试集检验以及个例分析,结果表明,在相同外推时效和检验反射率阈值的情况下,预测神经网络的临界成功指数、命中率均高于光流法,虚警率低于光流法。不同类型降水预测神经网络的SSIM值（structural similarity）均高于光流法,且层状云降水的SSIM值比对流云降水的大。因此,预测神经网络对强回波的预报能力高于光流法;在预报时效性上,预测神经网络模型具有一定的优越性;预测神经网络对层状云降水预报的准确率比对流云降水的高。      

循环同化雷达资料对一次飑线系统临近预报的改进作用

利用WRF（Weather Research Forecast）模式及其3D-Var（Three-Dimensional Variational assimilation）变分系统,针对2017年7月7日一次飑线进行了雷达资料的循环同化敏感性试验。结果表明：以循环同化雷达资料至飑线成熟期时刻的试验预报效果最好,主要原因在于预报的低层西北冷空气较强,从而导致较强的低层切变,再配合强的热力不稳定条件从而使飑线的发展得以维持。通过七组试验对比表明,对于单次雷达资料,同化的时机更为重要。同化飑线成熟阶段的雷达反射率,对低层热力层结有改善作用,为飑线发展提供了不稳定能量;对于循环同化,通过观测的影响和模式自身的热动力调整,对流场也有较好的修正作用,为对流系统的持续发展提供了充分的动力条件。     

北京及周边地区雷暴阵风锋特征统计分析

为全面和系统研究北京及周边地区阵风锋各方面特征,使用2006—2015年暖季（5—9月）北京多普勒雷达探测资料及北京、河北、天津自动气象站观测资料对北京及周边地区的阵风锋过程进行综合统计分析。结果表明,346次阵风锋过程有232次触发了对流,占总数的67%,表明阵风锋对雷暴具有较强的抬升触发能力。阵风锋在6—8月出现的日数占5—9月阵风锋总日数的85%;出现的时段主要是午后至傍晚（12—21时,北京时）,维持时间0.5—3 h;阵风锋在北京东南方向生成的数量最多,且触发对流的次数也最多;其次为偏东和东北方向;偏南和西南方向生成阵风锋数量居中,而偏北、偏西和西北地区阵风锋个例相对较少,触发对流的比例也相对较低。产生阵风锋的母风暴中48%为孤立雷暴（包括孤立多单体和超级单体风暴）,31%为雷暴群,21%为飑线;97%的母风暴最强回波在50 dBz以上,阵风锋的回波强度为10—25 dBz。91%的阵风锋移动速度集中在10—60 km/h,84%的阵风锋与母风暴的最大距离为1—60 km;在母风暴回波强度减弱到30 dBz以下时,80%的阵风锋能够继续维持的时间不超过2 h。阵风锋母风暴向东南方向移动的个例最多,从阵风锋和母风暴移动方向的关系来看,阵风锋与母风暴移向一致的情况占比最高,为32%,其次为母风暴无移动及阵风锋弧形扩散情况,各占17%;阵风锋与母风暴移向相反情况所占比例最低,只有3%。最后统计了阵风锋经过地面自动气象站时,自动观测量的变化情况。结果显示,阵风锋在经过地面自动气象站时会造成风速增大、温度降低、相对湿度增大、气压升高。      

梅汛期区域性暴雨的多尺度分析及临近预警

利用常规观测数据、NECP1°×1°逐6 h再分析资料、FY2E卫星黑体亮度温度TBB资料以及南京、常州多普勒天气雷达产品,对2012年江苏出梅之前的最后一场区域性暴雨过程进行多尺度分析。在此基础上,探索该类暴雨的临近预警线索,结果表明:(1)此次过程的雨带呈准纬向分布,属于典型的梅汛期静止锋降水。过程中主要有两次降水集中时段,两个阶段的降水性质存在差异,但都具备较高的降水效率。(2)中高纬大范围稳定的阻塞形势,为此次持续性暴雨过程的产生提供了有利的大尺度环流背景。而在此过程中,两段降水集中期的形成与地面触发系统的出现和维持有着较为密切的联系。(3)此次过程中两段降水集中期内的物理量特征以及TBB的演变情况和其对应的降水特征存在异同。(4)雷达特征分析表明,此次过程具有较高的降水效率和较长的持续时间。实际业务工作中可以通过判断回波的质心高度和边界层风速有无跃增来估计降水效率的潜势。当推断较高的降水效率潜势将持续较长时间时,应及时发布暴雨警报。     

SWAN2.0系统的设计与实现

强对流天气短时临近预报系统（Severe Weather Automatic Nowcasting,SWAN）是面向短时临近监测、分析、预报、预警制作等功能为一体的业务平台。SWAN2.0基于MICAPS4（Meteorological Information Comprehensive Analysis and Processing System Version 4.0,人机交互气象信息处理和天气预报制作系统）二次开发框架,采用C/S架构,服务器部署在省级,负责收集数据,运算SWAN产品;客户端部署在气象台站,实现具体的预报业务,并形成算法二次开发接口。SWAN2.0新增了三维变分风场反演、基于分雨团技术的雷达降水估测、冰雹识别等方法,实现了算法管理、产品生成、分析处理、资料检索显示、实时监控报警、预警产品制作等功能。SWAN2.0业务系统已在全国试用,在强对流天气监测、分析和短时临近预报预警中发挥了重要作用。     

Diagnostic analyses of convective events — The effect of propagating gust fronts

This paper is devoted to the testing experiment of a postprocessing tool aimed at the objective analysis of propagating gust fronts in a given convective environment. The tool is being developed to be applicable in the operational mode by utilizing NWP model outputs. The experiment was carried out on two summer convective cases which occurred in the Czech Republic. The cases were numerically simulated by the limited area NWP model LM COSMO with the horizontal resolution of 2.8 km. They represent different types of convective systems, both accompanied by objectively identifiable gust fronts and causing heavy precipitation. The event from July 2000 was characterised by the development of isolated thunderstorms. The other event from July 1998 was a long-lasting and organised convective system — a squall line. The hypothesis was that the developed postprocessing tool is capable to evaluate the role which downdraft outflows played in the decay and initiation of convective cells by interaction with convective environment and thus in prolongation of convection lifetime.The procedures of the Objective Analysis of Gust Fronts (OAGF) were applied to the thermodynamic outputs of the LM COSMO. The aim was to determine the position of gust fronts within the domain and to assess their speed of movement and the potential to initiate convection according to the properties of ambient vertical shear and stability as well as humidity conditions ahead of the respective downdraft outflows. In addition, the Radar Simulation Model (RSM) was employed to monitor the simulated convective systems in arbitrary PPI and RHI scans and to verify qualitatively the LM COSMO precipitation forecasts.The case studies has confirmed the applicability of the LM COSMO–OAGF chain and RSM, which may represent the potential for improving the operational nowcasting of hazardous convection phenomena. In both simulations, the objective gust fronts moved on into the vertical shear-favourable environment for triggering new convection. In addition to the dynamical organisation, there were also favourable stability and humidity conditions in the area of forced upward motions in the simulation of the event from July 2000.     

Development and behaviour of a radar-based operational tool for hailstorms identification

Hailstorms are a common meteorological phenomenon in Spain which causes substantial economic damage especially in spring and summer. During 2000 and 2001, a radar-based application for convective monitoring was developed at STAP (Forecasting and Analysis Techniques Department); in order to improve this nowcasting tool, it is needed to include an advanced procedure to estimate the presence of hail as a complementary module in the operational application. A preliminary study, carried out during 2001, showed that the Waldvogel technique, VIL (vertical integrated liquid) density and the hail detection algorithm (HDA) are the methodologies which proved more accurate in our latitudes.Throughout the spring and summer of 2001, all available information about hail events (time, place and hail size) and about storms without hail was used for tuning an experimental module to detect severe and non-severe hailstorms, taking into account the selected algorithms. During 2002, further information about storms was gathered in order to assess the behaviour of the developed hail module. Afterwards, a new module calibration was carried out with the information of the complete storms data set of 2001 and 2002. With this new calibration, the hail module became an operational tool during the spring and summer of 2003. Currently, the verification of the operational module using the data from the storms in 2003 is being elaborated. The aim of this work is to put forward the calibration procedure carried out, the verification results of 2002, and the performance of the hail estimate module in selected cases during 2003 in Spain.     

沪宁高速公路无锡段春季浓雾的实时监测和若干特征

20 0 0年 2月到 4月沪宁高速公路 ,共监测到 7次低能见度 (<2 0 0m)的春雾。本文应用环境气象监测仪AMW自动气象站 ,每分钟实测的有关资料和相应的环流背景场 ,对 7次春雾形成的物理过程作了研究分析。揭示了春雾形成过程中的若干特征和设计了实施临近预报制作的思路、流程。并论述了在高速公路沿线布设AMW自动气象监测仪的基础上作出低能见度的预测是可行和可能的