A Deep Learning Approach for Forecasting Thunderstorm Gusts in the Beijing–Tianjin–Hebei Region

Thunderstorm gusts are a common form of severe convective weather in the warm season in North China,and it is of great importance to correctly forecast them.At present,the forecasting of thunderstorm gusts is mainly based on traditional subjective methods,which fails to achieve high-resolution and high-frequency gridded forecasts based on multiple observation sources.In this paper,we propose a deep learning method called Thunderstorm Gusts TransU-net(TGTransUnet)to forecast thunderstorm gusts in North China based on multi-source gridded product data from the Institute of Urban Meteorology(IUM)with a lead time of 1 to 6 h.To determine the specific range of thunderstorm gusts,we combine three meteorological variables:radar reflectivity factor,lightning location,and 1-h maximum instantaneous wind speed from automatic weather stations(AWSs),and obtain a reasonable ground truth of thunderstorm gusts.Then,we transform the forecasting problem into an image-to-image problem in deep learning under the TG-TransUnet architecture,which is based on convolutional neural networks and a transformer.The analysis and forecast data of the enriched multi-source gridded comprehensive forecasting system for the period 2021–23 are then used as training,validation,and testing datasets.Finally,the performance of TG-TransUnet is compared with other methods.The results show that TG-TransUnet has the best prediction results at 1–6 h.The IUM is currently using this model to support the forecasting of thunderstorm gusts in North China.

Seasonal Variability of Rainfall and Thunderstorm Patterns in Kenya

This paper presents an analysis of spatial and temporal variation of rainfall and thunderstorm occurrence over Ken-ya from January 1987 to December 2017.The meteorological data used were obtained from the Kenya Meteorological Department(KMD)for the same period.This included the monthly thunderstorm occurrences and rainfall amounts of 26 synoptic stations across the country.The characteristics of monthly,seasonal and annual frequency results were presented on spatial maps while Time series graphs were used to display the pattern for annual cycle,seasonal varia-tions and the inter-annual variability of rainfall amounts and thunderstorm occurrences.A well-known non-parametric statistical method Mann Kendall(MK)trend test was used to determine and compare the statistical significance of the trends.Thunderstorm frequencies over the Eastern,Central and Coast regions of the country showed a bimodal pattern with high frequencies coinciding with March-April-May(MAM)and October-November-December(OND)rainy sea-sons.Very few thunderstorm days were detected over June-July-August(JJA)season.The areas to the western part of the country,near Lake Victoria,had the highest thunderstorm frequencies in the country over the three seasons:MAM,JJAS and OND.The annual frequency showed a quasi-unimodal pattern.These places near Lake Victoria showed sig-nificantly increasing thunderstorm trends during the MAM and OND seasons irrespective of the rainfall trends.This shows the effects of Lake Victoria over these areas,and it acts as a continuous source of moisture for thunderstorm for-mation.However,most stations across the country showed a reducing trend of thunderstorm frequency during MAM and JJA seasons.The importance of these findings is that they could support various policy makers,and users of cli-mate information,especially in the agriculture and aviation industries.

Radio-Acoustic Study of Thunderstorms

The observation, in the past, that a thunderstorm perturbed the transmissions of an old vacuum tubes radio with noise discharges in correspondence with lightnings, suggested the possibility of radio-acoustic study of thunderstorms. The noise discharges appeared to convey not only information about lightnings, but also about any other thunderstorm electromagnetic phenomena generating noise discharges. The low-cost instrumentation involved in the radio-acoustic study, comprised a radio Telefunken mod. T33B, a 15 m long indoor wire antenna, a mobile telephone Samsung Galaxy S20 FE 5G provided with the recorder App Enregistreur vocal, a computer HP Pavillion dv5-1254eg and the s/w audio analyser Audacity. A first thunderstorm on 20 June 2023 and a second thunderstorm on 22 June 2023, both above Munich, were radio-acoustic studied. The second thunderstorm was more active than the first and released much more energy.

Thunderstorm and Lightning Activities over Western Pacific,Northern Indian Ocean and South China Sea Along with Their Adjacent Lands

The Lightning Imaging Sensor(LIS)and Radar Precipitation Feature(RPF)data are used to investigate the activities and properties of lightning and thunderstorms over a region including the Western Pacific,northern Indian Ocean and the South China Sea along with their adjacent lands.The lands feature significantly more frequent lightning flashes and thunderstorms than the oceans,especially the open oceans.The highest densities of lightning and thunderstorm occur over the Strait of Malacca and the southern foothills of the Himalayas.Over the ocean regions,the Bay of Bengal and the South China Sea are characterized by relatively frequent lightning and thunderstorm activities.Larger average spatiotemporal size and optical radiance of flashes can be found over the oceans;specifically,the offshore area features the most significant flash duration,and the open ocean area is characterized by the greatest flash length and optical radiance.The smallest average values of flash properties can be found over and around the Tibetan Plateau(TP).The oceanic thunderstorms tend to have a significantly larger horizontal extent than the continental thunderstorms,with the former and latter having the average area of the regions with radar reflectivity larger than 20 dBZ,generally over 7000 km^(2) and commonly below 6000 km^(2),respectively.The TP thunderstorms show the smallest horizontal extent.Meanwhile,the oceanic thunderstorms exhibit greater 20 dBZ but smaller 40 dBZ top heights than the continental thunderstorms.The average flash frequency and density of the oceanic thunderstorms are typically less than 5 fl min^(-1) and 0.3 fl 100 km^(-2) min^(-1),respectively;in contrast,the corresponding values of continental thunderstorms are greater.It is explored that the regions associated with strong convective thunderstorms are more likely to feature small-horizontal-extent and low-radiance flashes.

Prediction-Based Thunderstorm Path Recovery Method Using CNN-BiLSTM

The loss of three-dimensional atmospheric electric field(3DAEF)data has a negative impact on thunderstorm detection.This paper proposes a method for thunderstorm point charge path recovery.Based on the relation-ship between a point charge and 3DAEF,we derive corresponding localization formulae by establishing a point charge localization model.Generally,point charge movement paths are obtained after fitting time series localization results.However,AEF data losses make it difficult to fit and visualize paths.Therefore,using available AEF data without loss as input,we design a hybrid model combining the convolutional neural network(CNN)and bi-directional long short-term memory(BiLSTM)to predict and recover the lost AEF.As paths are not present during sunny weather,we propose an extreme gradient boosting(XGBoost)model combined with a stacked autoencoder(SAE)to further determine the weather conditions of the recovered AEF.Specifically,historical AEF data of known weathers are input into SAE-XGBoost to obtain the distribution of predicted values(PVs).With threshold adjustments to reduce the negative effects of invalid PVs on SAE-XGBoost,PV intervals corresponding to different weathers are acquired.The recovered AEF is then input into the fixed SAE-XGBoost model.Whether paths need to be fitted is determined by the interval to which the output PV belongs.The results confirm that the proposed method can effectively recover point charge paths,with a maximum path deviation of approximately 0.018 km and a determination coefficient of 94.17%.This method provides a valid reference for visual thunderstorm monitoring.

我国大气电学研究的最新进展

大气电学主要研究地球大气和近地空间发生的电学过程及其机理和影响,其核心研究内容是雷电物理和雷暴电学。自1980年代以来,中国大气电学研究不断取得新的进展,特别是近年来,得益于高时间分辨率雷电探测技术的进步,大气电学研究不仅在雷电物理学和雷暴云电荷结构方面取得了重要成果,也在雷电和雷暴对近地空间的影响、强对流天气的雷电特征、以及雷电资料同化和预警预报等方面取得了重要进展。本文从六个方面对近五年来大气电学的主要研究进展进行回顾,包括高精度雷电探测和定位技术、雷电物理过程和机制、雷暴对中上层大气的影响、雷暴云电荷结构的观测和数值模拟、强对流天气的雷电特征与预报、雷电对气候变化的影响与响应等,最后对大气电学未来发展进行展望。

Analysis of Continuous Thunderstorm in One Week at Qingdao Airport Based on Sounding Data

Continuous thunderstorm occurring at Qingdao Airport in China from August 7 to 13,2022 was analyzed based on sounding data.The weather was divided into thunderstorm gale,thunderstorm and heavy precipitation,and some physical quantities and time variables which can effectively identify severe convective weather types were preliminarily obtained.The results show that CAPE was sensitive to different types of weather,but the uncertainty was relatively large.Convective temperature T_(CON),temperature difference between 500 and 850 hPa,and vertical wind shear can distinguish thunderstorm gale,thunderstorm and heavy precipitation weather obviously.Besides,K index,Showalter index,θ_(se) difference between 500 and 850 hPa were also important basis to distinguish thunderstorm and heavy precipitation weather.Thunderstorm gale can be distinguished by the 24-hour variations of K index,and the difference of dew point between 500 and 850 hPa.The 24-hour variations of(T-T_(d))_(500) and vertical wind shear can be used to distinguish between heavy precipitation and thunderstorm weather;the 24-hour variation of stratification stability Δθ_(se) can distinguish the three kinds of weather well.For the wind field,the existence of vertical wind shear was required for strong convective weather,and the 24-hour increment of thunderstorm gale and thunderstorm was larger than that of heavy precipitation.

基于模式物理量参数的云南雷暴大风概率预报技术研究

利用2019—2021年云南125个国家站大风数据和云南省地闪资料,统计云南雷暴大风个例,并挑选对雷暴大风有重要意义的物理量参数,结合NCEP再分析资料确定云南雷暴大风个例的物理量阈值,再基于ECMWF数值模式预报产品及确定的阈值,采用二分法进行云南雷暴大风概率预报。结果表明:在云南三次雷暴大风过程预报检验中,8月4日云南中部及东北部雷暴大风均命中,但在云南西部及西南部出现大范围的虚警,导致此次过程虚警率较高和临界成功指数较低;8月5日云南中部、东北及西北部雷暴大风预报正确,且云南西部及南部虚警范围小,虚警率较8月4日明显降低;7月7日云南自东北向西南出现大范围的雷暴大风天气过程,雷暴大风预报落区与实况基本吻合,呈现命中率高、虚警率较低的特征;三次过程命中率、临界成功指数、虚警率平均为0.873、0.203、0.789。

湖北冷季高架雷暴天气分类及环境参数特征分析

利用常规观测资料、加密地面自动站、闪电定位仪和ERA5再分析资料,将2011—2020年湖北冷季91次高架雷暴事件,按照形成机制分为雷雨型、强对流型和雷打雪型3类,并细致归纳了3类事件的时空分布特征、大气环流背景及关键环境参数等特征。(1)湖北冷季高架雷暴雷雨型最多,强对流型次之,雷打雪型最少。3类型存在明显的时空分布差异,雷雨型主要发生在秋末冬初(11月)和冬末初春(1—2月),强对流型及雷打雪型常出现在早春2月,3月基本以强对流型为主。(2)低槽冷锋、850 hPa切变线及低空西南急流是冷季高架雷暴发生的有利环流背景,近地面为稳定的冷气团控制,逆温明显,西南低空急流沿着锋面逆温层以上的850 hPa附近触发抬升,水汽、上升运动及不稳定层结均出现在850 hPa以上。雷雨型和雷打雪型距离冷锋超过100 km以上,强对流型不足100 km。(3)850 hPa是风场转换的重要层次。强对流型850 hPa露点温度(T_(d850))、K指数、850 hPa与500 hPa温差(ΔT_(85))、850 hPa假相当位温(θ_(se850))、西南急流厚度和强度(I700)、切变线强度(S_(850))最大,中低层(850~700 hPa)垂直风切变(SL78)最小;雷打雪型对水汽和不稳定能量的要求最低,SL78最大。

基于高密度站点的四川复杂地形下大风特征分析

基于四川省2016—2021年4—9月大风事件和闪电资料,将大风类型分为雷暴大风和一般大风,统计分析了两类大风的时空分布特征及与地形因子的关系。结果表明:四川地区两类大风均呈现高原多、盆地少的特征,大风类型普遍以一般大风为主,盆地内部分站点雷暴大风占比较高。各个分区不同类型大风发生频次均存在日变化和月变化。对于风速,盆地南部大风更强,盆地东北部和攀西地区的雷暴大风次之。对于风向,川西高原一般大风以北风和西南风为主,雷暴大风以北风为主,攀西地区和盆地不同分区的两类大风均以北风和东北风为主。大风的发生频次和风速与不同地形因子有一定的关系,不同类型大风总体变化趋势类似。发生频次均随海拔高度的增大逐渐增大,随坡度、粗糙度和起伏度的增大先增大后减小。风速随海拔高度的增大而增大,随坡度增大先增大后减小,而粗糙度和起伏度越小,平均风速和最大风速越大。

Assessment of the Impacts of Thunderstorm on Flight Operations at Murtala Mohammed International Airport,Ikeja,Lagos State,Nigeria

The inefficiency of the aviation industry and the persistent rise in aviation hazards have been linked to weather phenomena.As a result,researchers are looking for better solutions to the problem.The study examined the impact of thunderstorms on flight operations at Murtala Mohammed International Airport,Lagos.The data on thunderstorms and flight operations were sourced from Nigerian Meteorological Agency(NiMet)and Nigerian Airspace Management Agency(NAMA)respectively.In order to meet the research target,descriptive statistics(mean,standard deviation,and charts)and inferential statistics(Pearson’s Product Moment Correlation(PPMC)and Regression)were used.The significance level for all inferential analyses was set at 5%(0.05).The study revealed that 77.4%of thunderstorms occurred during the rainy season(April-October)while 22.6%occurred during the dry season(November-March).It also revealed some fluctuating movements of a thunderstorm in the study area.According to the findings,thunderstorms occur most frequently at the airport in June and less frequently in January and December.The study also discovered that thunderstorms at the airport are positively and significantly related to flight delays and cancellations,while the association between flight diversions and thunderstorm occurrence is positive but statistically insignificant.Furthermore,flight delays,flight diversions,and flight cancellations interact positively among themselves.The regression result of the study revealed that a 1%increase in thunderstorm occurrence leads to a 19.4%increase in flight delay,a 7.1%increase in flight cancellation,and a 4.3%increase in flight diversion.As a result,the study presented various regression models that may be utilized to make predictions.The study proposes consistent thunderstorm observation at the airport and steady forecasts using the regression models,based on the findings.However,it further recommends that pilots,air traffic controllers,and meteorologists be trained and retrained so that they can provide better and more efficient services.

2023年3月河南省一次极端暴雪和雷电天气成因分析

选用自动气象站、双偏振雷达、风廓线雷达和ERA5再分析等资料,分析2023年3月16日河南省一次极端暴雪和雷电天气成因。结果表明:此次极端暴雪过程主要天气系统为低槽、切变线、急流以及东北冷涡。冷涡配合-39℃冷中心稳定维持,其后部冷空气持续南下,850 hPa以下形成深厚冷垫,中高层西南暖湿气流沿冷垫爬升,形成河南省典型的降雪天气类型“天南地北型”。此次强降雪区位于整层大气可降水量大于20 mm区域的北部与700 hPa强辐合中心重叠的区域,河南中西部地形的抬升作用利于此极端降雪天气发生。冷平流与其次级环流共同作用,使局地气温骤降,导致降水相态转换较预期提前,以致多站降雪量或积雪深度超历史极值。双偏振雷达零滞后相关系数产品(CC)为相态转换监测提供了重要参考。850 hPa以下大气温度均低于0℃,且2 m气温降至1℃左右,可作为降雪预报指标。辐合切变及锋面次级环流有利于高架雷暴天气出现,20 dBz回波高度超过-20℃层高度可作为产生雷暴的关键指标。

机载双极化气象雷达雷暴回波仿真与验证

雷暴是一种短暂而剧烈的强对流天气,常伴有闪电、冰雹、强降水等危险天气,对民航飞机的飞行安全造成巨大威胁。机载气象雷达作为保证飞行器飞行安全必备的装备,用于探测与显示航路附近的实时气象信息,辅助机组人员规避危险气象。由于极化技术在气象探测方面的优势,双极化雷达成为机载气象雷达的发展方向。但是雷暴天气具有发展迅速、变化复杂,危险性高等特点,使得获取实测机载双极化气象雷达雷暴回波数据困难。为了解决这一问题,本文基于机载双极化气象雷达提出一种雷暴回波仿真方法并进行验证。方法首先利用数值预报模式WRF模式(Weather Research and Forecasting)对雷暴气象场景进行模拟;然后使用T-Matrix方法计算气象粒子的单个粒子散射振幅矩阵,同时结合场景内粒子的微物理特性,计算雷暴目标的反射率因子;最后应用雷达气象方程,基于机载气象雷达系统参数建立雷暴回波信号模型,实现机载双极化气象雷达雷暴回波信号仿真。最后,为检验方法的正确性和准确性,基于雷暴单体识别算法对回波仿真结果进行验证。通过仿真不同仰角下雷暴回波,实验结果表明,基于WRF模式的机载双极化气象雷暴回波仿真方法对雷暴天气具有良好的模拟能力,经单体识别算法验证,结果表明可准确体现雷暴单元的质心分布,结构属性和立体特征,对比实测数据,雷暴回波仿真结果与实测数据相吻合,实验结果具有真实性和准确性。

《雷雨》复数故事系统的生成及意义指向

话剧《雷雨》中有一个在时间和空间上层层叠叠的故事系统。其生成涉及从“五四”到20世纪30年代社会文化生活的多个层面,如个性解放、阶级斗争、文化时尚、旧家庭的恶习残留和人性错乱等。这些故事源头复杂,既涉及中西文化传统,也涉及时代语境。作家曹禺在讲述这些故事的时候,运用三角恋爱叙事、家庭戏、法庭审判叙事、戏剧巧合、人物身份背景模糊化、年龄漏洞和互文等方式,将本来散乱在不同历史阶段和当时社会各个层面的文化现象,在“家庭”格局下,收集、整理、剪辑、连缀、凝聚为一个以双重乱伦故事为树干,以其他故事为枝杈的层次丰富的故事树。这个复杂的故事树及其折叠艺术,所体现的伦理指向是复杂暧昧的,并远远逸出创作主体的把控。

东北冷涡背景下三类区域性强对流天气过程时空分布和环境特征对比分析

东北冷涡是造成中国暖季强对流的重要天气尺度系统之一。为对比东北冷涡与不同类型强对流过程的时空关系及其环境特征差异,基于欧洲中期天气预报中心第5代大气再分析数据和中国国家气象信息中心提供的逐时大风、降水观测资料,筛选了2017—2021年4—9月东北冷涡背景下9例雷暴大风型、9例强降水型以及8例混合型强对流天气过程,通过动态合成开展了分析研究。结果表明:(1)三类强天气过程相对于冷涡的时空分布差异明显:雷暴大风型过程,超过70%的雷暴大风出现在冷涡中心的西南部或南部;而混合型过程,超过70%的大风出现在冷涡中心的东南部或南部;混合型和强降水型过程中,短时强降水均主要出现在冷涡中心南部或东南部,但后者发生在冷涡东南部的比例更高;雷暴大风型和强降水型过程主要出现在东北冷涡的发展和成熟阶段,而混合型过程主要发生在东北冷涡的成熟阶段。(2)三类强天气过程的环流形势和环境条件差异显著。雷暴大风型过程多出现在5—6月,一般对应的东北冷涡更深厚,等温线更密集,大气环境偏干,存在气温垂直递减率大和强风垂直切变条件,雷暴大风多发生在冷涡南侧的锋区附近,对流层中、高层受干冷空气控制,叠加在低层比较浅薄的暖湿空气之上有利于大气层结条件不稳定的增强,降水粒子蒸发降温形成的下沉气流和地面冷池,叠加锋区辐合更有利于形成区域性地面强风;而强降水型过程多集中在7—8月,对应的东北冷涡强度较弱,等温线较稀疏,强降水一般出现在锋前靠近暖区一侧的强层结不稳定区域内,对应水汽充沛、整层暖湿的环境条件,中低层温差较小,风垂直切变较弱。混合型过程对应的月份和冷涡强度与强降水型过程更接近,水汽、高低层温差以及风垂直切变等环境条件介于上述两类过程之间,但下沉对流有效位能在三类过程中表现为最大。总体来看,相较于中国中、低海拔地区雷暴大风和短时强降水的环境特征而言,东北冷涡背景下的强天气过程对应更强的深层风垂直切变,具有更强的天气尺度动力强迫。

江苏雷暴大风双偏振雷达特征统计分析

利用双偏振雷达、地面自动站、闪电定位仪、探空等资料对江苏2012—2022年262次雷暴大风过程的环境参数和2020—2022年41个导致雷暴大风的对流风暴演变特征进行分析。结果表明:(1)雷暴大风发生在大气层结不稳定背景下,850 h Pa和500 h Pa温差中位数超过25°C,对流层中层存在干层;春季动力条件较好,0~6km垂直风切变中位数达到18.4 m·s^(-1),是夏季的2倍;夏季能量条件较好,CAPE平均值可达2 491.0 J·kg^(-1),而春季仅为977.5 J·kg^(-1)。(2)凝练和定量验证了基于双偏振特征量的雷暴大风风暴演变的概念模型:对流风暴的生命史分为3个阶段,初生阶段存在较强的Z_(DR)柱,Z和K_(DP)较弱且未及地;发展阶段K_(DP)柱显著增强,Z_(DR)柱稍有减弱;雷暴大风发生阶段Z、Z_(DR)和K_(DP)核心高度均明显降低。因此,较强的Z_(DR)柱,并伴随显著增强的K_(DP)柱是雷暴大风发生的前兆信号。(3)统计获得双偏振特征量预警指标:初生阶段和发展阶段多数分别发生在雷暴大风发生前60 min和前20 min;在0~2 km的高度上,3~4 d B的Z_(DR)大值区提前10~15 min到达雷暴大风站点。

播撒碘化银人工消雹对冰雹云微物理过程和起放电过程影响的数值模拟研究

为了全面了解人工消雹对云中冰相粒子的浓度和时空变化以及冰雹云微物理过程和起放电的影响,本文利用包含了AgI催化方案的三维强风暴动力电耦合数值模式,以AgI播撒量为唯一变化量进行了多组模拟实验。结果表明,催化过后,整体上,-40~0℃范围内的冰晶、雪花和霰粒子数浓度和比含水量增多。播撒AgI使霰的平均尺度减小,向雹的转化比例大为降低,因此冰雹的比含水量和浓度都减小。随着AgI播撒剂量的增加,冰晶、雪花和霰粒子的数浓度和比含量整体变化趋势不变,增大与减小区域相对应,但变化更明显;消雹效果会更好,但降雨量呈先增加后减小。播撒AgI会使冰雹云前期正的非感应起电率区出现时间提前,中心增强,上界高度抬升,后期负的非感应起电率区中心增强。所以,播撒后前期主要使底部次正电荷区增强,后期主要使上方主正电荷区和中部负电荷区增强。随着催化剂量增多,这些变化越明显。播撒AgI对地闪有一定的抑制作用,而使云闪和总闪少量增多,首次放电和云闪的峰值时间提前,放电持续性更强,闪电频发时段的闪电频率略有降低。

河南一次伴有龙卷的多阶段强对流天气形成机制分析

利用常规观测资料以及区域自动站、卫星、新一代天气雷达和ERA5再分析等高时空分辨率资料,对2022年6月13日河南一次伴有局地龙卷的多阶段强对流过程(以下简称“6.13”过程)的环流形势、中尺度系统演变特征进行了分析,并探讨了该过程不同阶段对流触发维持机制以及濮阳局地龙卷的雷达监测特征。结果表明:(1)这次东北冷涡槽后西北气流形势下大范围强对流天气具有影响范围广、持续时间长、灾害天气种类多的特点。(2)雷达监测到该过程强对流系统分3个阶段相继经过河南,各阶段强回波均持续8~9 h,移速30~50 km·h^(-1),强对流系统以多单体为主,受西北气流引导自西北向东南方向移动且落区有重叠。(3)河南上空始终维持强条件不稳定层结和中等到强的垂直风切变是“6.13”过程多阶段强对流天气长时间维持的重要原因。第一阶段河南本地强对流主要是由风场日变化、局地冷空气活动和地形分布共同作用形成的边界层辐合线或辐合中心触发;第二、三阶段强对流则由前期或同期周边区域强烈发展的地面中尺度雷暴高压伴随的阵风锋(出流边界)触发。(4)濮阳县局地龙卷由发展迅速的超级单体产生,该单体回波生成后12 min出现钩状回波和中尺度气旋性涡旋、18 min出现龙卷涡旋特征(TVS),且钩状回波和中尺度气旋性涡旋较龙卷发生有6 min的提前量。

廊坊市雷暴大风多普勒雷达特征指标预警应用分析

利用北京、天津和沧州多普勒天气雷达对2010—2019年廊坊市发生的29次雷暴大风天气过程中的阵风锋、径向速度大值区、垂直累积液态水含量(VIL)≥40 kg·m^(-2)等预警指标进行验证分析,结果表明:51.9%的站次出现了阵风锋,其中61.0%的雷暴大风出现在主体回波移动前方中部到右侧;17 m·s^(-1)以上大风速区作为预警指标,预警的平均提前量达47.2 min。100%的弓形回波雷暴大风出现前上游及可能影响区域存在≥17 m·s^(-1)的大风速区,以此发布预警可提前37.1 min;71.4%的雷暴大风站点上空或10 km范围内VIL≥40 kg·m^(-2),平均预警提前量最高,达到52.7 min;依据带状回波前侧或右前侧出现阵风锋发布预警的平均提前量为60.6 min。73.7%的块状回波雷暴大风天气上游及可能影响区域有≥17 m·s^(-1)的大风速区。结合上游及可能影响区域≥17 m·s^(-1)和≥20 m·s^(-1)大风速区、阵风锋、VIL≥40 kg·m^(-2)出现位置可以提前30~60 min发布雷暴大风预警信号,且可更加精准地预测灾害性大风的落区、出现时间和强度。

雷达资料循环同化对2021年“4·30”南通雷暴大风模拟的影响研究

基于多普勒天气雷达资料、ERA5再分析资料与地面自动站观测资料,利用WRF(Weather Research and Forecasting)模式、雷达径向风质控及三维变分同化系统(GSI)循环同化对2021年4月30日江苏南通的一次雷暴大风过程进行数值模拟研究,对比分析不同试验方案模拟的雷达反射率、风场与热动力的时空演变和结构特征。结果表明:逐30 min循环同化的Exp3方案较未同化和非临近循环同化方案模拟效果有较好提升,表明循环同化和增加频次有效改善了初始场;UNRAVEL退模糊算法质控有效消除了速度模糊,退模糊处理雷达资料后循环同化方案(Exp4)对此次雷暴大风的雷达反射率和地面风场模拟结果有显著调整,其相应特征和演变趋势与观测基本一致,表明UNRAVEL退模糊质控后循环同化更好的改善了初始场;从热动力场结果来看,Exp4方案动热力结构改善较明显,上层辐散下层辐合,存在“冷—暖—冷”的热动力结构,伴随着强烈上升运动、北高南低的气压分布和强垂直风切变,有助于下沉气流将中高层的水平动量向近地面底层传递,从而激发此次雷暴大风。