Distribution and Oceanic Dynamic Mechism of Precipitation Induced by Typhoon Lekima

Air-sea interaction usually affects the distribution of precipitation during typhoon period, but whether typhoon precipitation distribution is affected by ocean eddies is still unclear. In this study, based on a multi-source satellite database, reanalysis data and in-situ data were used to study the precipitation characteristics of Typhoon Lekima (2019) as well as its physical causes. The results showed that the precipitation of Lekima presents an asymmetric structure, exhibiting heavier precipitation on the left side of the typhoon path before 7 August, and with the typhoon strengthened, precipitation was evenly distributed around the typhoon center. The typhoon cloud system, characteristics of the typhoon, and ocean factors could be responsible for the asymmetric structure of precipitation during the typhoon period. The change in the typhoon cloud system during the typhoon influenced the distribution of precipitation. And there have been some oceanic processes that influenced the distribution of precipitation. Anticyclonic eddies and thick mixing level depths (MLDs) play important roles in typhoon precipitation. The anticyclonic eddies with thick MLD exist to reduce the mixing of the upper ocean to maintain the SST. Therefore, the SST and air-sea exchange can be sustained to influence typhoon precipitation. This study provides a new understanding of the impact of ocean processes on typhoon precipitation distribution.

Validation of Doppler Wind Lidar during Super Typhoon Lekima (2019)

This study undertook verification of the applicability and accuracy of wind data measured using a WindCube V2 Doppler Wind Lidar(DWL).The data were collected as part of a field experiment in Zhoushan,Zhejiang Province(China),which was conducted by Shanghai Typhoon Institute of China Meteorological Administration during the passage of Super Typhoon Lekima(2019).The DWL measurements were compared with balloon-borne GPS radiosonde(GPS sonde)data,which were acquired using balloons launched from the DWL location.Results showed that wind speed measured by GPS sonde at heights of<100 m is unreliable owing to the drift effect.Optimal agreement(at heights of>100 m)was found for DWL-measured wind speed time-averaged during the ascent of the GPS sonde from the ground surface to the height of 270 m(correlation coefficient:0.82;root mean square(RMS):2.19 m·h^(-1)).Analysis revealed that precipitation intensity(PI)exerts considerable influence on both the carrier-to-noise ratio and the rate of missing DWL data;however,PI has minimal effect on the wind speed bias of DWL measurements.Specifically,the rate of missing DWL data increased with increasing measurement height and PI.For PI classed as heavy rain or less(PI<12 mm·h^(-1)),the DWL data below 300 m were considered valid,whereas for PI classed as a severe rainstorm(PI>90 m·h^(-1)),only data below 100 m were valid.Up to the height of 300 m,the RMS of the DWL measurements was nearly half that of wind profile radar(WPR)estimates(4.32 m·s^(-1)),indicating that DWL wind data are more accurate than WPR data under typhoon conditions.

Typhoon Risk Perception: A Case Study of Typhoon Lekima in China

The typhoon is one major threat to human societies and natural ecosystems, and its risk perception is crucial for contextualizing and managing disaster risks in different social settings. Social media data are a new data source for studying risk perception, because such data are timely, widely distributed, and sensitive to emergencies.However, few studies have focused on crowd sensitivity variation in social media data-based typhoon risk perception. Based on the regional disaster system theory, a framework of analysis for crowd risk perception was established to explore the feasibility of using social media data for typhoon risk perception analysis and crowd sensitivity variation. The goal was to quantitatively analyze the impact of hazard intensity and social and geographical environments on risk perception and its variation among population groups. Taking the Sina Weibo data during Typhoon Lekima of 2019 as an example, we found that:(1)Typhoon Lekima-related Weibo public attention changed in accordance with the evolution of the typhoon track and the number of Weibo posts shows a significantly positive correlation with disaster losses, while socioeconomic factors,including population, gross domestic product, and land area, are not explanatory factors of the spatial distribution of disaster-related Weibo posts;(2) Females, nonlocals with travel plans, and people living in areas with high hazard intensity, low elevation, or near waterbodies affected by Lekima paid more attention to the typhoon disaster;and(3)Descriptions of rainfall intensity by females are closer to the meteorological observation data.

Drastic change in dynamics as Typhoon Lekima experiences an eyewall replacement cycle

Why does the 1909 typhoon,Lekima,become so destructive after making landfall in China?Using a newly developed mathematical apparatus,the multiscale window transform(MWT),and the MWT-based localized mutliscale energetics analysis and theory of canonical transfer,this study is intended to give a partial answer from a dynamical point of view.The ECMWF reanalysis fields are first reconstructed onto the background window,the TC-scale window,and the convection-scale window.A localized energetics analysis is then performed,which reveals to us distinctly different scenarios before and after August 8–9,2019,when an eyewall replacement cycle takes place.Before that,the energy supply in the upper layer is mainly via a strong upper layer-limited baroclinic instability;the available potential energy thus-gained is then converted into the TC-scale kinetic energy,with a portion to fuel Lekima’s upper part,another portion carried downward via pressure work flux to maintain the cyclone’s lower part.After the eyewall replacement cycle,a drastic change in dynamics occurs.First,the pressure work is greatly increased in magnitude.A positive baroclinic transfer almost spreads throughout the troposphere,and so does barotropic transfer;in other words,the whole air column is now both barotropically and baroclinically unstable.These newly occurred instabilities help compensate the increasing consumption of the TC-scale kinetic energy,and hence help counteract the dissipation of Lekima after making landfalls.

The impact of Typhoon Lekima (2019) on East China: a postevent survey in Wenzhou City and Taizhou City

Typhoon Lekima(2019)struck Zhejiang Province on 10 August 2019 as a supertyphoon,which severely impacted Zhejiang Province.The typhoon killed 45 people and left three others missing,and the total economic loss reached 40.71 billion yuan.This paper reports a postdisaster survey that focuses on the storm precipitation,flooding,landslides,and weather services associated with Typhoon Lekima(2019)along the southeastern coastline of Zhejiang Province.The survey was conducted by a joint survey team from the Shanghai Typhoon Institute and local meteorological bureaus from 26 to 28 August,2019,approximately two weeks after the disaster.Based on this survey and subsequent analyses of the results,we hope to develop countermeasures to prevent future tragedies.

Evaluation of forecast performance for Super Typhoon Lekima in 2019

The predictions for Super Typhoon Lekima(2019)have been evaluated from official forecasts,global models,regional models and ensemble prediction systems(EPSs)at lead times of 1–5 days.Track errors from most deterministic forecasts are smaller than their annual mean errors in 2019.Compared to the propagation speed,the propagation direction of Lekima(2019)was much easier to determine for the official agency and numerical weather prediction(NWP)models.The National Centers for Environmental Prediction Global Ensemble Forecast System(NCEP-GEFS),Japan Meteorological Agency Global Ensemble Prediction System(JMA-GEPS)and Meteorological Service of Canada Ensemble System(MSC-CENS)are underdispersed,and the Shanghai Typhoon Institute Typhoon Ensemble Data Assimilation and Prediction System(STI-TEDAPS)is overdispersed,while the ensemble prediction system from European Centre for Medium-Range Weather Forecasts(ECMWF)shows adequate dispersion at all lead times.Most deterministic forecasting methods underestimated the intensity of Lekima(2019),especially for the rapid intensification period after Lekima(2019)entered the East China Sea.All of the deterministic forecasts performed well at predicting the first landfall point at Wenling,Zhejiang Province with a lead time of 24 and 48 h.

中低纬度系统相互作用过程的中尺度风场分析

以山东济南和滨州两部S波段多普勒雷达的观测数据为基础,采用直接合成的方法,反演台风“利奇马”和西风槽相遇引发极端降水过程的中尺度系统三维风场。(1)冷暖空气交汇产生的切变线长时间维持是西风槽与台风相互作用过程中产生极端降水的关键,暖空气先进后退,表现为东南气流和西北气流先后越过雷达站,垂直方向出现复合切变;(2)最强上升运动出现在对流单体回波梯度最大的区域,最大下沉运动出现在回波顶下风方,中低层回波中心均为弱风速区;(3)发展中的对流单体各层均有气旋式入流,成熟的对流单体高层出流有反气旋式出流;(4)风垂直切变是雨团降水增幅的主要影响因素,成熟期的雨团具有低质心对流单体风暴的结构形态,垂直运动达到最强。

A catastrophic natural disaster chain of typhoon-rainstorm-landslide-barrier lake-flooding in Zhejiang Province, China

On August 10,2019,due to the effect of a rainstorm caused by Super Typhoon Lekima,a landslide occurred in Shanzao Village,China.It blocked the Shanzao stream,forming a barrier lake,and then the barrier lake burst.This is a rare natural disaster chain of typhoon-rainstorm-landslide-barrier lake-flooding.This study was built on field surveys,satellite image interpretation,the digital elevation model(DEM),engineering geological analysis and empirical regression.The purpose was to reveal the characteristics and causes of the landslide,the features and formation process of the barrier lake and the dam break flooding discharge.The results show that the volume of the landslide deposit is approximately 2.4×105 m3.The burst mode of the landslide dam is overtopping,which took only 22 minutes from the formation of the landslide dam to its overtopping.The dam-break peak flow was 1353 m3/s,and the average velocity was 2.8–3.0 m/s.This study shows that the strongly weathered rock and soil slope has low strength and high permeability under the condition of heavy rainfall,which reminds us the high risk of landslides and the importance of accurate early warning of landslides under heavy rainfalls in densely populated areas of Southeast China,as well as the severity of the disaster chain of typhoon-rainstorm-landslide-barrier lake-flooding.

基于集成学习的FY-4A/GIIRS红外通道亮温偏差订正研究

资料变分同化方法基于观测误差无偏的假设,故偏差订正是卫星资料质量控制的重要环节之一。开展了基于集成学习的风云四号A星(Feng-Yun 4A,FY-4A)干涉式大气垂直探测仪(Geostationary Interferometric Infrared Sounder,GIIRS)中波红外通道亮温偏差订正研究。将随机森林、极端梯度提升(eXtreme Gradient Boosting,XGBoost)、Decision Tree和Extra Tree作为集成学习的基础模型。在优化基础模型的超参数后,采用广义误差极小化方法集成基础模型回归结果。基于台风“利奇马”期间的加密晴空视场点资料,对比了集成学习、基础模型和离线法的GIIRS通道亮温偏差订正效果。试验结果表明,本文所采用的订正方法均取得了好的结果。在所有方法中,集成学习的订正效果最佳。在气团预报因子中,地理(经度和纬度)信息对基础模型贡献率较大。本文方法可推广至其他资料的偏差或误差订正。

台风Lekima(1909)登陆前后动热力结构变化对浙江极端降水的影响

利用NCEP FNL 1°×1°的全球再分析资料、FY-2F卫星相当黑体亮温TBB资料、中国自动站与CMORPH降水产品融合的逐时降水资料和多普勒天气雷达资料,重点分析了台风Lekima(2019)发展演变过程中的动热力结构变化和水汽分布特征与浙江极端强降水之间的关系。台风Lekima(2019)近海急剧加强为具有特殊双眼壁结构的超强台风,登陆前后环境水平风垂直切变维持较小值是主导台风高强度维持的重要原因。浙江上空维持着强盛的低层辐合和高层辐散场,高低层辐散风的高强度维持使得次级环流抽吸作用强,低层旋转风和辐散风对水汽、动量和热量的输送和分布起到显著的再分配作用,而中层的辐散风风向和风速变化对螺旋云带中的中尺度对流性降水具有重要的指示意义。登陆前后台风低层东北侧(超)低空急流和中层的辐合线是此次浙江台风暴雨的关键点,业务中需密切关注登陆前后台风东北侧的低空急流的影响区域及其变化。此外,700 hPa上非地转湿Q矢量散度场能较好指示未来1小时短时强降水的落区和强度变化,同时结合垂直速度场和低层水汽辐合场来综合判断台风降水落区的效果更佳。

极端暴雨下典型小流域重力侵蚀的分布及影响因素

为探究极端暴雨下重力侵蚀分布规律及其环境条件,以2019年“利奇马”台风引发的特大暴雨事件为对象,采用无人机航拍、室内解译等方法,研究了位于暴雨中心的山东省临朐县曾家沟小流域内不同类型重力侵蚀的数量、空间分布特征及其影响因素。结果表明:(1)小流域内发生的重力侵蚀共70处,主要类型为滑坡(49处),其次为泥石流(14处)和崩塌(7处)。(2)重力侵蚀面积、侵蚀量分别与坡度变率、坡度、坡位、高程、坡向和坡向变率呈正相关,与距梯田距离、距道路距离和土地利用类型呈负相关。(3)坡度是影响重力侵蚀的最重要因素,侵蚀易发生在坡度为30°~50°的斜坡。(4)人类活动对重力侵蚀的影响较大,特大暴雨下的严重重力侵蚀多发生在梯田田坎、道路边坡等位置,需将重力侵蚀防治的重心放在加强道路两侧边坡、梯田田坎和坡度>30°的陡坡边坡防护上。研究结果可为应对和预防重力侵蚀灾害提供科学依据。

台风“利奇马”远距离暴雨的关键动力因子和水汽来源

基于地面加密观测、ERA5再分析、ECMWF全球集合预报等多源资料,利用敏感性分析方法、涡度收支诊断方法以及拉格朗日水汽追踪方法,探讨1909号台风“利奇马”造成远距离暴雨的关键动力因子和水汽来源。结果表明,对流层低层短波槽的加深有利于台风远距离降水(Tropical cyclone Remote Precipitation,TRP)区南北两侧的气流共同增强TRP区域内的低层相对涡度,从而增强TRP。尤其相对涡度的散度项是影响TRP增强或减弱的关键作用项。在TRP增强阶段,有利于暴雨增强的正涡度主要由散度项贡献。负的散度项贡献导致相对涡度减小,TRP雨强也随即减弱。在水汽方面,TRP雨强和区域内的水汽含量密切相关。500 hPa上TRP区域内的水汽由局地和台风“利奇马”共同贡献;700 hPa的水汽主要由“利奇马”台风贡献;850 hPa的水汽则由局地和两个台风共同输送,其中台风“罗莎”的贡献更大一些。

登陆台风外围极端降水过程的中α尺度系统特征

采用全国多普勒雷达反射率因子拼图、山东省自动气象观测站数据,结合ERA50.25°×0.25°再分析资料,分析台风“利奇马”造成山东极端暴雨的中α尺度系统特征。结果表明:台风北侧东南急流与西风槽后偏西气流的切变引发的中α尺度辐合区是直接造成极端降水的中尺度系统;对流始于800~750 hPa,随后沿西风槽向高层发展,再伸展到低层,在台风北侧低层切变附近强烈发展;初始对流由低空急流触发,后高空出流迅速增强,促进上升运动发展,高低空急流上下耦合的正反馈作用促进了中α尺度辐合区深度发展,是极端降水发生发展的重要原因;初始对流发生在对流不稳定环境中,凝结潜热释放造成的湿斜压性和中低层垂直切变形成的条件性对称不稳定增长,使对流发展为有组织而长时间维持的深对流;水平风场将水汽汇集向暴雨区,上升运动将水汽向中高层输送,湿层逐渐增厚,当水汽通量15 g/(cm·hPa·s)等值线向上伸展到500 hPa时,降水强度超过20 mm/h;鲁中山区地形是影响降水中心落区的重要因素。

基于SBAS-InSAR技术的山早滑坡形变分析

台风暴雨诱发滑坡具有突发性,调查难度较大。以台风“利奇马”期间发生的山早滑坡为例,基于滑坡发生前的升轨哨兵一号2017年9月12日至2019年8月9日的24景数据,采用SBAS-InSAR技术分析了该时段滑坡的时序累积变形,并结合气象资料进一步分析了滑坡体地表形变的规律。结果表明,山早滑坡发生前的形变主要划分为滑坡体蠕变阶段、滑坡体前缘变形显著增加并向坡体中部逐渐扩大阶段、滑坡体后缘加速变形阶段3个阶段;滑坡体上InSAR监测点垂直方向的形变速率及累积变形数据显示坡体前缘及中部形变速率和累计变形较小,变形主要集中在滑坡体的后缘,其形变速率和累计沉降最大分别可达40 mm/a和320 mm,该滑坡为推移式滑坡。研究结果为滑坡的早期识别及监测预警提供了新的思路和方法,对滑坡灾害的防治有一定的参考价值。

基于全球闪电定位网的江淮闪电定位网探测效率分析:以台风“利奇马”为例

基于全球闪电定位网(World Wide Lightning Location Network,WWLLN)获取的闪电定位资料对江淮闪电定位网(Jianghuai Area Sferic Array,JASA)在内陆及近海区域的闪电实时探测性能进行评估。通过对2019年第9号超强台风“利奇马”期间产生的闪电活动进行对比分析,发现JASA和WWLLN对台风闪电的径向分布、时间变化和空间变化有较好的一致性,绝大部分闪电发生在云顶亮温小于220 K区域;在台风发展阶段,内核区闪电活动较为频繁,在台风成熟和消亡阶段时,闪电主要分布外雨带,内核区的闪电活动少但集中。在探测效率方面,JASA对江淮区域实时定位到的闪电数远多于WWLLN,相对探测效率和绝对探测效率分别为69.12%和92.51%。而在海洋区域(114~130°E,20~24°N和123~130°E,24~32°N),由于受到JASA站点位置分布的限制,闪电实时定位数略少于WWLLN,其相对探测效率和绝对探测效率分别为32.67%和52.26%。研究结果表明了JASA对内陆及近海区域雷暴具备较强的捕获能力,为实时监测台风期间强对流闪电活动的演变规律提供数据支撑,也为进一步完善站点布局以提升深海区域闪电探测性能提供了理论支撑。

基于利奇马台风路径下的FY-4A海洋热含量空间自相关分析

每年我国沿海多地遭受不同程度的台风灾害影响,台风对我国多个省市地区人民造成严重的生命和财产安全危害。海洋热含量(TCHP)是影响台风的主要因素之一,文中将2019年利奇马台风数据与基于FY-4A融合海温数据反演得到的TCHP数据做时空匹配,得到利奇马台风路径上的TCHP。然后在地统计学的基础上,引入全局自相关分析和局部自相关分析方法,对台风路径上的TCHP进行分析研究。结果表明:TCHP的全局Moran′s I值为0.94,即在相邻空间位置上具有高度的正空间自相关性;TCHP局部空间自相关特征主要以高-高,低-低这2种空间聚集形态为主,在局部空间上没有表现出异质性,具有较高的空间相关性;在利奇马台风发生及发展过程中,随空间位置的变化,TCHP属性值逐渐由低-低聚集类型向高-高聚集类型转变,对海-气交换产生负反馈影响,此时TCHP和台风移速在此变化过程中虽然波动较大,但是变化后维持在一定的范围内。台风强度也在变化之后增速也逐渐变缓,形成一个稳定状态。

超强台风利奇马(1909)期间海洋中尺度冷涡特征分析

对超强台风“利奇马”期间西北太平洋海表面高度异常(SLA)特征及台风移动路径附近中尺度冷涡特征进行了分析,结果表明:“利奇马”过境前后,西北太平洋SLA以正值为主,闭合SLA负值区C1负异常数值减小、范围扩大,C2变化不明显;“利奇马”以6.4~10.8 km/h移速横穿中尺度冷涡CE1,并向西北方向移动,移出前后CE1强度、范围加强(SLA极值为-19.6 cm);以13.9~20.4 km/h快速从CE2以东海域移过,过境前后CE2强度、范围变化不明显;CE1、CE2位于“利奇马”强迫区域内,“利奇马”对CE1影响时间长(18~42 h),使得CE1范围增大、强度增强,对CE2影响则不明显。

基于高光谱GIIRS红外亮温的大气三维风场反演研究

风场对于天气形势的演变和预报至关重要。基于风云四号A星干涉式大气垂直探测仪(GIIRS)中波通道资料和ERA5风场资料,采用LightGBM进行大气三维风场反演研究。首先,构建模型特征变量。GIIRS通道最优选择采用二步特征选择法:(1)建立GIIRS通道黑名单;(2)采用置换特征重要性(Permutation Feature Importance,PFI)方法选择特征变量,在形成通道最优子集的基础上,构建含有时空信息的特征变量。其次,构建基于LightGBM的三维风场反演方法。最后,基于台风“利奇马”期间的GIIRS加密资料开展了LightGBM超参数优化和相关反演试验。结果表明,相对于ERA5风场资料,测试集中风场U和V分量的均方根误差(Root Mean Square Error,RMSE)分别小于1 m/s和1.5 m/s。本文中的二步特征选择法能够实现GIIRS通道的动态最优选择。

台风“利奇马”(1909)影响期间上海强降水成因诊断分析

2019年第9号台风“利奇马”(1909)在8月9—11日影响上海期间造成了严重的风雨影响。基于ERA5逐小时再分析资料和上海区域高时空分辨率的地面观测资料,采用非地转Q矢量分解等方法诊断分析了此次强降水成因。结果表明,台风“利奇马”在上海造成的强降水主要来自台风东侧的螺旋雨带。强降水区东南西北各边界的相对湿度在垂直方向上随时间的变化差异明显,水汽的垂直输送和大气整层水汽含量在台风强降水中起重要作用。进一步利用非地转Q矢量分解方法揭示了东边界的大尺度和北边界的中尺度系统在强降水中起主要作用。台风登陆时呈现出整层大气被抬升之后最大强迫中心由高层向低层下传的态势,且此下传效应中尺度比大尺度强迫更加明显,从而有利于强降水的发生。

北上台风引发锦州连续性暴雨的成因分析

【目的】诊断分析锦州地区2019年8月10日至15日出现的连续性暴雨。【方法】利用Micaps实况数据资料、ECWMF再分析资料等进行分析。【结果】受西风带冷空气、副热带高压及减弱台风“利奇马”外围云系等连续影响,锦州地区此次暴雨过程持续时间长、累计雨量大、风力较强、致灾程度高,总降水量达暴雨到大暴雨量级,局部特大暴雨。【结论】此次暴雨持续时间长、累计雨量大主要是由于副热带高压和大陆高压两高对峙,移速较慢,以及源源不断的水汽和能量补充的影响,高层辐散、低层辐合的高低空配置有利于垂直上升运动发展。此外,冷空气从底层卷入使台风“利奇马”结构破坏,减弱填塞,斜压发展,虽然缩短了台风生命史,却是造成本次暴雨“长时效”特点的关键。