Typhoon-Induced Ocean Waves and Stokes Drift:A Case Study of Typhoon Mangkhut(2018)

Ocean waves and Stokes drift are generated by typhoons.This study investigated the characteristics of ocean waves and wave-induced Stokes drift and their effects during Typhoon Mangkhut using European Centre for MediumRange Weather Forecasts(ECMWF)ERA5 datasets and observational data.The results revealed that the typhoon generated intense cyclones and huge typhoon waves with a maximum wind speed of 45 m/s,a minimum pressure of955 h Pa,and a maximum significant wave height of 12 m.The Stokes drift caused by typhoon waves exceeded 0.6m/s,the Stokes depth scale exceeded 18 m,and the maximum Stokes transport reached 6 m^(2)/s.The spatial distribution of 10-m wind speed,typhoon wave height,Stokes drift,Stokes depth,and Stokes transport during the typhoon was highly correlated with the typhoon track.The distribution along the typhoon track showed significant zonal asymmetry,with greater intensity on the right side of the typhoon track than on the left side.These findings provide important insights into the impact of typhoons on ocean waves and Stokes drift,thus improving our understanding of the interactions between typhoons and the ocean environment.This study also investigated the contribution of Stokes transport to the total net transport during typhoons using Ekman-Stokes Numbers as a comparative measure.The results indicated that the ratio of Stokes transport to the total net transport reached up to 50%within the typhoon radius,while it was approximately 30%outside the radius.Strong Stokes transport induced by typhoon waves led to divergence in the transport direction,which resulted in upwelling of the lower ocean as a compensation current.Thus,Stokes transport played a crucial role in the vertical mixing of the ocean during typhoons.The findings suggested that Stokes transport should be paid more attention to,particularly in high latitude ocean regions,where strong winds can amplify its effects.

Atmospheric and oceanic responses to Super Typhoon Mangkhut in the South China Sea:a coupled CROCO-WRF simulation

The South China Sea(SCS)is the largest marginal sea in the Northwest Pacific Ocean,and it encounters frequent typhoons.The atmosphere and ocean will create significant thermal and dynamic responses during the intense disturbance caused by typhoons.However,these responses have not been thoroughly investigated owing to the complicated marine environment.According to the satellite data,the SCS Basin was observed to have a strong sea surface temperature(SST)response to Typhoon Mangkhut,resulting in widespread SST cooling.A coupled model was used to investigate the atmospheric and oceanic responses to Typhoon Mangkhut.Best-track data,satellite SST,and ARGO measurements show that the coupled WRF-CROCO simulation displays better track,intensity,SST,temperature,and salinity profiles than those of the WRF-only simulation.Results show that the typhoon induced rightward intensifications in wind speed,ocean current,and SST.The following are some remarkable atmosphere and ocean responses:(1)the SST below the inner-core region is cooled by 1℃,resulting in a 37%-44%decrease in wet enthalpy,and the central pressure is increased by~9 hPa.Therefore,the changes in SST below the innercore region of the SCS Basin have a significant impact on air-sea fluxes under high-wind conditions;(2)the ocean boundary layer analysis shows that near-inertial oscillations on the right side of the typhoon track and a strong inertial current up to~2.28 m/s in the upper ocean were observed,which resonated with the local wind and flow field on the right side and induced strong SST cooling;(3)a decrease in SST decreased the moist static energy of the typhoon boundary layer,thereby weakening the typhoon’s intensity.The difference in equivalent potential temperature and sea surface pressure have a good correlation,indicating that the influence of moist static energy on typhoon intensity cannot be overlooked.

Multi-scale Incremental Analysis Update Scheme and Its Application to Typhoon Mangkhut(2018)Prediction

In the traditional incremental analysis update(IAU)process,all analysis increments are treated as constant forcing in a model’s prognostic equations over a certain time window.This approach effectively reduces high-frequency oscillations introduced by data assimilation.However,as different scales of increments have unique evolutionary speeds and life histories in a numerical model,the traditional IAU scheme cannot fully meet the requirements of short-term forecasting for the damping of high-frequency noise and may even cause systematic drifts.Therefore,a multi-scale IAU scheme is proposed in this paper.Analysis increments were divided into different scale parts using a spatial filtering technique.For each scale increment,the optimal relaxation time in the IAU scheme was determined by the skill of the forecasting results.Finally,different scales of analysis increments were added to the model integration during their optimal relaxation time.The multi-scale IAU scheme can effectively reduce the noise and further improve the balance between large-scale and small-scale increments in the model initialization stage.To evaluate its performance,several numerical experiments were conducted to simulate the path and intensity of Typhoon Mangkhut(2018)and showed that:(1)the multi-scale IAU scheme had an obvious effect on noise control at the initial stage of data assimilation;(2)the optimal relaxation time for large-scale and small-scale increments was estimated as 6 h and 3 h,respectively;(3)the forecast performance of the multi-scale IAU scheme in the prediction of Typhoon Mangkhut(2018)was better than that of the traditional IAU scheme.The results demonstrate the superiority of the multi-scale IAU scheme.

FY-4A LMI Observed Lightning Activity in Super Typhoon Mangkhut(2018)in Comparison with WWLLN Data

Using lightning observations from the Fengyun-4A Lightning Mapping Imager(FY-4A LMI),best-track data from the Shanghai Typhoon Institute,bright temperature(TBB)data from Himawari-8 satellite,and composite reflectivity(CR)data from the South China radar network,we investigate the spatiotemporal distribution of lightning activity and convective evolution during the landfall of Super Typhoon Mangkhut,the strongest landing typhoon in China in2018.Three stages of active total lightning are observed,and differences of lightning characteristics between the inner core and the outer rainbands are present.The onset of inner-core lightning outbreak is about 4 h ahead of the maximum intensity of the storm,providing indicative information on the change of typhoon intensity.Lightning rates in the outer rainbands increase rapidly 12 h before the landfall,and lightning activity is mainly confined in the outer rainbands after the landfall.A good correlation in hourly variation is shown between lightning rates from the LMI and TBBs from the satellite.The averaged TBB within the inner core reaches its minimum(–80℃)when the innercore lightning outbreak occurs,indicating the occurrence and enhancement of deep convection there.Lightning locations observed by the LMI has a good spatial correspondence with regions of low TBBs and high CRs,revealing the monitoring capability of the LMI to lightning activity and deep convection in landing typhoons.Comparisons between the World Wide Lightning Location Network(WWLLN)and the LMI reveal that the spatial distribution,temporal evolution,and radial pattern of lightning activity in Mangkhut observed by the two systems are consistent.Furthermore,due to the detection capability of total lightning,the LMI has advantages in revealing the higher ratio of intra-cloud lightning within the inner core in typhoon.The continuous and real-time observation ofFY-4ALMI provides an unprecedented platform for monitoring total lightning and deep convection in landing typhoons in China,which will promote the generation of new research and applications in the future.

Assessment of the damages and direct economic loss in Hong Kong due to Super Typhoon Mangkhut in 2018

Super Typhoon Mangkhut hit Hong Kong on September 16,2018,necessitating the issuance of the highest tropical cyclone warning signal,No.10 Hurricane Signal.Packing ferocious winds and record-breaking storm surge,Mangkhut brought the most serious and widespread destruction to the territory in the recent three decades.A series of post event information search,field visits and damage surveys has been conducted by the Hong Kong Observatory(HKO)and the findings on the damages and impacts caused by Mangkhut in different parts of the territory are documented in this paper.Moreover,by analyzing the economic loss data reported by various government departments,public utilities and organizations in Hong Kong and the statistics on insurance claims from the Hong Kong Federation of Insurers(HKFI),the estimated direct economic loss due to Mangkhut in Hong Kong is about HK$4.60 billion,which is about 3.8 times to that of Super Typhoon Hato in 2017.On the contrary,in the Guangdong-Hong Kong-Macao Greater Bay Area,the estimated direct economic loss due to Hato is significantly higher than that of Mangkhut.This could be attributed to the early and effective warnings for Mangkhut,increased public awareness and typhoon preparedness for Mangkhut in 2018 since the fierce attack of Hato in 2017,and infrastructure enhancement of the major impact areas.

Natural and Socioeconomic Factors and Their Interactive Effects on House Collapse Caused by Typhoon Mangkhut

Typhoons are an environmental threat that mainly affects coastal regions worldwide.The interactive effects of natural and socioeconomic factors on the losses caused by typhoon disasters need further examination.In this study,GeoDetector was used to quantify the determinant powers of natural and socioeconomic factors and their interactive effects on the rate of house collapse in Guangdong and Guangxi Provinces of southeast China caused by Typhoon Mangkhut in 2018.We further identify the dominant factors that influenced the disaster losses.The local indicators of spatial association method was then introduced to explain the spatial heterogeneity of the disaster losses under the influence of the dominant factor.The results indicate that both natural and socioeconomic factors significantly affected the house collapse rate.The maximum precipitation was the dominant factor,with a q value of 0.21,followed by slope and elevation,with q values of 0.17 and 0.13,respectively.Population density and per capita gross domestic product had q values of 0.15 and0.13,respectively.Among all of the interactive effects of the influencing factors,the interactive effect of elevation and the ratio of brick-wood houses had the greatest influence(q=0.63)on the house collapse rate.These results can contribute to the formulation of more specific safety and property protection policies.

Ensemble Based Diagnosis of the Track Errors of Super Typhoon Mangkhut(2018)

Super Typhoon Mangkhut(2018)was the most high-impact typhoon in 2018 because of its long lifespan and significant intensity.The operational track forecasts in the short-to-medium range(deterministic and probabilistic forecast)showed a great uncertainty and the forecast landing points varied with different lead times.This study applied ensembles of high-resolution ECMWF forecasts to investigate the major factors and mechanisms of the bias production of the Mangkhut forecast track.The ensembles with the largest track bias were analyzed to examine the possible bias associated factors.The results suggested that environmental steering flows were the main cause for the erroneous southward track error with a variance contribution of 72%.The tropical cyclone(TC)size difference and the interaction of the TC with the subtropical high(SH)were other two key factors that contributed to the track error.Particularly,larger TCs may have led to a stronger erosion of the southern part of the SH,and thus induced significant changes in the large-scale environment and eventually resulted in an additional northward movement of TC.

A distributed hydrological forecast system and its application in predicting the flood caused by Mangkhut

The currently used hydrological forecast system in China is mainly focused on flood,and the flood forecasting frameworks are typically based on point discharge measurements and predictions at discrete locations,hence they can’t provide spatio-temporal information of various hydrological elements,such as surface runoff,soil moisture,ground water table,and flood inundation extents over large scales and at high spatial resolutions.The use of distributed hydrological model has recently appeared to be the most suitable option to bridge this gap.An open source GIS-based distributed hydrological forecast system was established recently,and the watershed delineation and hydrological modelling were integrated together seamlessly.The time and human consuming work of processing the spatial data in building distributed hydrological model could be reduced significantly,and the spatial distribution of hydrological information could be quickly simulated and predicted using this system.The system was applied successfully to forecast the flood caused by super strong typhoon"Mangkhut"which attacked the south China in2018.

基于多变量灰色模型的台风强度模拟方法

随着台风全路径模拟技术的不断完善,全海域、大范围的台风危险性分析方法得到发展,然而强度模型的模拟精度不能满足需求。针对台风强度演变受多因素影响、动力关系复杂及强度变化随机性强的特点,基于多变量灰色模型对台风强度模拟方法进行研究,并建立起台风多变量灰色强度模型。利用该模型还原了台风“山竹”的强度演变过程,同时对西北太平洋地区整体台风强度进行模拟及检验分析。结果表明:垂直风切变及垂直速度与台风强度的灰色关联度分别为0.771 8、0.745 1,显著高于其他3个环境因素;台风“山竹”强度模拟的后验差比值及小概率误差分别为0.349 1、0.960 8,达到了最高模拟精度;模型模拟所得西北太平洋地区整体的强度变化趋势及分布特征均与地区实际情况保持一致。

一种基于分析增量更新技术的台风初始化方案

台风初始化方案最大的困难在于其只能根据有限的观测资料(台风中心位置、最低气压、最大风速和大风半径等)来构造一个与模式动力-物理过程协调的涡旋模型。首先根据实际观测资料对背景场中的涡旋扰动进行重定位和风速调整,然后将分析增量更新(Incremental Analysis Update,IAU)技术应用于台风初始化方案中,将调整后的涡旋当作一个强迫项逐渐加入到模式预报过程中,通过模式自身调整来得到一个协调性较好的台风初始结构,从而改善模式对台风的预报性能。对"山竹"台风的多次预报结果表明:(1)台风初始化对于台风路径误差影响较小,对于强度预报改进则比较明显。特别是在台风生成初期,台风初始化技术能够有效地增强全球模式分析场中的涡旋强度,并解决预报过程中强度较弱的问题。(2)根据预先给定的三维风场,IAU技术能通过模式自身预报过程对其他变量进行调整,从而得到一个热力和动力协调的初始涡旋结构。相对于仅对初始风场的调整,它对24 h之后的路径和强度预报误差会有更进一步的改善。(3)对IAU中的松弛时间进行参数敏感性试验,发现该变量取3-6 h效果较好。

1822号台风“山竹”引起的南海北部热异常

1822号台风“山竹”是2018年登陆华南沿海的最强台风,给华南地区带来了强风暴雨等严重灾害。本文采用了欧洲中期天气预报中心海表温度(Sea Surface Temperature,SST)日值产品和中国风云系列卫星的热红外亮温数据,对数据进行均值残差处理、小波分析和相对功率谱(Relative Power Spectrum,RPS)估计,得到台风发展过程的SST变化以及亮温RPS信息。对SST和亮温RSP的综合分析结果表明:台风生成前和活动期间在南海北部引起了SST增温异常和过境后的冷迹,也出现了21 d和16 d特征周期的热辐射异常;异常过程反映了台风与海洋的热交换过程,即热交换开始于台风生成之前,促使台风向南海北部移动,台风过境后大幅度降温;台风产生的热异常集中在南海北部,但主要分布在台风路径南侧的海面范围,这可能与台风过程中的海-陆、海-气热交换密切相关。

自然灾害中政府和媒体的议程互动关系——以台风“山竹”为例

在自然灾害应对中,政府利用媒体力量将事件信息传递给公众,研究媒体上事件信息的议题讨论与政府建构的事件议题是否一致有助于了解政府危机沟通效果。以2018年台风“山竹”为例,基于网络议程设置理论分析自然灾害中政府和媒体的议程网络及其互动关系。研究发现,政府和媒体的议程网络存在显著的正相关性,且呈现出“合”与“离”的两种交互状态。宏观层面看,政策议程和媒体议程均聚焦于政府行为、事件陈述、实用信息属性上;微观层面看,政策议程建构逻辑偏感性色彩,议程网络结构呈现议题集中化和核心化特征;而媒体议程建构逻辑偏理性口吻,议程网络结构呈现议题均匀分布特征。据此得出:政府要主动建构议题,掌握危机沟通话语权;积极发挥新媒体特性,提高政策议程传播效能;合理组合议题要素,通过输出逻辑引导社会舆论。

海南高校应对台风“山竹”举措——以海南经贸职业技术学院为例

海南高校在应对台风的举措中包括过境前的准备和预防、登陆时的天气和应对、过境后的恢复及整理。海南经贸职业技术学院在台风“山竹”中能迅速反应、上下联动,一切以学生为本,确保师生人身安全及财产安全,积极做好防台风措施。

珠江河口风暴潮对径流的敏感性研究:以台风“山竹”为例

径流-风暴潮相互作用可增大河口区风暴潮增水,增加风暴潮灾害风险。基于SCHISM模式建立了珠江河口风暴潮数值模型,以台风“山竹”为例,采用实测资料对模型计算结果进行验证,最高潮位相对误差在9%以内。设计了台风“山竹”实测径流与5年一遇洪水的对比试验,讨论了径流变化对河口风暴潮增水的影响,结果表明:河口口门站位风暴潮增水随径流量的增大而增大。径流增加对泗盛围、南沙等站位的风暴潮影响较大,在风暴潮增水达到最大值时影响最为显著。以径流动力作用为主的区域,当上游径流量增大时,对风暴潮增水起到负影响作用:如磨刀门水道,随着径流的增加,沿河道上溯的风暴潮增水逐渐减小,由灯笼山站3.22 m减小至马口站1.12 m。以潮汐动力作用为主的区域,当上游径流量增大时,对风暴潮增水起到正影响作用:如珠江干流,随着径流的增加,沿河道上溯的风暴潮增水逐渐增大,大虎站的最大增水值为3.44 m,中大站为4.24m,从口门至后航道区域增大了0.8 m。

典型厄尔尼诺期间台风降水δ18O变化分析:以2018年22号台风“山竹”为例

台风因其特殊的物理结构,带来的降雨有别于一般的暴雨事件,其降水稳定同位素组成与一般的大气降水事件也有较大的差异。本文根据2018年第22号台风"山竹"登陆前后广州、东莞两地气象资料和每小时间隔的降水样品收集,分析了此次台风在两地的降水稳定同位素变化特征及其影响因素。台风"山竹"影响期间,广州降水δ18O值变化范围为–5.7‰~–19.2‰,变化幅度达13.5‰,其平均值为–15.5‰;东莞降水δ18O值变化范围为–7.3‰~–20.0‰,变化幅度达12.7‰,平均值为–14.8‰;两地降水δ18O值均呈现为3个阶段倒U型的变化特征。受到蒸发作用的影响,两地台风前端和尾端的降水氧同位素值相对偏正,其中广州为–5.7‰~–9.3‰,东莞为–7.3‰~–8.1‰。两地台风中端的降水稳定同位素值极端偏负,δ18O值变化范围分别为–16.0‰~–19.2‰(广州)和–13.0‰~–20.0‰(东莞),是该地区迄今为止已报道的最为偏负的降水δ18O值。分析认为,在厄尔尼诺状态下生成的远源台风"山竹"强度增强,其内部具有更强的对流和水汽循环过程,导致降水δ18O值极端偏负。

台风山竹(1822)龙卷的双极化相控阵雷达特征

2018年9月17日台风山竹(1822)外围螺旋雨带中发生EF2级龙卷。在高湿度、高不稳定、强垂直风切变的环流背景下,龙卷在台风外围雨带上微型超级单体右后侧钩状回波顶端的弱回波区中发展起来。具有高时空分辨率的广州X波段双极化相控阵雷达,不仅观测到超级单体的发展过程,还呈现出龙卷涡旋演变特征:单体风暴尾端在右后方入流加强作用下,逐渐形成钩状回波形态,此时对流层中低层2~3km高度附近的中气旋强度率先达到最大,随着旋转强度进一步加强和旋转中心高度逐步下降,低层强旋转特征越来越明显,当低层旋转速度达到峰值(超过21m·s^-1),旋转直径收缩到1km范围,地面出现EF2级以上龙卷,旋转速度对区域出现清晰的弱回波龙卷眼区特征。X波段双极化相控阵雷达在龙卷观测中优势显著,弥补了多普勒天气雷达观测的不足。

台风“山竹”期间深圳近地面水平风的垂直特征

基于深圳356 m气象梯度塔风速观测资料,采用统计分析的方法,以台风"山竹"为例分析了台风过程中深圳近地面水平风阵风因子、风廓线指数和湍流强度的垂直变化特征。结果表明:台风"山竹"影响期间,受城市下垫面影响近地面风湍流强度大于高层,阵风因子和湍流强度随高度变化符合指数规律,风速大于6级后逐渐趋于稳定;风廓线指数随高度增加、风速增大逐渐减小。此外,利用全部样本计算得到风廓线指数平均值约为0.23,符合《建筑结构荷载规范》的推荐范围,但利用该值推算近地面不同高度的风速值略大于实测值。

WRF大气模式与台风经验模型在超强台风“山竹”过程重构中的比较分析

通过中尺度气象研究与预报模式WRF(weather research and forecasting)和两种台风经验模型重构了2018年影响我国珠江口地区的超强台风“山竹”过程中的气压和风矢量场,在台风最佳路径数据的基础上开展了方法间的比较,并与香港、澳门和深圳三个国际机场的实测数据进行了对比分析,验证了三种模拟方案模拟台风“山竹”的可靠性。利用非结构网格半隐式跨尺度海洋模式SCHISM(semi⁃implicit cross⁃scale hydroscience integrated system model),将三种模拟气压和风场作为驱动场输入风暴潮模式中进行增水模拟试验,比较了它们在赤湾、三灶、横门和黄埔四个测站风暴潮增水中各自的效果,并进一步验证了WRF模式和两种经验模型模拟台风“山竹”的有效性。综合来看,WRF大气模式对气压、风速、风向及风暴增水模拟效果最佳,如果进一步优化该模式的各种参数化方案,可能还能提高其精度。如果不具备使用WRF大气模式的条件,台风经验1模型也是一个完全可以接受的、简单快捷的方案。

台风“山竹”期间GPM卫星降水产品的误差评估

利用CMORPHGC数据作为基准数据,采用7种统计指数对比分析了V6B IMERG多种产品基于台风“山竹”期间在中国大陆、华南和华东雨区的降水情况。结果表明:(1)IMERG对华南台风强降雨有一定的辨识能力而对华东地区强降雨的估测能力较差;(2)IMERG_FRCal在4个产品中表现最好且能很好反映台风降雨评估,在准实时产品中,IMERG_ERUnCal的空间降水估测能力较优,而IMERG_LRUnCal的时序分布特征及估测华东由台风带来的降雨量表现较好;(3)IMERG降水探测主要集中在降水率小于5mm·h^-1时,而在降水率大于30mm·h^-1时,中国大陆和华东雨区中仅有IMERG_ERUnCal和IMERG_FRCal评估能力较强而华南雨区的各IMERG产品均表现不足的探测能力。V6B IMERG在台风期间的降水误差中仍然存在有限的估测能力。

超强台风“山竹”(1822)的闪电活动特征

为了进一步认识热带气旋(TC)全生命期中闪电的活动特征,本文利用全球闪电定位网(WWLLN)资料、中央气象台的TC路径数据、风云四号A星(FY-4A)的相当黑体温度(TBB)数据和ERA5再分析资料,研究了2018年登陆中国的最强台风“山竹”从生成到消亡全生命期中闪电活动的时空分布和随强度的变化特征,探讨了闪电活动与风圈半径及下垫面的关系。结果表明:(1)“山竹”中的闪电活动有明显的三圈结构,内核闪电密度最大,内雨带几乎没有闪电,外雨带闪电数量最多。内核闪电与外雨带闪电的主要发生时间不同,外雨带在远海也能产生大量闪电。(2)闪电活动的方位分布与TC强度、所处地理位置及环境密切相关,不同时期闪电方位分布不同。(3)闪电活动与风圈半径没有明确的关系,闪电活动多发于风圈半径较小的东南和西南方位。(4)TC快速增强期间及前后,内核闪电活动对TC强度增强具有一定的指示作用。此外,内核闪电活动与对流强度呈现较好的相关性。(5)岛屿和陆地的存在对于强对流的发展有着极重要的作用。气流遇到较高地形被迫抬升,形成闪电。TC西南方位距岛屿东南侧约300 km的海面,水汽、热量充足且人为气溶胶较多,有利于上升气流的发展,进而产生闪电。这些认识有助于闪电资料在TC中小尺度强对流监测和预警中的应用。