热带气旋闪电活动特征研究综述

针对热带气旋（tropical cyclone,TC）闪电已有研究,首先从闪电活动分布特征、眼壁闪电爆发对TC强度和路径的指示、外雨带闪电活动与雨带对流结构的关系三个方面进行了总结;其次从动力一微物理方面对TC闪电的形成原因和特征机理进行了梳理;最后提出当前研究中存在的两个关键问题,并对后续研究内容进行了展望。基于地基和空基相结合的综合闪电探测得到的闪电属性特征参量,有望建立一个明确的、具有代表性的闪电活动一TC强度变化关系。利用沿海地区架设的三维闪电定位系统结合地基双偏振霄达,针对登陆台风强对流过程开展的综合观测研究,将有助于推进闪电观测资料在台风中小尺度强对流监测、预警和资料同化中的应用。     

三维变分同化机载雷达资料对飓风预报的影响研究——2012年Isaac试验

随着气旋内部资料(Inner core data)在热带气旋预报中的使用,其重要性逐渐受到人们越来越多的关注。为了研究该资料中尾部机载雷达(Tail Doppler Radar,TDR)资料在业务系统中的应用效果,本文利用2012年飓风等级热带气旋Isaac期间的TDR资料,采用业务HWRF(Weather Research and Forecasting model for Hurricane)数值模式与业务GSI(Grid-point Statistical Interpolation system)三维变分同化(Three-Dimensional Variational Data Assimilation, 3DVar)系统对TDR资料进行了同化,展开了一系列预报试验,并对其效果进行了分析和研究。结果表明与HWRF的业务预报相比,GSI系统同化TDR资料后对热带气旋的路径和强度预报有明显改进;但其同化效果同时也表明业务三维变分中的静态背景误差协方差在TDR资料的应用中仍需要进一步的改进。     

2006年超级台风“桑美”强度与结构变化的数值模拟研究

使用一个高分辨率、非静力数值模式WRF模式对2006年超级台风Saomei强度和结构进行了数值模拟研究.首先,评估了Makin的粗糙度长度公式对台风Saomei强度和结构变化的影响,结果表明,采用新参数后,使得模拟的台风强度变化与实况最佳路径资料的强度变化更一致,对超级台风Saomei强度预报有改进;但对台风路径的影响不大.通过QuikSCAT、雷达和TRMM非常规资料的验证,进一步表明模拟的台风Saomei的结构与实况很接近,可以再现台风内核区域的部分"双眼墙"和"Annular"结构.其次,通过对台风Saomei边界层过程模拟的改进,表明在平均风速大于40 m/s时边界层各物理量明显改善,使得模式最大强度比传统的简单外推插值方案有显著改进,特别是在台风最强阶段,当台风Saomei眼墙区域的海表面拖曳系数C_d的相对变小,使得其眼墙区域的平均切向风速、径向风速、垂直风速、温度距平、涡旋动能和绝对角动量等物理量均有增强.表明台风Saomei眼墙氏域(20-40 km)各物理量的贡献对其强度和结构变化的影响十分重要.最后,在此基础上进一步分析模式海温和大尺度环境垂直风切变对台风Saomei强度和结构变化的可能影响,讨论了台风Saomei在其增强和消弱阶段中,大尺度环境垂直风切变对其强度变化的负反馈作用.     

热带气旋垂直倾斜度估算及在强度分析中的应用

该文给出了热带气旋暖心垂直倾斜度参数F_TC-VGP(TC vertical gradient parameter) 的定义。使用卫星微波遥感的温度垂直分布以及热带气旋最佳路径数据等资料,对2009—2011年典型热带气旋的暖心垂直倾斜度进行计算,并研究其与气旋强度变化的关系。结果表明:暖心垂直倾斜度参数F_TC-VGP变化与气旋自身强度变化有较好的对应性,该参数的变化能够明显地指示气旋强度增强、减弱以及强度突变, 能够指示环境场变化 (冷空气侵入) 等;其与气旋强度变化的周期不同,在强度增强或减弱阶段,倾斜度参数是经过快速适应性调整才完成了对热带气旋变化过程的贡献。因此,F_TC-VGP参数的计算和研究结果实现了对于热带气旋内部三维结构特征的定量描述,可以准确把握热带气旋强度和变化趋势,并对热带气旋的监测、预报具有一定业务参考价值。     

多源资料循环同化在台风“潭美”预报中的应用

为了检验不同观测资料在台风预报中的作用,以美国NCEP (National Centers for Environmental prediction)业务同化系统GSI (Grid Statistical Interpolation)为平台,选取2013年路径较复杂且登陆后降水持续较强的“潭美”台风过程为例,分别加入常规地面和高空观测资料、极轨卫星NOAA18、NOAA19、METOP-A和METOP-B资料,以及多普勒雷达基数据资料,探讨不同观测资料同化对台风的预报效果。同时,对台风采用Bogus初始化方案以及循环资料同化对台风路径和强度预报效果进行了对比分析。结果表明:常规观测资料对台风路径预报改善效果最明显,卫星资料的融入对海上台风路径的修正较好,而雷达资料则对台风登陆后的路径预报有改善;并且多源资料的融入效果最好。同时,采用Bogus方案可有效调整初始台风的位置和强度,从而对后期台风路径和强度预报有正效应。采用间隔6 h资料循环同化方法,可有效利用各时段资料,对台风路径和强度预报有较好的改善。      

全球数值模式中的台风初始化Ⅱ: 业务应用

由于缺少大量有效的观测资料,台风初始化对数值天气预报业务模式而言,仍然是一个悬而末决的难题.中国国家气象中心自从1996年将台风数值预报系统投入业务运行以来,一直使用经验的人造bogus涡旋台风初始化技术.实际上,不同时期的台风有着不同的环流结构,即使同一个台风在不同的生命期也具有不同的结构特征,而这些结构特征的差异并不能依靠现有的bogus涡旋技术体现出来,这种主观方法的统一性与台风在时空上的差异性形成了强烈的反差.最近,基于国家气象中心全球资料分析同化-预报循环系统,设计和发展了一套新的台风初始化业务方案,它主要由初始涡旋形成、涡旋重定位和涡旋调整3部分过程组成.相比于业务中使用的人造bogus涡旋台风初始化方案,新方案在很大程度上减少了人为因素对台风涡旋结构的影响,而更多地是依靠数值模式自身的动力和物理过程来协调约束产生三维空间的涡旋结构.应用新方案,文中对生成于西北太平洋的2006年0605号台风格美(Kaemi)进行了数值试验,初步分析表明,新方案在实现台风涡旋环流结构的初始化方面效果较好,同时,对台风格美多个时次的预报结果也显示,相比于业务使用的bogus方案而言,新方案对台风路径平均预报误差有了大幅度的降低.     

登陆台风强度变化过程预报的影响试验研究

探索了基于WRF模式的集合卡尔曼滤波同化方法（WRF-EnKF,简称EnKF）在近海有可能达到更强台风连续循环同化中国大陆高时空分辨率多普勒天气雷达径向风观测资料的效果,同时检验台风Vicente（2012）的三维结构演变及其动力学特征。通过短期集合预报得到跟随当前流场变化着的背景误差协方差的台风涡旋和动力学结构。研究发现,EnKF同化预报系统能有效地同化高时空分辨率雷达径向速度观测资料,显著改善初始场中台风Vicente的中小尺度内核结构,同时提高对台风Vicente的路径和强度及其相伴随的短期强降水预报。在台风最强时刻同化雷达径向风观测能快速（1~2 h）得到真实的暖核台风结构,同时进一步提高台风路径和强度的预报。另外,EnKF同化雷达径向风观测资料还能有效提高短期降水预报,1 h和3 h累积降水的分布、降水中心以及降水随时间演变都能得到显著改善,这与改善台风路径、结构和强度有密切关系。因此,对中国东南沿海有可能达到较强的台风进行同化雷达径向风观测资料可改善登陆台风的预报水平,这为利用我国地基多普勒天气雷达观测资料改善模式的初始场从而提高台风预报提供一定的指示作用。      

基于物理约束扰动的EnSRF雷达资料同化

在完善WRF集合均方根滤波同化系统的双向嵌套预报方案、雷达资料质量控制方案和多微物理过程积分方案的基础上,引入了一种扰动势函数、流函数的尺度较小、物理意义更明显的集合初始扰动新方案.通过台风“桑美”登陆过程中的多普勒雷达资料直接同化试验,对比新扰动方案与目前应用较多的背景误差协方差随机扰动和全场随机扰动方案,对集合滤波同化效果的影响.试验结果表明,3种初始扰动方案都有效改善了台风内部结构,但新方案由于尺度更小、结构更为合理,其同化效果也更为显著,提高了对台风路径、中心最低气压、最大风速及降水的预报质量.     

FY-4A卫星云导风观测误差优化及同化效果影响研究

为了推进FY-4A卫星资料在数值模式中的实际应用,本研究选择云导风产品作为研究对象,首先统计了FY-4A高层水汽通道和红外通道云导风的观测误差,进一步基于WRFDA(Weather Research and Forecasting model Data Assimilation system)系统,利用默认观测误差和新观测误差进行了为期一个月的循环同化及预报试验,并分析了试验期间的台风预报效果。结果表明:相较于默认观测误差,FY-4A云导风产品的新观测误差垂直结构特征更加明显;采用本研究统计的FY-4A云导风观测误差,能够在默认观测误差的基础上改善风场的分析和预报效果;试验期间的两个台风个例分析表明,新观测误差也能够减小台风路径的预报误差。     

FY-3A SATELLITE MICROWAVE DATA ASSIMILATION EXPERIMENTS IN TROPICAL CYCLONE FORECAST

China’s new generation of polar-orbiting meteorological satellite FY-3A was successfully launched on May 26,2008,carrying microwave sounding devices which had similar performance to ATOVS of NOAA series.In order to study the application of microwave sounding data in numerical prediction of typhoons and to improve typhoon forecasting,we assimilated data directly for numerical forecasting of the track and intensity of the 2009 typhoon Morakot(0908)based on the WRF-3DVar system.Results showed that the initial fields of the numerical model due to direct assimilation of FY-3A microwave sounding data was improved much more than that due to assimilation of conventional observations alone,and the improvement was especially significant over the ocean,which is always without conventional observations.The model initial fields were more reasonable in reflecting the initial situation of typhoon circulation as well as temperature and humidity conditions,and typhoon central position at sea was also adjusted.Through direct 3DVar assimilation of FY-3A microwave data,the regional mesoscale model improves the forecasting of typhoon track.Therefore,the FY-3A microwave data could efficiently improve the numerical prediction of typhoons.     

主分量分析在热带气旋强度客观预报中的试用

为了解主分量因子分析在热带气旋强度客观预报中的应用效能,在NCEP再分析资料、T106L19模式产品和热带气旋历史观测资料基础上,采用主分量因子分析技术,结合多元线性回归和BP型人工神经网络,开展了西北太平洋热带气旋的强度客观预报技术研究试验。试验包含完全预报法原理下的预报因子有无主分量分析、线性与非线性预报方法建模等方面的比较。结果表明,预报因子的主分量分析通过降低线性回归和BP人工神经网络模型的维数,提高因子间独立性,可减小模型强度预报平均绝对误差,提高模型实际预报能力。     

2018年西北太平洋台风活动特征和预报难点分析

利用1949—2018年中国气象局台风最佳路径、2018年中央气象台的台风路径强度实时预报、ECMWF数值预报以及NCEP逐日高分辨率海温RTG_SST(0.083°×0.083°)等资料,对2018年西北太平洋台风活动的主要特征和预报难点进行了分析。结果表明:2018年台风生成频数偏多,生成源地偏东,南海台风活跃;生成时间集中,盛夏台风异常偏多,台风群发性强,双台风或多台风共存活动频次偏多;台风生命史长,累积气旋能量偏高,超强台风偏多,但整体强度偏弱,较弱台风异常偏多;台风登陆频数和频次偏多,登陆地段偏北,且登陆台风强度明显偏弱。中央气象台24~120 h台风路径预报误差分别为72、124、179、262和388 km,各时效误差较2017年均有减少,特别是长时效路径预报误差明显减少;24~120 h台风强度预报误差分别为3.7、5.1、5.5、6.6和7.1 m·s^-1。由于双台风或多台风之间的相互作用、“鞍型场”等造成路径预报难度大以及多台风之间复杂水汽输送、近海台风强度变化不确定性大等原因,造成强度预报难度大。若采用更多观测资料、进行更深入的台风机理研究以及研发更有效的台风客观预报技术将是突破这些难点的有效途径。     

Initialization and simulation of a landfalling typhoon using a variational bogus mapped data assimilation (BMDA)

Summary Recently, a new data assimilation method called “3-dimensional variational data assimilation of mapped observation (3DVM)” has been developed by the authors. We have shown that the new method is very efficient and inexpensive compared with its counterpart 4-dimensional variational data assimilation (4DVar). The new method has been implemented into the Penn State/NCAR mesoscale model MM5V1 (MM5_3DVM). In this study, we apply the new method to the bogus data assimilation (BDA) available in the original MM5 with the 4DVar. By the new approach, a specified sea-level pressure (SLP) field (bogus data) is incorporated into MM5 through the 3DVM (for convenient, we call it variational bogus mapped data assimilation – BMDA) instead of the original 4DVar data assimilation. To demonstrate the effectiveness of the new 3DVM method, initialization and simulation of a landfalling typhoon – typhoon Dan (1999) over the western North Pacific with the new method are compared with that with its counterpart 4DVar in MM5. Results show that the initial structure and the simulated intensity and track are improved more significantly using 3DVM than 4DVar. Sensitivity experiments also show that the simulated typhoon track and intensity are more sensitive to the size of the assimilation window in the 4DVar than that in the 3DVM. Meanwhile, 3DVM takes much less computing cost than its counterpart 4DVar for a given time window.     

ECMWF资料和Bogus资料的2015年热带气旋结构的对比分析

利用ECMWF新推出的0.125 °高分辨率再分析资料对2015年出现在西北太平洋海域的所有被编号的热带气旋按强度进行分类分析,通过与Bogus对比发现该资料模拟的热带气旋整体表现良好,无论是对强台风以上级别、台风还是强热带风暴级以下热带气旋的温度场、高度场、湿度场和风场的刻画均比较符合热带气旋的实际发展状态,且该再分析资料既可获得热带气旋的非对称、精细结构,并且分辨率又与模式相匹配,有利于在未来的预报和同化分析中起到积极作用,以便最终应用于热带气旋的数值预报领域,进而取代Bogus模型。      

雷达反射率三维拼图观测资料在北方区域数值模式预报系统中的同化应用研究

以业务应用为目标,开展雷达反射率三维拼图观测资料在北方区域数值预报系统中的同化应用研究。采用雷达反射率间接同化方法同化北方雷达反射率拼图观测资料,重点关注其对降水、湿度、温度及风的预报能力影响。首先,基于2017年8月雷达拼图观测资料批量同化和对比试验,对雷达拼图资料同化应用效果进行定量评估,结果表明雷达拼图资料同化虽然加大了地面风场预报误差,但在降水预报和湿度、温度预报等方面有明显的改善作用。其次,选择在业务中预报难度较大的强降水个例开展分析研究,分析表明:（1）同化雷达拼图观测资料有效提高了模式降水预报性能,临近降水发生的循环起报时次预报效果更好;（2）对于短时间多次强降水过程发生的预报,循环同化雷达拼图资料可及时弥补模式中由于前次降水导致的水汽、能量等消耗及热/动力条件削弱,持续支持降水系统发展。最后,通过考察雷达反射率的不同同化方案,发现同化反演水凝物或者估计水汽均能改善模式降水预报性能,但是同化估计水汽对降水预报性能的改善更为明显,联合使用两方案能同时对水凝物分布、热力场等进行调整,可提高模式降水预报性能。      

Numerical Simulation of a Landfall Typhoon Using a Bogus Data Assimilation Scheme

A typhoon bogus data assimilation scheme (BDA) using dimension-reduced projection four-dimen-sional variational data assimilation (DRP-4-DVar),called DRP-BDA for short,is built in the Advanced Regional Eta Model (AREM).As an adjoint-free approach,DRP-BDA saves time,and only several minutes are taken for the full BDA process.To evaluate its performance,the DRP-BDA is applied to a case study on a landfall ty-phoon,Fengshen (2008),from the Northwestern Pacific Ocean to Guangdong province,in which the bogus sea level pressure (SLP) is assimilated as a kind of observa-tion.The results show that a more realistic typhoon with correct center position,stronger warm core vortex,and more reasonable wind fields is reproduced in the analyzed initial condition through the new approach.Compared with the control run (CTRL) initialized with NCEP Final (FNL) Global Tropospheric Analyses,the DRP-BDA leads to an evidently positive impact on typhoon track forecasting and a small positive impact on typhoon inten-sity forecasting.Furthermore,the forecast landfall time conforms to the observed landfall time,and the forecast track error at the 36th hour is 32 km,which is much less than that of the CTRL (450 km).     

Reanalysis of western Pacific typhoons in 2004 with multi-satellite observations

Summary A pilot tropical cyclone reanalysis project was conducted to construct a reliable, high temporal and spatial resolution tropical cyclone dataset for selected western Pacific typhoons in summer 2004, with the application of the latest satellite observations and a 4-dimensional variational data assimilation method. Primary data used for the reanalysis include SSM/I rain rate, GOES-retrieved upper-level wind, QuikSCAT surface wind, Aqua AIRS/AMSU retrieved temperature and moisture profiles, and JTWC best track data. A regular reanalysis procedure was established and up to 12 western Pacific typhoons have been reanalyzed. The reanalysis period covers the entire life cycle of a tropical cyclone, from a few days prior to its genesis to its final decay stage. A preliminary analysis shows that the reanalysis product significantly improves typhoon intensity, structure, and track, compared to the NCEP operational final analysis. The validation of the TC structure against independent observations shows that the reanalysis reproduces well the asymmetric characteristics of TC rain bands and cloud bands. A further modeling experiment with an initial condition from the reanalysis product reveals a significant improvement in typhoon intensity forecast compared to a parallel experiment with an initial condition from the NCEP final analysis, which provides a further indication of quality of the tropical cyclone reanalysis. The reanalysis product and the raw observational data will soon be posted on the data server of the IPRC Asia-Pacific Data-Research Center () for public use.     

IMPROVEMENT OF NUMERICAL SIMULATION OF TYPHOON RANANIM (0414) BY USING DOPPLER RADAR DATA

Typhoon Rananim (0414) has been simulated by using the non-hydrostatic Advanced Regional Prediction System (ARPS) from Center of Analysis and Prediction of Storms (CAPS). The prediction of Rananim has generally been improved with ARPS using the new generation CINRAD Doppler radar data. Numerical experiments with or without using the radar data have shown that model initial fields with the assimilated radar radial velocity data in ARPS can change the wind field at the middle and high levels of the troposphere; fine characteristics of the tropical cyclone (TC) are introduced into the initial wind, the x component of wind speed south of the TC is increased and so is the y component west of it. They lead to improved forecasting of TC tracks for the time after landfall. The field of water vapor mixing ratio, temperature, cloud water mixing ratio and rainwater mixing ratio have also been improved by using radar reflectivity data. The model’s initial response to the introduction of hydrometeors has been increased. It is shown that horizontal model resolution has a significant impact on intensity forecasts, by greatly improving the forecasting of TC rainfall, and heavy rainstorm of the TC specially, as well as its distribution and variation with time.     

基于集合Kalman滤波数据同化的热带气旋路径集合预报研究

构建了一个基于集合Kalman滤波数据同化的热带气旋集合预报系统，通过积云参数化方案和边界层参数化方案的9个不同组合，采用MM5模式进行了不同时间的短时预报。对预报结果使用“镜像法”得到18个初始成员，为同化提供初始背景集合。将人造台风作为观测场，同化后的结果作为集合预报的初值，通过不同参数组合的MM5模式进行集合预报。对2003～2004年16个台风个例的分析表明，初始成员产生方法能够对热带气旋的要素场、中心强度和位置进行合理扰动。同化结果使台风强度得到加强，结构更接近实际。基于同化的集合路径预报结果要优于未同化的集合预报。使用“镜像法”增加集合成员提高了预报准确度，路径预报误差在48小时和72小时分别低于200 km和250 km。     

Evaluation of radar and automatic weather station data assimilation for a heavy rainfall event in southern China

To improve the accuracy of short-term(0–12 h) forecasts of severe weather in southern China, a real-time storm-scale forecasting system, the Hourly Assimilation and Prediction System(HAPS), has been implemented in Shenzhen, China. The forecasting system is characterized by combining the Advanced Research Weather Research and Forecasting(WRF-ARW)model and the Advanced Regional Prediction System(ARPS) three-dimensional variational data assimilation(3DVAR) package. It is capable of assimilating radar reflectivity and radial velocity data from multiple Doppler radars as well as surface automatic weather station(AWS) data. Experiments are designed to evaluate the impacts of data assimilation on quantitative precipitation forecasting(QPF) by studying a heavy rainfall event in southern China. The forecasts from these experiments are verified against radar, surface, and precipitation observations. Comparison of echo structure and accumulated precipitation suggests that radar data assimilation is useful in improving the short-term forecast by capturing the location and orientation of the band of accumulated rainfall. The assimilation of radar data improves the short-term precipitation forecast skill by up to9 hours by producing more convection. The slight but generally positive impact that surface AWS data has on the forecast of near-surface variables can last up to 6–9 hours. The assimilation of AWS observations alone has some benefit for improving the Fractions Skill Score(FSS) and bias scores; when radar data are assimilated, the additional AWS data may increase the degree of rainfall overprediction.