Ensemble forecasting of tropical cyclone motion using a barotropic model. Part III: Combining perturbations of the environment and the vortex

Summary This is the third in a series of papers to investigate the applicability of the ensemble forecasting (EF) technique in the prediction of tropical cyclone (TC) motion. In the previous two papers, either the environment or the vortex was perturbed and the other unperturbed component was then merged onto the perturbed component at the initial time. In the present study, the separately-perturbed environment and vortex fields are combined at this time. The objective is to determine the extent to, and the synoptic pattern under which, such a combination can improve the TC motion forecast compared with perturbing only one component.The study makes use of the same barotropic model as the previous studies and the same dataset – 66 cases from the Tropical Cyclone Motion Experiment TCM90. Perturbations of the environment and those of the vortex are first generated separately using the breeding of growing modes (BGM) method, and then combined at the initial forecast time. The performance of this combined scheme, labeled as BGMC, is then compared with that of the scheme with only the environment or the vortex perturbations (termed BGME and BGMV, respectively).The BGMC distribution of ensemble forecast tracks are found to be basically similar to those in BGME but the spread is reduced. Some poor forecast members in BGME also become close to the best track in BGMC. The relative skill scores of the BGMC forecasts relative to the best track are almost all positive but those under the perfect model assumption are negative because the control forecast is better. While both BGMC and BGME schemes can improve TC forecast track under transition synoptic conditions, BGMC also achieve a higher success rate under complicated vortex and environment interactions. In general, the BGMC scheme is superior to the BGMV scheme.     

基于BGM与ETKF的台风"苏拉"(1209)集合预报的对比试验Ⅰ:路径预报

采用FNL再分析资料和美国联合台风警报中心(Joint Typhoon Warning Center,JTWC)资料,运用中尺度WRF(Weather Research and Forecasting)模式,分别使用增长模繁殖法(Breeding of Growing Mode,BGM)和集合卡尔曼变换方法(Ensemble Transform Kalman Filter,ETKF),对1209号台风"苏拉"进行了台风路径的集合预报试验,并对预报效果进行对比分析。结果表明:采用BGM或ETKF初始扰动的集合预报系统,集合平均预报对风场、温度场、位势高度场的预报效果均优于控制预报;ETKF方法的预报改进程度较BGM方法更大,且对风场和温度场预报技巧的优势尤为明显。BGM方法所得到的集合成员离散度小于ETKF方法,对大气真实状态的表征能力不及后者;两种扰动方法的集合平均都明显改善了台风"苏拉"的路径预报结果,尤其是控制预报在福建沿海第二次登陆后移速过快的问题,但对台风登陆位置预报的改进不明显;此外,采用ETKF方法的集合平均对台风"苏拉"路径预报的改进效果远优于采用BGM方法的集合平均预报。     

一次登陆台风的集合预报试验

选取0713号台风"韦帕"临近登陆过程为试验个例,在GRAPES_TCM模式基础上,采用增长模繁殖法(BGM)分别对台风涡旋场和环境场进行扰动来构造集合成员,进行集合预报,作为对台风数值预报方法的一种新的尝试。试验结果表明:通过BGM的动力调整后,成员间体现出不同的扰动形态,使得在后期的预报中产生合适的集合离散度。在台风登陆前后,大尺度平均位势高度场和风场以及集合系统的离散度均发生了明显的变化,可以看到大尺度环境场引导作用的差异使得成员间对台风路径的预报各不相同,体现了预报的不确定性。对路径预报而言,简单的算术平均并没有优于控制预报的表现,但通过聚类分析后,可以提高集合产品的使用效率。从中可以得到一点启发:怎样利用集合系统提供的大量信息值得进一步思考,聚类分析不失为一种改善集合预报产品利用效率的有效方法。     

AN ENSEMBLE FORECAST EXPERIMENT OF A LANDING TYPHOON

Based on the Global Regional Assimilation and Prediction System-Tropical Cyclone Model(GRAPES-TCM),an ensemble forecast experiment was performed,in which Typhoon Wipha during the period immediately prior to landfall was selected for the study and the breeding of growing mode(BGM) method was used to perturb the initial conditions of the vortex field and the environment field.The results of the experiment indicate that each member had a different initial status in BGM processing and they show a reasonable spread among members along with the forecast phase.Changes in the large-scale field,thermodynamic structure,and spread among members took place when Wipha made landfall.The steering effect of the large-scale field and the interaction between the thermodynamics and the dynamics resulted in different tracks of the members.Meanwhile,the forecast uncertainty increased.In summary,the ensemble mean did not perform as well as the control forecast,but the cluster mean provided some useful information,and performed better than the control in some instances.The position error was 34 km for 24 h forecast,153 km for 48 h forecast,and 191 km for 66 h forecast.The strike probability chart qualitatively described the forecast uncertainty.     

GRAPES区域集合预报条件性台风涡旋重定位方法研究

为了在集合预报中更合理描述台风涡旋中心定位的不确定性,采用2009—2018年中国气象局和日本气象厅台风最佳路径数据,分析台风最佳路径涡旋中心定位的不确定性特征,在此基础上设计条件性台风涡旋重定位方法（Conditional Typhoon Vortex Relocation,CTVR）,构建集合成员台风涡旋中心重定位阈值条件、台风涡旋分离数学处理及涡旋重定位等数学处理过程,利用中国气象局数值预报中心区域集合预报系统（Global/Regional Assimilation and Prediciton System-Regional Ensemble System,GRAPES-REPS）对2018年西北太平洋上的3个台风（1808号“玛莉亚”、1824号“谭美”和1825号“康妮”）进行轴对称结构和轴对称+非对称结构条件性台风涡旋重定位两种方案的集合预报试验和检验评估。结果表明:（1）中国气象局和日本气象厅台风最佳路径误差平均值为13.72 km,可视为台风涡旋中心定位不确定性的合理估计值;（2）统计检验结果和典型个例分析表明,采用轴对称结构和轴对称+非对称结构条件性台风涡旋重定位方法的台风集合预报路径误差及集合预报一致性结果比较接近;（3）条件性台风涡旋重定位方法可以有效改进GRAPES-REPS区域集合预报台风路径概率预报效果,如台风路径集合预报平均误差有所减小,集合预报一致性（路径离散度与路径均方根误差比值）增大,特别是预报初期概率预报效果改进更为显著,而预报中后期改进有限;（4）通过对“玛莉亚”台风集合预报诊断分析发现,经过条件性台风涡旋重定位后,各集合成员的台风路径误差在预报初期明显减小且路径收敛,但随着预报时效的延长台风路径逐渐发散。应用条件性台风涡旋重定位方法后,台风涡旋环流与大尺度环境场仍然比较连续协调,且台风涡旋环流外的大尺度环境场具有一致性特点,最低气压误差、最大风速误差和降水预报技巧基本不变。可见,条件性台风涡旋重定位方法的应用可以提供更准确的台风路径预报不确定性信息,帮助预报员做出更准确的预报决策。      

2009年夏季西太平洋台风路径和强度的多模式集成预报

基于TIGGE资料中的中国气象局、欧洲中期天气预报中心、日本气象厅和英国气象局等四个中心的2009年5月1日-8月31日台风预报资料,利用多模式集合平均、消除偏差集合平均和加权消除偏差集合平均等方法,对2009年8月1-31日预报期的西太平洋的台风路径和强度(中心气压)进行24～ 72 h预报时效的多模式集成预报,并对0907号台风“天鹅”和0908号台风“莫拉克”进行个例分析.结果表明:各中心对于不同时效的预报,预报技巧有明显差异.消除偏差集合平均与加权消除偏差集合平均显著地减小了预报误差,预报效果优于最好的单个中心预报和多模式集合平均.对于24 ～ 72 h预报,加权消除偏差集合平均方法始终表现出最好的预报性能.     

2011年“洛克”和“桑卡”双台风预报效果的初值试验研究

采用南海台风模式,对2011年业务预报误差较大的台风“洛克”（1115）和“桑卡”（1116）双台风的初值方案进行试验和研究,目的在于寻求改进预报的线索,从而提升台风模式性能。针对“洛克”和“桑卡”台风设计了几组初值方案对比试验,结果表明,仅对弱台风“桑卡”进行重定位和bogus的初值处理,与对双台风都进行初值处理相比较,两台风的路径预报误差减小。分析认为仅对弱台风作初值处理以改善其涡旋环流的影响是该双台风路径预报得以改进的原因。对2011—2012年所有弱台风进行批量预报试验,结果表明对弱台风采用重定位和bogus的初值处理,台风路径预报和强度预报的误差减小。对弱台风进行重定位和bogus初值处理,可改善模式对弱台风的预报效果。此外,目前南海台风模式中现有的bogus方法构造的涡旋相对于弱台风而言云顶偏高,可考虑发展针对弱台风的涡旋模型。      

A Relocation-based Initialization Scheme to Improve Track-forecasting of Tropical Cyclones简

A relocation procedure to initialize tropical cyclones was developed to improve the representation of the initial conditions and the track forecast for Panasonic Weather Solutions Tropical Operational Forecasts. This scheme separates the vortex perturbation and environment field from the first guess, then relocates the initial vortex perturbations to Lhe observed position by merging them with the environment field. The relationships of wind vector components with stream function and velocity potential are used for separating the vortex disturbance from first guess. For the separation of scalars, a low-pass Barnes filter is employed. The irregular-shaped relocation area corresponding to the specific initial conditions is determined by mapping the edge of the vortex radius in 36 directions.Then, the non-vortex perturbations in the relocation area are removed by a two-pass Barnes filter to retain the vortex perturbations, while the variable fields outside the perimeter of the modified vortex are kept ide.ntical to the original first guess. The potential impacts of this scheme on track forecasts were examined for three hurricane cases in the 2011-12 hurricane season. The experimental results demonstrate that the initialization scheme is able to effectively separate the vortex field from the environment field and maintain a relatively balanced and accurate relocated first guess. As the initial track error is reduced, the following track forecasts are considerably improved. The 72-h average track forecast error was redu,~ed by 32.6% for the cold-start cases, and by 38.4% when using the full-cycling data assimilation because of the accumulatedL improvements from the initialization scheme.     

Improvement of 6–15 Day Precipitation Forecasts Using a Time-Lagged Ensemble Method简

A time-lagged ensemble method is used to improve 6-15 day precipitation forecasts from the Beijing Climate Center Atmospheric General Circulation Model,version 2.0.1.The approach averages the deterministic predictions of precipitation from the most recent model run and from earlier runs,all at the same forecast valid time.This lagged average forecast （LAF） method assigns equal weight to each ensemble member and produces a forecast by taking the ensemble mean.Our analyses of the Equitable Threat Score,the Hanssen and Kuipers Score,and the frequency bias indicate that the LAF using five members at time-lagged intervals of 6 h improves 6-15 day forecasts of precipitation frequency above 1 mm d-1 and 5 mm d-1 in many regions of China,and is more effective than the LAF method with selection of the time-lagged interval of 12 or 24 h between ensemble members.In particular,significant improvements are seen over regions where the frequencies of rainfall days are higher than about 40％-50％ in the summer season; these regions include northeastern and central to southern China,and the southeastem Tibetan Plateau.     

热带气旋路径集合预报试验

以MM5模式为试验模式，分别用增长模繁殖法（BGM）和模式物理过程扰（MPP）形成12个集合成员，对2005年登陆我国的8个热带气旋进行了52次路径集合预报试验，以寻找适合西北太平洋热带气旋路径的集合预报方法。结果表明:BGM方法的集合预报结果总体上好于控制试验结果，其中对强度较弱的热带气旋的集合预报效果更好。MPP方法的集合预报结果总体上不如控制试验结果，但对初始时刻强度达到台风的热带气旋的集合预报效果较好，集合预报相对于控制试验的改进效果明显。基于BGM方法和MPP方法集合预报的不同特点，将两种方法相结合形成扰动成员，这一综合方法的集合预报效果好于单一方法的集合预报效果。BGM方法和MPP方法的系统发散度总体上都偏小。     

台风路径集合预报试验

基于T63L9模式,利用BGM法进行了台风路径的集合预报试验,并对集合预报中的一个关键技术—繁殖长度进行了研究。结果表明:相对于控制预报,利用增长模繁殖法制作的集合预报对台风路径预报的技巧水平有了很大提高。集合预报中采用不同的繁殖长度对台风路径预报效果有一定影响。繁殖长度取2 d和3 d集合预报效果相对于控制预报都有很大提高。繁殖长度取为2 d时,集合离散度较小,取为3 d时较合理,取为4 d时,离散度较大。对台风路径的预报采用集合选择平均后,繁殖2 d和繁殖3 d的集合预报系统的预报效果都优于控制预报。从综合集合预报效果分析,繁殖长度取为3 d更合适。当集合预报中繁殖长度取为3 d时,在预报的前3天,台风路径集合预报误差基本维持在100 km,第4天误差也只接近300 km。相对于控制预报,集合预报的改进率在预报的2～4 d基本超过了60%,甚至可达到70%。     

Assimilating AMSU-a radiance data with the WRF hybrid En3DVAR system for track predictions of Typhoon Megi (2010)

The impact of assimilating radiances from the Advanced Microwave Sounding Unit-A (AMSU-A) on the track prediction of Typhoon Megi (2010) was studied using the Weather Research and Forecasting (WRF) model and a hybrid ensemble three-dimensional variational (En3DVAR) data assimilation (DA) system. The influences of tuning the length scale and variance scale factors related to the static background error covariance (BEC) on the track forecast of the typhoon were studied. The results show that, in typhoon radiance data assimilation, a moderate length scale factor improves the prediction of the typhoon track. The assimilation of AMSU-A radiances using 3DVAR had a slight positive impact on track forecasts, even when the static BEC was carefully tuned to optimize its performance. When the hybrid DA was employed, the track forecast was significantly improved, especially for the sharp northward turn after crossing the Philippines, with the flow-dependent ensemble covariance. The flow-dependent BEC can be estimated by the hybrid DA and was capable of adjusting the position of the typhoon systematically. The impacts of the typhoon-specific BEC derived from ensemble forecasts were revealed by comparing the analysis increments and forecasts generated by the hybrid DA and 3DVAR. Additionally, for 24 h forecasts, the hybrid DA experiment with use of the full flow-dependent background error substantially outperformed 3DVAR in terms of the horizontal winds and temperature in the lower and mid-troposphere and for moisture at all levels.     

Impact of assimilating IASI radiance observations on forecasts of two tropical cyclones

The impact of assimilating Infrared Atmospheric Sounding Interferometer (IASI) radiance observations on the analyses and forecasts of Hurricane Maria (2011) and Typhoon Megi (2010) is assessed using Weather Research and Forecasting Data Assimilation (WRFDA). A cloud-detection scheme (McNally and Watts 2003) was implemented in WRFDA for cloud contamination detection for radiances measured by high spectral resolution infrared sounders. For both Hurricane Maria and Typhoon Megi, IASI radiances with channels around 15-μm CO₂ band had consistent positive impact on the forecast skills for track, minimum sea level pressure, and maximum wind speed. For Typhoon Megi, the error reduction appeared to be more pronounced for track than for minimum sea level pressure and maximum wind. The sensitivity experiments with 6.7-μm H₂O band were also conducted. The 6.7-μm band also had some positive impact on the track and minimum sea level pressure. The improvement for maximum wind speed forecasts from the 6.7-μm band was evident, especially for the first 42 h. The 15-μm band consistently improved specific humidity forecast and we found improved temperature and horizontal wind forecast on most levels. Generally, assimilating the 6.7-μm band degraded forecasts, likely indicating the inefficiency of the current WRF model and/or data assimilation system for assimilating these channels. IASI radiance assimilation apparently improved depiction of dynamic and thermodynamic vortex structures.     

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。      

集合方法在月动力预报信息提取中的应用

本工作将集合方法应用于提取月动力预报有用信息。利用中国气象局国家气候中心Ｔ６３Ｌ１６全球谱模式的５００百帕高度场月集合预报产品（集合成员数为８个，初始场的选取采用滞后方法（ＬＡＦ），即相邻两天的００００，０６００，１２００和１８００ＧＭＴ的初始化资料），就１９９７年１月至５月共１５次预报，分析了集合预报成员间的离散度与预报评分（距平相关系数和均方根误差）的关系，研究了用集合各成员预报离散度作为各个成员逐日预报的权重对月预报效果的影响。结果表明集合预报成员的离散度与预报评分有显著的相关，是有效预报长度Ｎ的一个很好估计；用离散度作为权重平均的月预报高度距平相关系数明显高于算术平均和线性权重，此外个例分析表明月平均环流及其异常的预报得到明显的提高。     

Tropical cyclone track and intensity prediction with a structure adjustable balanced vortex

A new Tropical Cyclone (TC) initialization method with the structure adjustable bogus vortex was applied to the forecasts of track, central pressure, and wind intensity for the 417 TCs observed in the Western North Pacific during the 3-year period of 2005–2007. In the simulations the Final Analyses (FNL) with 1° × 1° resolution of National Center for Environmental Prediction (NCEP) were incorporated as initial conditions. The present method was shown to produce improved forecasts over those without the TC initialization and those made by Regional Specialized Meteorological Center Tokyo. The average track (central pressure, wind intensity) errors were as small as 78.0 km (11.4 hPa, 4.9 m s^?1) and 139.9 km (12.4 hPa, 5.5 m s^?1) for 24-h and 48-h forecasts, respectively. It was found that the forecast errors are almost independent on the size and intensity of the observed TCs because the size and intensity of the bogus vortex can be adjusted to fit the best track data. The results of this study indicate that a bogus method is useful in predicting simultaneously the track, central pressure, and intensity with accuracy using a dynamical forecast model.     

A convection-allowing ensemble forecast based on the breeding growth mode and associated optimization of precipitation forecast

A convection-allowing ensemble forecast experiment on a squall line was conducted based on the breeding growth mode (BGM). Meanwhile, the probability matched mean (PMM) and neighborhood ensemble probability (NEP) methods were used to optimize the associated precipitation forecast. The ensemble forecast predicted the precipitation tendency accurately, which was closer to the observation than in the control forecast. For heavy rainfall, the precipitation center produced by the ensemble forecast was also better. The Fractions Skill Score (FSS) results indicated that the ensemble mean was skillful in light rainfall, while the PMM produced better probability distribution of precipitation for heavy rainfall. Preliminary results demonstrated that convection-allowing ensemble forecast could improve precipitation forecast skill through providing valuable probability forecasts. It is necessary to employ new methods, such as the PMM and NEP, to generate precipitation probability forecasts. Nonetheless, the lack of spread and the overprediction of precipitation by the ensemble members are still problems that need to be solved.     

基于增长模繁殖法的暴雨集合预报

采用WRF模式对2010年9月发生在河南省附近的一次暴雨过程进行了集合预报试验。用增长模繁殖方法(BGM)制作了集合预报方案1;为了充分利用背景场信息,结合时间滞后法,制定了集合预报方案2:滚动繁殖法;考虑到暴雨过程中天气形势的特殊性,结合区域空间特征,制定了集合预报方案3:区域繁殖法。这3组试验均对变量U、V、T、Q进行了初值扰动,加上控制预报,均产生了9个集合成员。试验结果表明:几种集合预报方法在预报效果上相较于控制预报都具有明显的改善,滚动繁殖法及区域繁殖法对增长模繁殖法都具有一定的改进作用,其中区域繁殖法的预报效果更优,与实况更为接近。     

热带气旋奇异向量在GRAPES全球集合预报中的初步应用

基于副热带奇异向量的初值扰动方法已应用于GRAPES （Global and Regional Assimilation PrEdiction System）全球集合预报系统,但存在热带气旋预报路径离散度不足的问题。通过分析发现,热带气旋附近区域初值扰动结构不合理导致预报集合不能较好地估计热带气旋预报的不确定性,是路径集合离散度不足的可能原因之一。通过建立热带气旋奇异向量求解方案,将热带气旋奇异向量和副热带奇异向量共同线性组合生成初值扰动,以弥补热带气旋区域初值扰动结构不合理这一缺陷,进而改进热带气旋集合预报效果。利用GRAPES全球奇异向量计算方案,以台风中心10个经纬度区域为目标区构建热带气旋奇异向量求解方案,针对台风“榕树”个例进行集合预报试验,并开展批量试验,利用中国中央气象台最优台风路径和中国国家气象信息中心的降水观测资料进行检验,对比分析热带气旋奇异向量结构特征和初值扰动特征,评估热带气旋奇异向量对热带气旋路径集合预报和中国区域24 h累计降水概率预报技巧的影响。结果表明,热带气旋奇异向量具有局地化特征,使用热带气旋奇异向量之后,热带气旋路径离散度增加,路径集合平均预报误差和离散度的关系得到改善,路径集合平均预报误差有所减小,集合成员更好地描述了热带气旋路径的预报不确定性;中国台风降水的小雨、中雨、大雨、暴雨各量级24 h累计降水概率预报技巧均有一定提高。总之,当在初值扰动的生成中考虑热带气旋奇异向量后,可改进热带气旋初值扰动结果,并有助于改善热带气旋路径集合预报效果。      

不同 AMDAR资料同化时间窗对台风“摩羯”预报影响研究

2018年第14号台风“摩羯”对山东造成了大范围暴雨和大风天气,基于WRF（Weather Research and Forecasting）模式及其Hybrid-3DVAR混合同化预报系统,对Hybrid-3DVAR不同集合协方差比例和不同航空气象数据转发（aircraft meteorological data relay,以下简称AMDAR）资料同化时间窗对台风“摩羯”预报的影响进行了数值研究。结果表明：加大集合协方差比例对台风“摩羯”路径预报有较大影响和改进;当全部取来自集合体的流依赖误差协方差时,预报的台风路径最好,降水预报也最接近实况;AMDAR资料同化对于台风路径和降水预报也有正的改进作用,但加大集合协方差比例到100%时对台风路径预报影响更大;不同资料同化时间窗会影响同化的AMDAR资料数量,从而影响台风降水精细化预报;45 min同化时间窗的要素预报误差最小,对台风造成的强降水精细特征预报最接近实况;不同资料同化时间窗主要影响台风降水预报落区分布,对台风路径预报影响相对较小。