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。      

台风路径数值预报实时订正技术及其集成应用

以台风路径数值预报的短时效预报偏差和目标时效（指所需订正的时效）的纬度预报为预报因子,采用多元线性回归方法建立了台风路径预报的偏差预估方程,继而对台风路径预报进行实时订正。本文以12 h为短时效,通过对欧洲中期天气预报中心确定性预报模式（ECMWF-IFS）和集合预报模式（ECMWF-EPS）的台风路径预报的应用,得到以下结论:2018年试报结果表明,24 h、36 h、48 h、60 h、72 h、84 h订正后的ECMWF-IFS台风路径预报的平均距离误差分别比订正前减小了7.3 km、9.3 km、8.9 km、6.5 km、6.9 km、2.6 km,总体来说较强台风（指12 h的台风强度实况≥32.7 m s?1）路径预报的订正效果更好。尝试了先对ECMWF-EPS各成员的台风路径预报进行订正,再进行集成预报,并对比了以下5种方式得到的台风路径预报:“订正后的确定性预报”、“所有集合预报成员集合平均”、“优选集合预报成员集合平均”、“所有集合预报成员先订正再集合平均”和“优选集合预报成员先订正再集合平均”,2018年试报结果表明,对于平均距离误差,24 h和36 h“优选集合预报成员先订正再集合平均”最小,48 h和60 h“所有集合预报成员先订正再集合平均”最小,72 h和84 h“优选集合预报成员集合平均”最小,如果在业务中有针对性地进行应用,有望获得一个在各预报时效表现都较优异的台风路径客观综合预报结果。24 h、36 h、48 h、60 h“优选集合预报成员先订正再集合平均”的平均距离误差分别比“所有集合预报成员集合平均”减小了13.3 km、11.7 km、10.0 km、7.6 km,比中央气象台官方预报（对应的时效为12 h、24 h、36 h、48 h）减小了0.7 km、2.0 km、3.9 km、2.4 km。     

不同背景场误差样本模拟方案对数值预报的影响——以“苏迪罗”台风为例

利用天气研究和预报模式(Weather Research and Forecasting Model,WRF)、WRF三维变分同化(Weather Research and Forecasting-Three-Dimensional Variational Data Assimilation,WRF-3DVAR)及美国国家气象中心(National Meteorological Center,NMC)方法,采用热启动循环同化和冷启动两种不同初值方案开展数值试验,探讨不同初值方案模拟的背景场误差样本对背景误差协方差及其同化预报效果产生的影响。结果表明:由不同初值方案模拟的背景场误差样本统计得到的背景误差协方差,其单点同化试验均符合理论模型,但二者分析增量场的差异较显著。对2015年"苏迪罗"台风降水个例进行的数值试验表明,不同初值方案模拟的背景场误差样本统计得到的背景误差协方差对同化分析场具有一定影响,进而对台风移动路径和台风降水的模拟产生了较显著的影响,但对台风强度和台风中心附近最大风速的影响不显著。4个不同起报时刻数值试验进一步表明,采用热启动循环同化背景场误差样本模拟方案统计的背景误差协方差,对"苏迪罗"台风路径和降水预报效果较好,其中对台风路径的影响主要体现在数值预报模式积分24 h之后。     

1604号台风“妮妲”近海加强垂直结构的诊断分析

1604号强台风"妮妲"(强台风级)于2016年8月2日03:35在广东省深圳市大鹏半岛登陆。采用中央气象台台风强度路径数据、NCEP/NCAR 1°×1°再分析资料,计算出台风"妮妲"中心附近的环境风垂直切变、相对涡度垂直切变、垂直速度、水汽通量等物理量,结果表明:1)台风"妮妲"具有明显的近海加强特征;"妮妲"中心附近存在呈纬向分布的垂直切变密集带,登陆前12~0 h密集带接近最密程度,"妮妲"中心垂直风切变平均值减小,台风强度增强,垂直风切变平均值增大,台风强度维持。2)"妮妲"中心附近相对涡度垂直切变增大,台风强度增强,相对涡度垂直切变减小,台风强度维持;"妮妲"中心附近垂直速度增大,台风强度维持或增强。3)"妮妲"中心上空的1 000~850 h Pa之间存在最大水汽通量净入流区。     

基于贝叶斯方案的雷达反射率反演水汽及其同化试验

雷达资料是目前为数不多有能力为高分辨率预报模式提供高分辨率信息资料的资料之一。为充分利用该资料所包含的中小尺度信息,文中基于雷达反射率,利用贝叶斯方法反演出大气相对湿度;将质控后的资料引入3Dvar系统进行同化分析,为高分辨率模式提供初值场。以台风“妮妲”登陆为例,通过一维反演及三维变分系统分析,有效地订正了实况有回波而模式预报无回波区域的大气湿度趋于合理,增加背景场的湿度,减小模拟回波比观测偏强的区域的大气湿度;同化大气湿度后模式在前6小时报出的台风外围回波分布、演变更合理,改进了降水雨带的分布与强度。1个月的批量试验反映1D+3Dvar同化雷达资料后,大气对流层中低层（850~400 hPa）增湿明显,其增湿影响程度可延续12小时以上。其逐时降水预报在前12小时的TS均比控制试验高,而大于5 mm以上降水预报偏差则与控制试验的大略一致或更接近1。      

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。     

GPS弯曲角资料在WRF模式中的同化试验——对台风“森拉克”的影响分析

实现了在WRF模式中GPS掩星弯曲角资料的三维变分同化,正演算子采用大气一维球对称假设条件下,Abel变换方法计算弯曲角。以2008年13号台风“森拉克”为例,研究了COSMIC弯曲角资料对台风预报路径、强度及降水等的影响。与控制试验及台风实况的对比结果表明,同化COSMIC弯曲角资料后,在24小时预报以后,对台风路径预报有较明显的改进效果,路径预报误差平均降低约67.5%;但台风强度预报整体偏弱。分析认为,同化弯曲角资料后,台风附近形势场的改进是提高路径预报的原因。由于弯曲角资料本身存在水平分辨率较低的问题,以及对流层底部信号质量不如中上部和平流层是台风强度预报偏弱的重要原因。      

基于混合集合同化方案的台风“海鸥”的数值模拟研究

混合变分/集合同化是基于变分+集合思路新兴发展起来的一种资料同化方法。利用WRF和WRFDA最新版本3.5构建混合集合同化的流程,通过单点试验直观体现出混合集合同化方案“流依赖”背景误差协方差的影响。对台风“海鸥”路径和强度的模拟和分析表明,混合集合同化方案在台风路径和强度的预报上要强于三维变分同化方案。对比两种方案同化后的分析场表明,混合集合同化方案分析出的台风中心强度优于三维变分同化方案分析结果,其原因一方面是混合集合同化方案初始场是采用集合平均的结果,另一方面是混合集合同化方案采用“流依赖”背景误差协方差的影响,这两个因素对台风的预报准确性有一定作用。      

基于混合集合—变分同化方案对台风“布拉万”模拟中协方差权重系数的选择

利用WRF以及WRFDA3.6.1的ETKF-3DVAR混合集合—变分同化方案,对2012年第15号台风"布拉万"进行了模拟,并分析协方差权重系数对"流依赖"属性和台风强度、路径的模拟效果的影响。通过单点实验发现:随着集合协方差权重系数增加,分析增量的"流依赖"属性就越发明显。当集合协方差权重系数大于0.5时,由于集合成员数量以及预报质量的限制,将会引入虚假的"流依赖"信息,使得分析增量的范围形状不再发生变化,强度有所减弱。在对台风"布拉万"路径和强度的模拟中发现:集合协方差权重系数取0.5以下的预报结果普遍好于系数大于0.5的预报结果,其中,当集合协方差权重系数取0.25时路径预报误差最小,当集合协方差权重系数取0.2时强度预报误差最小。     

2016年GRAPES_TYM改进及对台风预报影响

为了进一步提高国家气象中心区域模式台风数值预报系统（GRAPES_TYM）的预报能力,2016年对模式参考大气廓线以及涡旋初始化方案进行了改进:由模式初始场水平方向平均的一维参考大气代替原来的等温大气,涡旋初始化方案取消了原涡旋重定位并将涡旋强度调整半径由原来的12°减小到4°。对2014—2016年的生命史超过3 d的所有台风进行了回算,路径及近地面最大风速统计误差分析表明:参考大气的改进可以减小模式对台风预报路径预报的系统北偏和平均路径误差,尤其是140°E以东的转向台风。涡旋初始化方案中强度调整半径的减小会进一步减小模式预报路径的北偏趋势,从而进一步减小平均误差。同业务系统预报结果相比,改进后的GRAPES_TYM（包括参考大气和涡旋初始化）可以使平均路径误差分别减小10%（24 h）,12%（48 h）,16%（72 h）,14%（96 h）以及15%（120 h）。同美国NCEP全球模式路径预报相比,GRAPES_TYM在西行、西北行登陆我国的台风路径预报有一定优势。     

Sample Optimization of Ensemble Forecast to Simulate a Tropical Cyclone Using the Observed Track

Ensemble forecasting is widely used in numerical weather prediction. However, the ensemble may not satisfy a perfect Gaussian probability distribution because of a limited number of members, with some members significantly deviating from the true atmospheric state. Such outliers (belonging to low probability events) may downgrade the accuracy of an ensemble forecast. In this study, the observed track of a tropical cyclone (TC) is used to restrict the probability distribution of samples by investigating the evolution of TCs. Unlike data assimilation, the method we employed uses observational data. By restricting the probability distribution, ensemble spread could be decreased through sample optimization. In addition, the prediction results showed that track and intensity errors could be reduced by sample optimization. When the vertical structures of TCs considered in this study were compared, different thermal structures were found. This difference may have been caused by sample optimization, which may affect intensity and track. Nevertheless, it should be noted that the replacement of a large number of inferior samples may inhibit the improvement of simulated results.     

SAMPLE OPTIMIZATION OF ENSEMBLE FORECAST TO SIMULATE TROPICAL STORMS (MERBOK, MAWAR, AND GUCHOL) USING THE OBSERVED TRACK

Nowadays, ensemble forecasting is popular in numerical weather prediction (NWP). However, an ensemble may not produce a perfect Gaussian probability distribution owing to limited members and the fact that some members significantly deviate from the true atmospheric state. Therefore, event samples with small probabilities may downgrade the accuracy of an ensemble forecast. In this study, the evolution of tropical storms (weak typhoon) was investigated and an observed tropical storm track was used to limit the probability distribution of samples. The ensemble forecast method used pure observation data instead of assimilated data. In addition, the prediction results for three tropical storm systems, Merbok, Mawar, and Guchol, showed that track and intensity errors could be reduced through sample optimization. In the research, the vertical structures of these tropical storms were compared, and the existence of different thermal structures was discovered. One possible reason for structural differences is sample optimization, and it may affect storm intensity and track.     

The Simulation of Five Tropical Cyclones by Sample Optimization of Ensemble Forecasting Based on the Observed Track and Intensity

The quality of ensemble forecasting is seriously affected by sample quality. In this study, the distributions of ensemble members based on the observed track and intensity of tropical cyclones (TCs) were optimized and their influence on the simulation results was analyzed. Simulated and observed tracks and intensities of TCs were compared and these two indicators were combined and weighted to score the sample. Samples with higher scores were retained and samples with lower scores were eliminated to improve the overall quality of the ensemble forecast. For each sample, the track score and intensity score were added as the final score of the sample with weight proportions of 10 to 0, 9 to 1, 8 to 2, 7 to 3, 6 to 4, 5 to 5. These were named as "tr", "91", "82", "73", "64", and "55", respectively. The WRF model was used to simulate five tropical cyclones in the northwestern Pacific to test the ability of this scheme to improve the forecast track and intensity of these cyclones. The results show that the sample optimization effectively reduced the track and intensity error, "55" usually had better performance on the short-term intensity prediction, and "tr" had better performance in short-term track prediction. From the overall performance of the track and intensity simulation, "91" was the best and most stable among all sample optimization schemes. These results may provide some guidance for optimizing operational ensemble forecasting of TCs.     

Experiments of DSAEF_LTP Model with Two Improved Parameters for Accumulated Precipitation of Landfalling Tropical Cyclones over Southeast China

The Dynamical-Statistical-Analog Ensemble Forecast model for landfalling tropical cyclones (TCs) precipitation (DSAEF_LTP) utilises an operational numerical weather prediction (NWP) model for the forecast track, while the precipitation forecast is obtained by finding analog cyclones, and making a precipitation forecast from an ensemble of the analogs. This study addresses TCs that occurred from 2004 to 2019 in Southeast China with 47 TCs as training samples and 18 TCs for independent forecast experiments. Experiments use four model versions. The control experiment DSAEF_LTP_1 includes three factors including TC track, landfall season, and TC intensity to determine analogs. Versions DSAEF_LTP_2, DSAEF_LTP_3, and DSAEF_LTP_4 respectively integrate improved similarity region, improved ensemble method, and improvements in both parameters. Results show that the DSAEF_LTP model with new values of similarity region and ensemble method (DSAEF_LTP_4) performs best in the simulation experiment, while the DSAEF_LTP model with new values only of ensemble method (DSAEF_LTP_3) performs best in the forecast experiment. The reason for the difference between simulation (training sample) and forecast (independent sample) may be that the proportion of TC with typical tracks (southeast to northwest movement or landfall over Southeast China) has changed significantly between samples. Forecast performance is compared with that of three global dynamical models (ECMWF, GRAPES, and GFS) and a regional dynamical model (SMS-WARMS). The DSAEF_LTP model performs better than the dynamical models and tends to produce more false alarms in accumulated forecast precipitation above 250 mm and 100 mm. Compared with TCs without heavy precipitation or typical tracks, TCs with these characteristics are better forecasted by the DSAEF_LTP model.     

THE EFFECT OF SAMPLE OPTIMIZATION ON THE ENSEMBLE KALMAN FILTER IN FORECASTING TYPHOON RAMMASUN (2014)

In a limited number of ensembles, some samples do not adequately reflect the true atmospheric state and can in turn affect forecast performance. This study explored the feasibility of sample optimization using the ensemble Kalman filter (EnKF) for a simulation of the 2014 Super Typhoon Rammasun, which made landfall in southern China in July 2014. Under the premise of sufficient ensemble spread, keeping samples with a good fit to observations and eliminating those with poor fit can affect the performance of EnKF. In the sample optimization, states were selected based on the sample spatial correlation between the ensemble state and observations. The method discarded ensemble states that were less representative and, to maintain the overall ensemble size, generated new ensemble states by reproducing them from ensemble states with a good fit by adding random noise. Sample selection was performed based on radar echo data. Results showed that applying EnKF with optimized samples improved the estimated track, intensity, precipitation distribution, and inner-core structure of Typhoon Rammasun. Therefore, the authors proposed that distinguishing between samples with good and poor fits is vital for ensemble prediction, suggesting that sample optimization is necessary to the effective use of EnKF.     

登陆热带气旋路径和强度预报的效益评估初步研究

近年来有关热带气旋(TC)灾情的评估指标和方法的研究取得明显进展,但较少涉及TC预报对减少灾害损失的贡献(即效益)分析。基于中央气象台的TC实时路径和强度预报,针对登陆中国大陆的TC,初步分析了TC的路径和强度预报误差与其造成的直接经济损失之间的可能关系,并在此基础上建立了包含TC路径和强度预报误差的TC直接经济损失的预估模型。TC登陆前后24 h的路径和强度预报误差与TC所致直接经济损失均呈正相关关系;对于单个登陆TC而言,若24 h TC路径预报误差每减小1 km可减少因灾直接经济损失约0.97亿元,若强度预报每减小1 m/s可减少因灾直接经济损失约3.8亿元(以2014年为基准年)。可见,提高TC路径和强度预报精度对于减灾的效益巨大,且当前尤以提高强度预报能力的效益为佳。      

“非bogus初值”热带气旋数值预报及其性能

从高分辨模式特点及精细预报的需要出发，尝试了用“非bogus初值”开展热带气旋精细数值预报的方案。即直接采用四维同化形成的热带气旋（TC）初值，而不再加入“人造台风”（BOGUS）信息，以图避免人为理想结构带来的虚假信息，对热带气旋路径、强度、结构等有更为精细和准确的预报。用2001年所有影响华南的TC实例，对方案的可行性进行了分析。结果表明，本方案可以较好地预报TC的生成；路径预报准确率较高，对疑难路径及局地效应反映较为细致，路径预报误差随时效增大不显著；强度趋势预报指示意义强，准确率较高；尤其是能很好地反映TC的云、雨、风等的非对称结构、螺旋结构等特征的时空演化，对TC中尺度结构的刻画能力和预报可用性较强。显示了方案的优越性和发展潜力，也意味着“非bogus初值”方案应该作为未来TC数值预报发展的一个主要技术方向。分析表明目前条件下本方案还存在一些不足之处，主要表现在因初始信息的不足，当在TC过弱、初生或远离大陆等情况下，常会出现初始场中TC位置和强度与实况偏差过大，容易造成较大预报误差。     

Ensemble Forecast for Tropical Cyclone Based on CNOP-P Method: A Case Study of WRF Model and Two Typhoons

In this paper, we set out to study the ensemble forecast for tropical cyclones. The case study is based on the Conditional Nonlinear Optimal Perturbation related to Parameter (CNOP-P) method and the WRF model to improve the prediction accuracy for track and intensity, and two different typhoons are selected as cases for analysis. We first select perturbed parameters in the YSU and WSM6 schemes, and then solve CNOP-Ps with simulated annealing algorithm for single parameters as well as the combination of multiple parameters. Finally, perturbations are imposed on default parameter values to generate the ensemble members. The whole proposed procedures are referred to as the Perturbed Parameter Ensemble (PPE). We also conduct two experiments, which are control forecast and ensemble forecast, termed Ctrl and perturbed-physics ensemble (PPhyE) respectively, to demonstrate the performance for contrast. In the article, we compare the effects of three experiments on tropical cyclones in aspects of track and intensity, respectively. For track, the prediction errors of PPE are smaller. The ensemble mean of PPE filters the unpredictable situation and retains the reasonably predictable components of the ensemble members. As for intensity, ensemble mean values of the central minimum sea-level pressure and the central maximum wind speed are closer to CMA data during most of the simulation time. The predicted values of the PPE ensemble members included the intensity of CMA data when the typhoon made landfall. The PPE also shows uncertainty in the forecast. Moreover, we also analyze the track and intensity from physical variable fields of PPE. Experiment results show PPE outperforms the other two benchmarks in track and intensity prediction.     

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...     

GRAPES区域集合预报系统对登陆台风预报的检验评估

针对2015年7—9月登陆中国大陆沿海的台风,利用GRAPES-REPS区域集合预报资料和集合统计诊断分析方法,对登陆台风的移动路径、时间、地点、强度和降水等进行检验评估,以期为预报员应用GRAPES登陆台风概率预报提供依据。检验结果表明,(1)集合平均移动路径要优于控制预报,集合预报各成员登陆地点存在20~340 km差异,但实况登陆地点均能落在集合成员登陆地点中。(2)对24 h和48 h登陆地点误差而言,集合平均较控制预报更接近实况。(3)随着预报时间的趋近,集合平均、控制预报和集合成员登陆地点距离误差逐渐缩小,登陆地点空间位置预报也没有明显的系统性误差。(4)集合成员对台风登陆时间预报偏早,平均提前2.3 h。(5)在强度预报中,尽管最低气压和近中心最大风速存在登陆前偏弱而登陆后偏强的趋势,但登陆点预报值区间包含了实况观测值,表明GRAPES-REPS集合预报能够较好展示多种可能信息。(6)不同量级降水AROC评分为0.56~0.76,具有预报参考价值;另外AROC评分的高低及台风暴雨落区的准确性与台风登陆点和登陆时间误差密切相关。可见,GRAPES-REPS区域集合预报可以在台风登陆地点、时间、强度和降水预报等方面提供更多的预报不确定性信息,有助于做出正确的预报决策。