基于观测路径的集合预报样本优选对热带气旋的模拟研究

集合预报是从一定误差范围内的一组初值出发,这组初值(样本)代表了大气状态的概率分布,集合预报中集合样本的好坏严重影响分析质量。质量较差样本进入集合预报中难免会降低集合预报的整体质量。由于集合样本是模拟大气可能状态的概率分布,因此样本的优选是提高分析质量的关键。通过对集合样本优胜劣汰来分析样本优选对模拟效果的影响。由于台风预报中台风路径的模拟至关重要,因此样本优选的方案为将样本模拟的路径信息与观测的台风报文路径相比较后,保留误差较低的样本,剔除误差较高的样本,从而提升样本的整体质量。但过多的样本被替换将导致集合离散度的大幅下降,因此替换样本的数量要适度。研究结果表明样本优选极可能有利于热带气旋路径和强度模拟的改进,其中对“妮妲”路径误差的改进为4% ~13%,对“鲇鱼”路径误差的改进为11%~28%,对“妮妲”的强度误差改进为5%~37%,“鲇鱼”的强度误差改进为1%~27%。      

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.     

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.     

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.     

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。      

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.     

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。      

对流尺度集合预报成员数对降水预报的影响北大核心CSCD

选取2022年川渝地区发生的16个强降水个例开展对流尺度集合预报批量试验,并通过对31组初值采用不同集合成员数时的降水集合预报技巧进行检验评估和综合分析。结果表明:集合成员的降水预报技巧总体上大致相当,因而采用不同成员数时预报技巧差异也不明显;表征降水总体分布特征的Talagrand分布和预报失误概率以及表征降水概率预报技巧的相对作用特征面积随着成员数的增加而逐渐改进,但当成员数达到一定数值后继续增大成员数对预报改进不明显。总体而言,对流尺度集合预报成员数设置为16~18最适宜。     

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。      

“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。     

西北太平洋TC移动速度异常及预报误差特征的分析

利用国家气象局和上海台风研究所(CMA-STI)整编的西北太平洋1970—2009年热带气旋(TC,Tropical Cyclone)及TC最佳路径数据集和2005—2010年的TC路径预报误差资料,应用百分位法,确定TC移动速度异常指标,分析了40 a来西北太平洋TC移动速度及其变化异常发生的时空分布特征,研究了TC速度预报误差对路径预报误差的影响及其与大尺度引导气流之间的关系。结果显示:1)西北太平洋TC移速及移速变化累积概率达95%(5%)分位数的阈值分别为10.8 m·s~(-1)(1.43 m·s~(-1))和2.42m·s~(-1)(-1.72 m·s~(-1))。2)快速移动及加速的TC大都出现在日本海地区,而缓慢的和减速移动TC主要出现在南海区域。3)TC移动速度异常的季节变化表现为,快速移动的TC在5月出现的频率达到最高,缓慢移动的TC在10月频率达到最高,加速移动的TC在6月频率达到最高。4)近6 a的TC移速预报误差对TC路径预报误差的贡献平均约为41.6%。5)对TC路径预报误差偏大,且移速预报误差贡献大的个例分析显示,该个例大尺度环境引导气流偏弱使TC移动速度偏慢。而如果预报的大尺度环境引导气流偏强,使预报的TC移速偏快,那么就容易导致大的路径预报误差。     

区域集合预报系统2 m温度预报的校准技术

采用非齐次高斯回归 (NGR) 技术对国家气象中心区域集合预报系统的2 m温度预报结果开展了一阶偏差和二阶离散度的校准研究。对预报结果比较详尽的检验分析表明:校准后的2 m温度预报可靠性和预报技巧均显著提高,表现为校准后集合预报成员的均方根误差与离散度更为接近;原Talagrand直方图中的“L”形分布现象得到有效改善;Brier评分、最小连续分级概率评分 (CRPS) 明显减小,相对作用特征 (ROC) 面积增大,说明校准后的2 m温度预报表现出更好的预报技能。此外,NGR技术与自适应误差订正技术的对比试验表明,NGR在消除集合平均偏差和提高集合离散度两个方面均有优势。     

西北太平洋热带气旋路径的历史模拟

基于IBTrACS提供的热带气旋最佳路径数据集,在统计分析历史热带气旋的发生年频次、发生位置、路径移动及强度变化等的基础上,建立了西北太平洋热带气旋轨迹合成模型。模型包括生成模型、移动模型、消亡模型及强度模型4个部分,并从地理轨迹密度、年登陆率、登陆风速分布三个方面,对模拟的气旋路径与历史气旋路径进行比较,以验证模型的准确性和可靠性。结果表明,构建的西北太平洋热带气旋全路径统计模拟模型稳健可靠,可进一步应用于研究区热带气旋的定量精细化的风险评估,能提高气旋风险灾害评估的可信度。     

西北太平洋热带气旋频次的延伸期动力-统计预报方法和评估

介绍了西北太平洋热带气旋(TC)频次的延伸期预报方法,比较了新构建的动力-统计和统计预报模型的预测技巧,并探讨了预报误差来源及改进方向。动力-统计预报模型是基于动力模式预测的热带季节内振荡(ISO)信号及ISO-TC生成的同期统计关系来进行预报;统计预报模型则是基于TC生成的前兆ISO信号建模预报。预报评估结果显示,动力-统计混合预报模型的预报技巧高于统计预报模型,原因在于影响TC次季节变化的前兆信号并不稳定,且随着预报超前时间迅速消散,无法提供有效且稳定的可预报源;相反地,TC生成与同期的ISO背景场显著相关,动力模式对ISO(预报因子)有较好的预报能力,因此动力-统计相结合的预报方法为TC延伸期预报提供了有效途径。虽然目前动力-统计预报模型的预报技巧可达5～6周,但仍有进一步改进和提高的空间。通过对不同类型TC预报技巧检验和误差分析,研究认为年际和年代际背景场对ISO调控TC活动的影响不可忽略,且热带外ISO信号(如罗斯贝波破碎和西风急流强度等)对TC频次和轨迹也有显著影响,这些因子为TC延伸期预报提供了潜在可预报源。     

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。     

Effect of Initial Vortex Intensity Correction on Tropical Cyclone Intensity Prediction:A Study Based on GRAPES_TYM

Predicting the intensity of tropical cyclones(TCs)is challenging in operational weather prediction systems,partly due to the difficulty in defining the initial vortex.In an attempt to solve this problem,this study investigated the effect of initial vortex intensity correction on the prediction of the intensity of TCs by the operational numerical prediction system GRAPES_TYM(Global and Regional Assimilation and Prediction System_Typhoon Model)of the National Meteorological Center of the China Meteorological Administration.The statistical results based on experiments using data for major TCs in 2018 show that initial vortex intensity correction can reduce the errors in mean intensity for up to 120-h integration,with a noticeable decrease in the negative bias of intensity and a slight increase in the mean track error.The correction leads to an increase in the correlation coefficient of Vmax(maximum wind speed at 10-m height)for the severe typhoon and super typhoon stages.Analyses of the errors in intensity at different stages of intensity(including tropical storms,severe tropical storms,typhoons,severe typhoons,and super typhoons)show that vortex intensity correction has a remarkable positive influence on the prediction of super typhoons from 0 to 120h.Analyses of the errors in intensity for TCs with different initial intensities indicate that initial vortex correction can significantly improve the prediction of intensity from 24 to 96 h for weak TCs(including tropical storms and severe tropical storms at the initial time)and up to 24 h for strong TCs(including severe typhoons and super typhoons at the initial time).The effect of the initial vortex intensity correction is more important for developing TCs than for weakening TCs.     

1949—2009年西北太平洋热带气旋气候特征

利用1949—2009年中国气象局热带气旋（TC:Tropical Cyclone）最佳路径数据集,对西北太平洋TC生成源地的时空分布、生成和登陆我国TC的年、月频数分布、强度分布和地理分布等气候特征进行统计分析。研究结果表明：在这61年中生成的TC呈减少趋势,登陆我国的TC数量比较稳定,不过近10年来登陆的较强TC数量却呈现出上升趋势;每年6—10月是TC高发期,强度等级越高的TC生成季节越偏晚,而8月是生成和登陆数量最多的月份;TC平均生命期随强度等级的增加而增大,且逐渐表现出单峰值分布特征;TC频数的地理分布以我国南海和菲律宾以东洋面为中心,向四周呈辐射状减少,近10年来其活动范围有所西伸加强。     

An Application of the Adjoint Method to a Statistical-Dynamical Tropical-Cyclone Prediction Model (SD-90) Ⅱ: Real Tropical Cyclone Cases

In the first paper in this series, a variational data assimilation of ideal tropical cyclone (TC) tracks was performed for the statistical-dynamical prediction model SD-90 by the adjoint method, and a prediction of TC tracks was made with good accuracy for tracks containing no sharp turns. In the present paper, the cases of real TC tracks are studied. Due to the complexity of TC motion, attention is paid to the diagnostic research of TC motion. First, five TC tracks are studied. Using the data of each entire TC track, by the adjoint method, five TC tracks are fitted well, and the forces acting on the TCs are retrieved. For a given TC, the distribution of the resultant of the retrieved force and Coriolis force well matches the corresponding TC track, i.e., when a TC turns, the resultant of the retrieved force and Coriolis force acts as a centripetal force, which means that the TC indeed moves like a particle; in particular, for TC 9911, the clockwise looping motion is also fitted well. And the distribution of the resultant appears to be periodic in some cases. Then, the present method is carried out for a portion of the track data for TC 9804, which indicates that when the amount of data for a TC track is sufficient, the algorithm is stable. And finally, the same algorithm is implemented for TCs with a double-eyewall structure, namely Bilis (2000) and Winnie (1997),and the results prove the applicability of the algorithm to TCs with complicated mesoscale structures if the TC track data are obtained every three hours.     

An Application of the Adjoint Method to a Statistical-Dynamical Tropical-Cyclone Prediction Model (SD–90) II: Real Tropical Cyclone Cases

In the first paper in this series, a variational data assimilation of ideal tropical cyclone (TC) tracks was performed for the statistical-dynamical prediction model SD-90 by the adjoint method, and a prediction of TC tracks was made with good accuracy for tracks containing no sharp turns. In the present paper, the cases of real TC tracks are studied. Due to the complexity of TC motion, attention is paid to the diagnostic research of TC motion. First, five TC tracks are studied. Using the data of each entire TC track, by the adjoint method, five TC tracks are fitted well, and the forces acting on the TCs are retrieved. For a given TC, the distribution of the resultant of the retrieved force and Coriolis force well matches the corresponding TC track, i.e., when a TC turns, the resultant of the retrieved force and Coriolis force acts as a centripetal force, which means that the TC indeed moves like a particle; in particular, for TC 9911, the clockwise looping motion is also fitted well. And the distribution of the resultant appears to be periodic in some cases. Then, the present method is carried out for a portion of the track data for TC 9804, which indicates that when the amount of data for a TC track is sufficient, the algorithm is stable. And finally, the same algorithm is implemented for TCs with a double-eyewall structure, namely Bilis (2000) and Winnie (1997), and the results prove the applicability of the algorithm to TCs with complicated mesoscale structures if the TC track data are obtained every three hours.