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1.
2013年欧洲中心台风集合预报的检验   总被引:1,自引:0,他引:1  
广州中心气象台利用中国气象局下发的欧洲中心台风集合预报数据,制作了台风集合预报产品,供业务参考应用。利用欧洲中心台风集合预报数据,对2013年1307—1331号热带气旋的集合预报路径和强度进行检验,通过对比集合平均、模式高分辨率确定性预报和预报员主观预报,发现路径集合平均在24~120 h预报误差最小;在有限的预报样本数中,从热带风暴到台风级别的热带气旋,各预报时效路径集合平均的误差随强度增强而减小;强引导气流背景下的热带气旋预报误差小于弱引导气流的误差。对比强度集合平均和模式高分辨率确定性预报,发现各时效集合平均的误差比确定性预报大,随着预报时效的延长误差没有明显增大或减小的趋势,而且强度集合平均预报,在中心最低气压、中心最大风速、热带气旋等级都表现出明显的系统性偏弱特征;对不同级别的热带气旋强度预报,集合平均的误差随强度增强而增大,即强度集合预报对强度较弱的热带气旋有更高的准确率;对比受强、弱引导气流影响的两类热带气旋,集合平均对受弱引导气流影响的一类预报误差更小。  相似文献   

2.
The objective of this study is to provide evidence of predictability on intraseasonal time scales (10–30 days) for western North Pacific tropical cyclone formation and subsequent tracks using the 51-member ECMWF 32-day forecasts made once a week from 5 June through 25 December 2008. Ensemble storms are defined by grouping ensemble member vortices whose positions are within a specified separation distance that is equal to 180 n mi at the initial forecast time t and increases linearly to 420 n mi at Day 14 and then is constant. The 12-h track segments are calculated with a Weighted-Mean Vector Motion technique in which the weighting factor is inversely proportional to the distance from the endpoint of the previous 12-h motion vector. Seventy-six percent of the ensemble storms had five or fewer member vortices. On average, the ensemble storms begin 2.5 days before the first entry of the Joint Typhoon Warning Center (JTWC) best-track file, tend to translate too slowly in the deep tropics, and persist for longer periods over land. A strict objective matching technique with the JTWC storms is combined with a second subjective procedure that is then applied to identify nearby ensemble storms that would indicate a greater likelihood of a tropical cyclone developing in that region with that track orientation. The ensemble storms identified in the ECMWF 32-day forecasts provided guidance on intraseasonal timescales of the formations and tracks of the three strongest typhoons and two other typhoons, but not for two early season typhoons and the late season Dolphin. Four strong tropical storms were predicted consistently over Week-1 through Week-4, as was one weak tropical storm. Two other weak tropical storms, three tropical cyclones that developed from precursor baroclinic systems, and three other tropical depressions were not predicted on intraseasonal timescales. At least for the strongest tropical cyclones during the peak season, the ECMWF 32-day ensemble provides guidance of formation and tracks on 10–30 day timescales.  相似文献   

3.
This study explored the impact of coastal radar observability on the forecast of the track and rainfall of Typhoon Morakot(2009)using a WRF-based ensemble Kalman filter(EnKF)data assimilation(DA)system.The results showed that the performance of radar EnKF DA was quite sensitive to the number of radars being assimilated and the DA timing relative to the landfall of the tropical cyclone(TC).It was found that assimilating radial velocity(Vr)data from all the four operational radars during the 6 h immediately before TC landfall was quite important for the track and rainfall forecasts after the TC made landfall.The TC track forecast error could be decreased by about 43% and the 24-h rainfall forecast skill could be almost tripled.Assimilating Vr data from a single radar outperformed the experiment without DA, though with less improvement compared to the multiple-radar DA experiment.Different forecast performances were obtained by assimilating different radars, which was closely related to the first-time wind analysis increment, the location of moisture transport, the quasi-stationary rainband, and the local convergence line.However, only assimilating Vr data when the TC was farther away from making landfall might worsen TC track and rainfall forecasts.Besides, this work also demonstrated that Vr data from multiple radars, instead of a single radar, should be used for verification to obtain a more reliable assessment of the EnKF performance.  相似文献   

4.
陈博宇  郭云谦  代刊  钱奇峰 《气象》2016,42(12):1465-1475
本文以2013—2015年主要登陆台风暴雨过程为研究对象,利用ECMWF降水和台风路径集合预报以及中央气象台实时业务台风中心定位资料,在统计分析的基础上,提出一种业务上可用的针对单模式集合预报的台风降水实时订正技术(简称集合成员优选技术)。结果表明,在登陆台风暴雨过程预报中,集合成员优选技术对改进集合统计量降水产品有明显的帮助,并较ECMWF确定性预报产品有一定优势;该方法对改进短期时效预报产品的效果优于中期时效预报,对大暴雨评分的改进高于暴雨和大雨评分。另外,本文基于概率匹配平均(Probability Matching average,PM)和融合(FUSE)产品的计算原理,提出融合匹配平均(Fuse Matching average,FM)产品,结果表明,对36 h时效预报,优选10~15个成员的PM产品TS(Threat Scores)评分可达最优,大暴雨评分较确定性预报提高近10%;对60和84 h时效预报,FM产品大暴雨评分较确定性预报提高超过20%。  相似文献   

5.
为提升GRAPES_TYM对西北太平洋和中国南海热带气旋路径及强度的预报能力、增加对北印度洋热带气旋的预报,2019年8月GRAPES_TYM 3.0版投入业务运行。GRAPES_TYM 3.0版的模式垂直分层由GRAPES_TYM 2.2版的50层增加到68层;预报区域由覆盖西北太平洋、中国南海扩展到覆盖北印度洋。试验结果显示:模式垂直分层增加可以改进模式对强台风及超强台风的预报能力,减小平均路径预报误差、显著减小平均强度预报误差以及强度预报负偏差;模式预报区域扩大到覆盖北印度洋对平均路径误差和平均强度误差影响不显著,但长时效预报比较敏感,如20°N以北热带气旋120 h预报路径。2016—2018年的回算结果与NCEP-GFS和ECMWF的预报结果对比分析表明:GRAPES_TYM 3.0版的平均路径误差与NCEP-GFS接近,同ECMWF相比误差较大;但24—96 h强度预报误差明显小于NCEP-GFS和ECMWF,NCEP-GFS和ECMWF对热带气旋强度预报存在明显的负偏差。综上所述,模式垂直分层由50层增加到68层对热带气旋强度预报至关重要,而长时效路径预报对模式预报区域扩大到覆盖北印度洋更为敏感。   相似文献   

6.
This paper proposes a method for multi-model ensemble forecasting based on Bayesian model averaging (BMA), aiming to improve the accuracy of tropical cyclone (TC) intensity forecasts, especially forecasts of minimum surface pressure at the cyclone center (Pmin). The multi-model ensemble comprises three operational forecast models: the Global Forecast System (GFS) of NCEP, the Hurricane Weather Research and Forecasting (HWRF) models of NCEP, and the Integrated Forecasting System (IFS) of ECMWF. The mean of a predictive distribution is taken as the BMA forecast. In this investigation, bias correction of the minimum surface pressure was applied at each forecast lead time, and the distribution (or probability density function, PDF) of Pmin was used and transformed. Based on summer season forecasts for three years, we found that the intensity errors in TC forecast from the three models varied significantly. The HWRF had a much smaller intensity error for short lead-time forecasts. To demonstrate the proposed methodology, cross validation was implemented to ensure more efficient use of the sample data and more reliable testing. Comparative analysis shows that BMA for this three-model ensemble, after bias correction and distribution transformation, provided more accurate forecasts than did the best of the ensemble members (HWRF), with a 5%–7% decrease in root-mean-square error on average. BMA also outperformed the multi-model ensemble, and it produced “predictive variance” that represented the forecast uncertainty of the member models. In a word, the BMA method used in the multi-model ensemble forecasting was successful in TC intensity forecasts, and it has the potential to be applied to routine operational forecasting.  相似文献   

7.
两个集合预报系统对秦岭及周边降水预报性能对比   总被引:2,自引:1,他引:1       下载免费PDF全文
利用欧洲中期天气预报中心 (ECMWF)、美国大气环境预报中心 (NCEP) 集合预报系统 (EPS) 降水量预报资料,CMORPH (NOAA Climate Prediction Center Morphing Method) 卫星与全国3万个自动气象站降水量融合资料,基于技巧评分、ROC (relative operating characteristic) 分析等方法,对比两个集合预报系统对秦岭及周边地区的降水预报性能。结果表明:两个系统均能较好表现降水量的空间形态,对于不同量级降水,ECMWF集合预报系统0~240 h控制及扰动预报优于NCEP集合预报系统,但NCEP集合预报系统264~360 h预报时效整体表现更好; ECMWF集合预报系统0~120 h大雨集合平均优于NCEP集合预报系统,两个系统集合平均的预报技巧整体低于其控制及扰动成员预报,这种现象ECMWF集合预报系统表现更为显著; ECMWF集合预报系统降水预报概率优于NCEP集合预报系统。ROC分析显示,随着预报概率的增大,ECMWF集合预报系统在命中率略微下降的情况下,显著减小了空报率,NCEP集合预报系统则表现出高空报、高命中率。  相似文献   

8.
西北太平洋(含南海)热带气旋路径集成预报分析   总被引:2,自引:1,他引:1  
基于2004—2009 年中国中央气象台、日本气象厅、美国联合台风警报中心、欧洲中心对西北太平洋和南海编号热带气旋主客观预报资料,利用算术平均、多元回归以及历史平均误差等三种集成方法,建立了热带气旋路径集成预报业务化系统。通过2007—2009 年的业务运行结果分析发现,欧洲中心客观预报参与的24、48 和72 h 集成比主观预报三个成员集成预报水平分别提高约2%、3%~5%和3%~5%,减小误差2.5 km左右、6~9 km 和10~12 km。技巧分析发现,24~72 h 集成预报有正技巧,多元回归集成技巧相对稍低,而算术平均和以各成员平均误差的平方倒数为权重系数的集成技巧对于各集成成员来说技巧差异不大。96 h 集成预报对欧洲中心的客观预报没有正技巧。   相似文献   

9.
The impacts of AMSU-A and IASI (Infrared Atmospheric Sounding Interferometer) radiances assimila-tion on the prediction of typhoons Vicente and Saola (2012) are studied by using the ensemble transform ...  相似文献   

10.
基于集合Kalman滤波数据同化的热带气旋路径集合预报研究   总被引:1,自引:2,他引:1  
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。  相似文献   

11.
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.  相似文献   

12.
The performance of the ECMWF 32-day ensemble predictions of western North Pacific tropical cyclone events (formation plus track) made once a week during the 2009 season is evaluated with the same procedures as for the 2008 season. Seventeen of the 23 tropical cyclones during the 2009 season occurred during multiple storm scenarios that are more difficult to predict, and many of the deficient track predictions involved unusual and rapidly changing tracks that typically involve interactions with adjacent synoptic circulations that are not predictable on intraseasonal timescales (10–30 days). Such incorrect predictions of the duration and tracks of these multiple cyclones were found to degrade the performance in predicting subsequent tropical cyclone formations and tracks during the 32-day integration. Predominantly northward tracks throughout the life cycle tended to be less predictable on intraseasonal timescales. Given these caveats, the overall performance of the ECMWF ensemble for the 12 typhoons was more successful than during the 2008 season. However, the performance for three tropical storms during the 2009 season was less successful due to the difficult track forecast scenarios. A surprisingly good performance was found in predicting the formation location and early track segments of eight minimal tropical storms or tropical depressions. The less satisfactory aspect for many of the late season tropical depressions was that the ECMWF ensemble continued to predict member vortices for extended periods after the system had actually dissipated.  相似文献   

13.
A dual-resolution(DR) version of a regional ensemble Kalman filter(EnKF)-3D ensemble variational(3DEnVar) coupled hybrid data assimilation system is implemented as a prototype for the operational Rapid Refresh forecasting system. The DR 3DEnVar system combines a high-resolution(HR) deterministic background forecast with lower-resolution(LR) EnKF ensemble perturbations used for flow-dependent background error covariance to produce a HR analysis. The computational cost is substantially reduced by running the ensemble forecasts and EnKF analyses at LR. The DR 3DEnVar system is tested with 3-h cycles over a 9-day period using a 40/13-km grid spacing combination. The HR forecasts from the DR hybrid analyses are compared with forecasts launched from HR Gridpoint Statistical Interpolation(GSI) 3D variational(3DVar)analyses, and single LR hybrid analyses interpolated to the HR grid. With the DR 3DEnVar system, a 90% weight for the ensemble covariance yields the lowest forecast errors and the DR hybrid system clearly outperforms the HR GSI 3DVar.Humidity and wind forecasts are also better than those launched from interpolated LR hybrid analyses, but the temperature forecasts are slightly worse. The humidity forecasts are improved most. For precipitation forecasts, the DR 3DEnVar always outperforms HR GSI 3DVar. It also outperforms the LR 3DEnVar, except for the initial forecast period and lower thresholds.  相似文献   

14.
Extending an earlier study, the best track minimum sea level pressure (MSLP) data are assimilated for landfalling Hurricane Ike (2008) using an ensemble Kalman filter (EnKF), in addition to data from two coastal ground-based Doppler radars, at a 4-km grid spacing. Treated as a sea level pressure observation, the MSLP assimilation by the EnKF enhances the hurricane warm core structure and results in a stronger and deeper analyzed vortex than that in the GFS (Global Forecast System) analysis; it also improves the subsequent 18-h hurricane intensity and track forecasts. With a 2-h total assimilation window length, the assimilation of MSLP data interpolated to 10-min intervals results in more balanced analyses with smaller subsequent forecast error growth and better intensity and track forecasts than when the data are assimilated every 60 minutes. Radar data are always assimilated at 10-min intervals. For both intensity and track forecasts, assimilating MSLP only outperforms assimilating radar reflectivity (Z) only. For intensity forecast, assimilating MSLP at 10-min intervals outperforms radar radial wind (Vr) data (assimilated at 10-min intervals), but assimilating MSLP at 60-min intervals fails to beat Vr data. For track forecast, MSLP assimilation has a slightly (noticeably) larger positive impact than Vr(Z) data. When Vr or Z is combined with MSLP, both intensity and track forecasts are improved more than the assimilation of individual observation type. When the total assimilation window length is reduced to 1h or less, the assimilation of MSLP alone even at 10-min intervals produces poorer 18-h intensity forecasts than assimilating Vr only, indicating that many assimilation cycles are needed to establish balanced analyses when MSLP data alone are assimilated; this is due to the very limited pieces of information that MSLP data provide.  相似文献   

15.
基于TIGGE资料的东亚地面气温预报的不一致性研究   总被引:1,自引:0,他引:1       下载免费PDF全文
基于TIGGE资料中欧洲中期天气预报中心(ECMWF)、美国国家环境预报中心(NCEP)和中国气象局(CMA)3个集合预报系统的地面气温集合预报资料,运用跳跃指数研究了3个集合预报系统中东亚地面气温的控制预报及集合平均预报的不一致性。结果表明,各个集合预报系统地面气温预报的时间平均不一致性指数差异较大。ECM WF时间不一致性指数最小,NCEP次之,CM A最大。另外NCEP的控制预报、ECM WF的控制预报和集合平均预报,这三者的时间平均不一致性指数随预报时效延长而增加,且集合平均预报一致性优于控制预报。而对于CMA预报的不一致性,无论是控制预报还是集合平均预报总体上都稳定地保持在较高的水平。此外,ECMWF的地面气温冬(夏)季预报的不一致性相对较强(弱),且单点跳跃随预报时效延长变化不明显,而控制预报和集合平均预报的异号两点跳跃以及三点跳跃出现的频率总体上随预报时效延长略有增加。  相似文献   

16.
总结回顾了集合敏感性分析(ESA)在诊断中纬度高影响天气预报不确定性中的应用。作为一个简单高效且不需要大量计算资源的方法,集合敏感性分析主要被应用在中纬度气旋、台风或飓风的温带转换,以及在强对流过程中诊断预报误差和不确定性的来源。集合敏感性方法极有灵活性,可以根据实际需要改变不同的预报变量和初始场。在对2010年美国东岸圣诞节暴风雪的分析中,集合敏感性分析通过三种形式来诊断了预报不确定性的初值敏感性,即基于EOF分析的敏感性、预报差别的敏感性,以及基于短期预报误差的向前积分敏感性回归。三种方法证实气旋路径的不确定性主要和位于美国南部大平原的短波槽初始误差相关。此外,气旋强度的不确定性还和产生于北太平洋向下游延伸的罗斯贝波列相关。集合敏感性分析方法对于分析中纬度气旋的不确定性、诊断初值敏感性、分析误差发展机制都非常有效。集合敏感性分析也被应用于分析台风/飓风的温带气旋转换过程的不确定性。在对2019年美国首个主要登陆台风Dorian的分析中发现,加拿大CMC的集合预报主要不确定性来自于强度的不确定性,而这个不确定性与初始时刻的大尺度环流型有关,较连贯的信号可以追溯至东北太平洋的前倾槽。而NCEP和ECMWF的不确定性主要在于气旋位置的东北—西南向移动,而敏感性主要和飓风系统本身(即其北部低压区和中纬度槽)的锁相有关。分析结果进一步验证了集合敏感性分析对诊断模式之间的不一致性,以及模式成员之间不一致性的不确定性来源和发展过程的可靠性。集合敏感性分析方法综合了集合预报、资料同化和敏感性分析,因此对于资料同化技术改进、诊断模式误差(或者缺陷)、附加(目标)观测最优策略,以及评估观测对预报的影响等都有重要意义。同时可以更有效地利用集合预报信息,帮助预报员提高情景意识,最终减少高影响天气预报中的决策失误。  相似文献   

17.
使用世界气象组织季节内至季节尺度(Subseasonal to Seasonal, S2S)预测项目数据库评估了多个集合预报系统在S2S时间尺度对台风的预报能力。评估的时间段为1999—2010年期间每年5月1日—10月31日。为评估S2S时间尺度台风的预报技巧,使用了台风密集度来描述台风的生成及移动状况。台风密集度定义为一段时间内500 km范围内台风出现的概率。台风密集度由6个S2S集合预报系统后报结果计算得出,它们分别由BoM、CMA、ECMWF、JMA、CNRM和NCEP开发使用。这6个预报系统台风密集度的预报技巧评分表明,当预报时效为11~30天时,ECMWF预报系统的评分为正值,比基于气候状态的参考预报能略好地预报台风。   相似文献   

18.
This study presented an evaluation of tropical cyclone (TC) intensity forecasts from five global ensemble prediction systems (EPSs) during 2015-2019 in the western North Pacific region. Notable error features include the underestimation of the TC intensity by ensemble mean forecast and the under-dispersion of the probability forecasts.The root mean square errors (brier scores) of the ensemble mean (probability forecasts) generally decrease consecutively at long lead times during the five years, but fluctuate between certain values at short lead times.Positive forecast skill appeared in the most recent two years (2018-2019) at 120 h or later as compared with the climatology forecasts. However, there is no obvious improvement for the intensity change forecasts during the 5-yearperiod, with abrupt intensity change remaining a big challenge. The probability forecasts show no skill for strongTCs at all the lead times. Among the five EPSs, ECMWF-EPS ranks the best for the intensity forecast, while NCEP-GEFS ranks the best for the intensity change forecast, according to the evaluation for ensemble mean and dispersion. As for the other probability forecast evaluation, ECMWF-EPS ranks the best at lead times shorter than 72 h, while NCEP-GEFS ranks the best later on.  相似文献   

19.
This paper investigates the possible sources of errors associated with tropical cyclone (TC) tracks forecasted using the Global/Regional Assimilation and Prediction System (GRAPES). The GRAPES forecasts were made for 16 landfalling TCs in the western North Pacific basin during the 2008 and 2009 seasons, with a forecast length of 72 hours, and using the default initial conditions (“initials”, hereafter), which are from the NCEP-FNL dataset, as well as ECMWF initials. The forecasts are compared with ECMWF forecasts. The results show that in most TCs, the GRAPES forecasts are improved when using the ECMWF initials compared with the default initials. Compared with the ECMWF initials, the default initials produce lower intensity TCs and a lower intensity subtropical high, but a higher intensity South Asia high and monsoon trough, as well as a higher temperature but lower specific humidity at the TC center. Replacement of the geopotential height and wind fields with the ECMWF initials in and around the TC center at the initial time was found to be the most efficient way to improve the forecasts. In addition, TCs that showed the greatest improvement in forecast accuracy usually had the largest initial uncertainties in TC intensity and were usually in the intensifying phase. The results demonstrate the importance of the initial intensity for TC track forecasts made using GRAPES, and indicate the model is better in describing the intensifying phase than the decaying phase of TCs. Finally, the limit of the improvement indicates that the model error associated with GRAPES forecasts may be the main cause of poor forecasts of landfalling TCs. Thus, further examinations of the model errors are required.  相似文献   

20.
This paper investigates the possible sources of errors associated with tropical cyclone(TC) tracks forecasted using the Global/Regional Assimilation and Prediction System(GRAPES). The GRAPES forecasts were made for 16 landfalling TCs in the western North Pacific basin during the 2008 and 2009 seasons, with a forecast length of 72 hours, and using the default initial conditions("initials", hereafter), which are from the NCEP-FNL dataset, as well as ECMWF initials. The forecasts are compared with ECMWF forecasts. The results show that in most TCs, the GRAPES forecasts are improved when using the ECMWF initials compared with the default initials. Compared with the ECMWF initials, the default initials produce lower intensity TCs and a lower intensity subtropical high, but a higher intensity South Asia high and monsoon trough, as well as a higher temperature but lower specific humidity at the TC center. Replacement of the geopotential height and wind fields with the ECMWF initials in and around the TC center at the initial time was found to be the most efficient way to improve the forecasts. In addition, TCs that showed the greatest improvement in forecast accuracy usually had the largest initial uncertainties in TC intensity and were usually in the intensifying phase. The results demonstrate the importance of the initial intensity for TC track forecasts made using GRAPES, and indicate the model is better in describing the intensifying phase than the decaying phase of TCs. Finally, the limit of the improvement indicates that the model error associated with GRAPES forecasts may be the main cause of poor forecasts of landfalling TCs. Thus, further examinations of the model errors are required.  相似文献   

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