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1.
利用历史台风最佳路径、中央气象台台风路径强度实时预报,以及ECMWF数值预报和NCEP海温实况等资料,对2017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：2017年台风生成具有源地偏西、南海台风偏多和台风群发特征明显等特征;台风活动具有年度活跃程度低、台风极值强度偏弱和超强台风异常偏少等特征;台风登陆具有登陆台风个数多、登陆地点偏南、登陆强度偏弱等特征。对2017年度的预报误差进行分析,结果显示：24、48、72、96和120 h台风路径预报误差分别为74、137、233、318、428 km,各时效误差均较2016年有所增加;但与日本、美国相比,除120 h外,中国路径预报水平依然处于领先地位。 24、48、72、96和120 h台风强度误差分别为3.6、5.4、6.6、7.4和6.8 m·s-1,较2016年有所减小,24 h误差为历史最低值。强度预报水平居于日本、美国之间。另外,2017年最主要的预报难点是双台风或多台风之间复杂的相互作用和近海快速加强台风的强度预报。 相似文献
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2018年共有29个台风在西北太平洋和南海生成,生成台风个数偏多,南海台风活跃。有10个台风登陆我国,登陆强度整体明显偏弱,但是登陆台风个数明显偏多、登陆时间集中、登陆地段偏北、北上台风偏多,造成台风降水范围广、暴雨强度大、超警河流多。其中,“安比”、“摩羯”、“温比亚”一个月内相继在华东地区登陆并深入内陆北上,且登陆后长时间维持热带风暴级强度,给华东、华北、东北等地区带来大范围强降雨。“艾云尼”移动缓慢,与西南季风环流相结合,给广东等地区造成长时间的持续强降水。“山竹”是2018年登陆我国最强台风,其7级风圈明显偏大,给广东、香港等地区带来大范围、长时间的强风和强降水。2018年所有预报时效的路径预报误差较2017年均有所降低,路径预报水平进一步提高,但是强度预报水平仍然没有明显的进步。 相似文献
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《气象》2021,(8)
2019年在西北太平洋及南海共生成台风29个,比多年同期平均偏多2个,其中6个台风登陆我国,比多年平均偏少1个;台风整体强度偏弱,但全年最强台风夏浪极值强度达到68 m·s~(-1)(17级以上);登陆台风整体强度偏弱,但"利奇马"登陆强度强(52 m·s~(-1),超强台风级)、影响重;秋季台风生成数较常年明显偏多,尤其是11月生成台风数达到6个。2019年中央气象台台风路径预报平均误差与近5年(2014—2018年)的平均误差相比,在24～72 h的预报误差有所增大,而96～120 h的预报误差则明显减小,尤其是120 h的预报准确率创新高。与日、美官方预报相比,中国在24 h和96～120 h的预报水平处于领先地位,在48～72 h的预报误差比日本略高,但低于美国,与EC确定性模式相当。 相似文献
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钱奇峰董林许映龙周冠博王皘 《气象》2023,(10):1254-1266
利用1949—2021年中国气象局台风最佳路径资料、2022年中央气象台台风路径和强度实时业务资料、欧洲中期预报中心ERA-Interim逐6 h再分析资料等,对2022年西北太平洋和南海台风活动的主要特征进行分析。结果表明:2022年,台风活动的阶段性、群发性特征明显,生成位置偏北偏西,登陆我国的台风数量偏少、强度偏强,自2019年以来,已连续4年登陆台风个数偏少。预报误差分析表明,在台风生成初期、台风与西风带结合后转向以及多台风(低压)活动期间的路径预报误差较大。进一步分析台风暹芭、梅花和轩岚诺的预报难点,结果表明:“暹芭”北侧的大陆高压和高层急流的预报偏差是导致后期路径预报调整的主要原因;“梅花”登陆后陆上路径预报偏差主要由模式对引导气流的预报偏差所致;“轩岚诺”路径和强度变化复杂,在其快速加强和快速减弱的速率、结构变化导致的强度波动和尺度变化等方面存在预报偏差。 相似文献
6.
中央气象台台风强度综合预报误差分析 总被引：6，自引：5，他引：1
本文从总误差、逐年趋势、误差分布等方面对2001—2012年中央气象台（Central Meteorological Observatory, CMO）的台风（TC）强度综合预报水平进行分析,初步分析了强度迅速变化台风预报偏差大的原因。结果表明,强度预报水平没有明显改善,预报误差呈现逐年波动状态,强度稳定TC的预报误差最小,迅速加强TC的预报误差最大。24、96~120 h预报偏强的概率较大,而48~72 h预报偏弱的概率大。南海东北部等海域的预报误差较大,应在业务预报中特别予以关注。随着TC强度的逐渐增强,强度预报在120 h内预报偏强的可能性变大,而强度预报偏弱的可能性减小。根据误差分析结果,提出了一个强度概率预报方案,检验结果表明可在业务中参考使用。 相似文献
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我国台风路径业务预报误差及成因分析 总被引：4，自引：1，他引：3
利用2005 2009年中国气象局(CMA)提供的西北太平洋(包括南海)台风路径业务预报资料,比较了各类型台风路径、台风登陆位置及登陆时间的预报误差,登陆台风不同阶段以及华东登陆和华南登陆台风的路径预报误差。结果表明:CMA在2005 2009年的路径预报水平与1999 2003年的相比有了显著提高。平均南海台风预报误差大于西北太平洋。异常路径台风主要出现于南海,三个预报时效(24、48和72 h)异常路径的预报误差平均都小于正常路径。将登陆台风分为远海、登陆期间和登陆后三个阶段,显示登陆期间台风预报误差最大,同一阶段华南登陆台风的预报误差大于华东登陆台风。台风登陆位置在24、48和72 h预报时效的平均预报误差分别为71.1、122.6和210.6 km,48和72 h台风实际登陆时间有70%早于预报时间,平均分别提早8和12 h。比较大尺度引导气流与台风移动的偏差及24 h路径预报误差,得到南海三种典型登陆台风路径的大尺度引导气流与台风移动的偏差及其与路径预报误差的关系不一样,即误差成因不同。南海倒抛物线型的大尺度引导气流与台风移动的偏差最大,其预报误差最小;西一西北型的大尺度引导气流与台风移动的偏差最小,其预报误差最大,可能与大尺度环流预报准确性差有关。登陆华东的预报误差小于登陆华南台风的预报误差,这与台风登陆华南时其大尺度引导气流和台风移动的偏差大于登陆华东的台风有关。 相似文献
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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
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T639台风预报误差与环境场变量的相关分析和回归分析 总被引：1，自引：1，他引：0
利用国家气象中心全球谱模式T639L60(简称T639)数值预报结果和上海台风研究所整编的台风最佳路径数据,基于2009—2010年的样本,分析了西北太平洋和南海台风的环境场预报变量与路径预报误差的相关性,利用线性回归分析,建立了T639台风中心预报误差与环境风整层垂直切变、400 hPa台风环流强度的24~120 h各预报时效线性预估模型(建模样本数分别为299、232、170、117和84个),并利用2011年的样本对模型进行了检验(检验样本数分别为182、146、117、85和61个)。初步结果表明,环境风垂直切变与路径误差呈正相关,台风各层环流强度与路径误差大致呈负相关,其中400 hPa上的负相关性最明显;由环境风垂直切变与400 hPa台风环流强度建立的线性预估模型能对路径预报误差作出定性估计,其中24h预报时效的预估模型有较好的预估效果。 相似文献
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利用历史台风最佳路径资料、2016年台风最佳路径实况和中央气象台台风路径强度实时预报资料,以及ECMWF数值预报和集合预报产品,对2016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：1—6月的淡季空台风和盛夏秋季多台风现象均与2016年〖JP2〗赤道海温由厄尔尼诺向拉尼娜转换有关;长时效路径预报误差有时异常偏大,可能与集合预报产品的发散度很大有关,但是如果能够掌握数值天气预报对大尺度天气系统预报的系统性偏差,也可以做出精度更高的预报;24 h强度预报误差超过了5 m·s-1,这种现象在过去十多年的业务预报中并不多见,个别最大误差竟达20~26 m·s-1。〖JP〗强度预报的大误差与强度预报中没有定量产品可供参考有关,定性地分析台风强度变化规律对于提高强度预报作用很小,所以急需建立和发展定量和精细化的强度预报方法。 相似文献
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Shaoying LI Jun PENG Weimin ZHANG Jianping WU Qiang YAO Xiangrong YANG Tengling LUO 《大气科学进展》2023,40(3):464-482
The accurate forecasting of tropical cyclones(TCs) is a challenging task. The purpose of this study was to investigate the effects of a dry-mass conserving(DMC) hydrostatic global spectral dynamical core on TC simulation. Experiments were conducted with DMC and total(moist) mass conserving(TMC) dynamical cores. The TC forecast performance was first evaluated considering 20 TCs in the West Pacific region observed during the 2020 typhoon season. The impacts of the DMC dynamical core on forecasts o... 相似文献
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应用国家气象中心全球谱模式T213L31(简称T213) 及其升级版本T639L60(简称T639) 对2009—2010年西北太平洋热带气旋数值预报的结果进行对比。结果表明:T213与T639模式24～120 h预报平均距离误差基本相近,但由于T639模式分辨率较高,T639模式的热带气旋强度预报明显好于T213模式。从分类误差来看,T639模式对于西北行登陆及转向热带气旋的路径预报好于T213模式,但对西行及北上热带气旋预报误差偏大。对于异常路径热带气旋预报,T639模式能较好预报环流形势的突然调整,对路径突变的热带气旋预报比T213模式有明显优势;从登陆类热带气旋预报的移向误差来看,T213模式存在东北偏北向系统性偏差,T639模式存在东北偏东向系统性偏差。 相似文献
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本文从四个方面检验分析了ECMWF 2009—2015年西北太平洋热带气旋集合平均预报性能。结果表明：集合预报对路径的预测能力逐年提高,对强度预报整体偏弱。随着热带气旋强度增强,集合预报对移速和移向的预测能力提高,而移向预报偏左、移速预报偏慢、强度预测偏弱的现象较明显。将影响热带气旋的引导气流分为偏强、中等、偏弱三类,引导气流偏弱时热带气旋移动偏慢,因此移向预报的不确定性大;而引导气流偏强时热带气旋移向明确,只是移速预报不稳定。进入南海的三类路径热带气旋,集合预报对西行、西北行两类的移速、移向预报效果较好,而西行后北折的预报较差,在热带气旋北折前,移向预报发散度很大,向北转折后移向趋于稳定,移速预报的误差相对较大。这几种情形的检验结果,在热带气旋集合预报的业务应用中值得注意。 相似文献
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登陆热带气旋路径和强度预报的效益评估初步研究 总被引：1，自引：3，他引：1
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。 相似文献
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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. 相似文献
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In recent work, three physical factors of the Dynamical-Statistical-Analog Ensemble Forecast Model for Landfalling Typhoon Precipitation (DSAEF_LTP model) have been introduced, namely, tropical cyclone (TC) track, TC landfall season, and TC intensity. In the present study, we set out to test the forecasting performance of the improved model with new similarity regions and ensemble forecast schemes added. Four experiments associated with the prediction of accumulated precipitation were conducted based on 47 landfalling TCs that occurred over South China during 2004-2018. The first experiment was designed as the DSAEF_LTP model with TC track, TC landfall season, and intensity (DSAEF_LTP-1). The other three experiments were based on the first experiment, but with new ensemble forecast schemes added (DSAEF_LTP-2), new similarity regions added (DSAEF_LTP-3), and both added (DSAEF_LTP- 4), respectively. Results showed that, after new similarity regions added into the model (DSAEF_LTP-3), the forecasting performance of the DSAEF_LTP model for heavy rainfall (accumulated precipitation ≥250 mm and ≥100 mm) improved, and the sum of the threat score (TS250 + TS100) increased by 4.44%. Although the forecasting performance of DSAEF_LTP-2 was the same as that of DSAEF_LTP-1, the forecasting performance was significantly improved and better than that of DSAEF_LTP-3 when the new ensemble schemes and similarity regions were added simultaneously (DSAEF_LTP-4), with the TS increasing by 25.36%. Moreover, the forecasting performance of the four experiments was compared with four operational numerical weather prediction models, and the comparison indicated that the DSAEF_LTP model showed advantages in predicting heavy rainfall. Finally, some issues associated with the experimental results and future improvements of the DSAEF_LTP model were discussed. 相似文献
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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%。 相似文献
18.
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
19.
Tropical cyclone (TC) genesis forecasting is essential for daily operational practices during the typhoon season.The updated version of the Tropical Regional Atmosphere Model for the South China Sea (CMA-TRAMS) offersforecasters reliable numerical weather prediction (NWP) products with improved configurations and fine resolution. Whiletraditional evaluation of typhoon forecasts has focused on track and intensity, the increasing accuracy of TC genesisforecasts calls for more comprehensive evaluation methods to assess the reliability of these predictions. This study aims toevaluate the effectiveness of the CMA-TRAMS for cyclogenesis forecasts over the western North Pacific and South ChinaSea. Based on previous research and typhoon observation data over five years, a set of localized, objective criteria has beenproposed. The analysis results indicate that the CMA-TRAMS demonstrated superiority in cyclogenesis forecasts, pre dicting 6 out of 22 TCs with a forecast lead time of up to 144 h. Additionally, over 80% of the total could be predicted 72 hin advance. The model also showed an average TC genesis position error of 218.3 km, comparable to the track errors ofoperational models according to the annual evaluation. The study also briefly investigated the forecast of Noul (2011). Theforecast field of the CMA-TRAMS depicted thermal and dynamical conditions that could trigger typhoon genesis, con sistent with the analysis field. The 96-hour forecast field of the CMA-TRAMS displayed a relatively organized three dimensional structure of the typhoon. These results can enhance understanding of the mechanism behind typhoon genesis,fine-tune model configurations and dynamical frameworks, and provide reliable forecasts for forecasters. 相似文献
20.
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. 相似文献