T213与T639模式热带气旋预报误差对比

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。     

2018年西北太平洋台风活动特征和预报难点分析

利用1949—2018年中国气象局台风最佳路径、2018年中央气象台的台风路径强度实时预报、ECMWF数值预报以及NCEP逐日高分辨率海温RTG_SST(0.083°×0.083°)等资料,对2018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:2018年台风生成频数偏多,生成源地偏东,南海台风活跃;生成时间集中,盛夏台风异常偏多,台风群发性强,双台风或多台风共存活动频次偏多;台风生命史长,累积气旋能量偏高,超强台风偏多,但整体强度偏弱,较弱台风异常偏多;台风登陆频数和频次偏多,登陆地段偏北,且登陆台风强度明显偏弱。中央气象台24~120 h台风路径预报误差分别为72、124、179、262和388 km,各时效误差较2017年均有减少,特别是长时效路径预报误差明显减少;24~120 h台风强度预报误差分别为3.7、5.1、5.5、6.6和7.1 m·s^-1。由于双台风或多台风之间的相互作用、“鞍型场”等造成路径预报难度大以及多台风之间复杂水汽输送、近海台风强度变化不确定性大等原因,造成强度预报难度大。若采用更多观测资料、进行更深入的台风机理研究以及研发更有效的台风客观预报技术将是突破这些难点的有效途径。     

Possible sources of forecast errors generated by the global/regional assimilation and prediction system for landfalling tropical cyclones. Part I: Initial uncertainties

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.     

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.     

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.     

Possible Sources of Forecast Errors Generated by the Global/Regional Assimilation and Prediction System for Landfalling Tropical Cyclones. Part Ⅰ: Initial Uncertainties

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.     

Ensemble Based Diagnosis of the Track Errors of Super Typhoon Mangkhut (2018)

Super Typhoon Mangkhut (2018) was the most high-impact typhoon in 2018 because of its long lifespan and significant intensity. The operational track forecasts in the short-to-medium range (deterministic and probabilistic forecast) showed a great uncertainty and the forecast landing points varied with different lead times. This study applied ensembles of high-resolution ECMWF forecasts to investigate the major factors and mechanisms of the bias production of the Mangkhut forecast track. The ensembles with the largest track bias were analyzed to examine the possible bias associated factors. The results suggested that environmental steering flows were the main cause for the erroneous southward track error with a variance contribution of 72%. The tropical cyclone (TC) size difference and the interaction of the TC with the subtropical high (SH) were other two key factors that contributed to the track error. Particularly, larger TCs may have led to a stronger erosion of the southern part of the SH, and thus induced significant changes in the large-scale environment and eventually resulted in an additional northward movement of TC.

     

Ensemble Based Diagnosis of the Track Errors of Super Typhoon Mangkhut(2018)

Super Typhoon Mangkhut(2018)was the most high-impact typhoon in 2018 because of its long lifespan and significant intensity.The operational track forecasts in the short-to-medium range(deterministic and probabilistic forecast)showed a great uncertainty and the forecast landing points varied with different lead times.This study applied ensembles of high-resolution ECMWF forecasts to investigate the major factors and mechanisms of the bias production of the Mangkhut forecast track.The ensembles with the largest track bias were analyzed to examine the possible bias associated factors.The results suggested that environmental steering flows were the main cause for the erroneous southward track error with a variance contribution of 72%.The tropical cyclone(TC)size difference and the interaction of the TC with the subtropical high(SH)were other two key factors that contributed to the track error.Particularly,larger TCs may have led to a stronger erosion of the southern part of the SH,and thus induced significant changes in the large-scale environment and eventually resulted in an additional northward movement of TC.     

垂直分层加密和预报区域扩大对GRAPES_TYM台风预报的影响

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。      

Evaluation of a Regional Ensemble Data Assimilation System for Typhoon Prediction

An ensemble Kalman filter (EnKF) combined with the Advanced Research Weather Research and Forecasting model (WRF) is cycled and evaluated for western North Pacific (WNP) typhoons of year 2016. Conventional in situ data, radiance observations, and tropical cyclone (TC) minimum sea level pressure (SLP) are assimilated every 6 h using an 80-member ensemble. For all TC categories, the 6-h ensemble priors from the WRF/EnKF system have an appropriate amount of variance for TC tracks but have insufficient variance for TC intensity. The 6-h ensemble priors from the WRF/EnKF system tend to overestimate the intensity for weak storms but underestimate the intensity for strong storms. The 5-d deterministic forecasts launched from the ensemble mean analyses of WRF/EnKF are compared to the NCEP and ECMWF operational control forecasts. Results show that the WRF/EnKF forecasts generally have larger track errors than the NCEP and ECMWF forecasts for all TC categories because the regional simulation cannot represent the large-scale environment better than the global simulation. The WRF/EnKF forecasts produce smaller intensity errors and biases than the NCEP and ECMWF forecasts for typhoons, but the opposite is true for tropical storms and severe tropical storms. The 5-d ensemble forecasts from the WRF/EnKF system for seven typhoon cases show appropriate variance for TC track and intensity with short forecast lead times but have insufficient spread with long forecast lead times. The WRF/EnKF system provides better ensemble forecasts and higher predictability for TC intensity than the NCEP and ECMWF ensemble forecasts.     

An Evaluation of Tropical Cyclone Genesis Forecast over the Western North Pacificand the South China Sea from the CMA-TRAMS

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.     

2009—2015年ECMWF热带气旋集合预报的检验及分析

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。     

热带气旋相似和最大概率集成预报方法及其预报业务试用

利用建立在计算机系统的热带气旋历史资料,经反复试验提出了一套集热带气旋发生的日期相似、地理位置相似、路径相似和强度相似等相结合的挑选“最相似”热带气旋的方案;并利用所挑选的路径和强度“最相似”历史样本,分别对各预报时效的移动方向、移动速度和强度进行分级概率值统计,根据最大概率值选取相应的移向、移速和强度作为热带气旋路径和强度的预报。本方法已在计算机系统成功开发并投入业务试用,检验结果表明：本方法具有一定的预报能力,其输出的未来24、48、72小时的路径和强度预报对预报员有一定参考价值。     

CONDITIONAL NONLINEAR OPTIMAL PERTURBATIONS: APPLICATION IN TROPICAL CYCLONE FORECASTS

Considering the feature of tropical cyclones (TCs) that strong positive vorticity exists in the lower layers of troposphere, this study proposed to use vorticity at 850 hPa as cost function to find the conditional nonlinear optimal perturbation (CNOP), which was largely different from those previous studies using total energy of perturbed forecast variables. The CNOP was obtained by an ensemble-based approach. All of the sensitive areas determined by CNOP with vorticity at 850 hPa as cost function for the three cases were located over the TC core region and its vicinity. The impact of the CNOP-based adaptive observations on TC forecasts was evaluated with three cases via observational system simulation experiments (OSSEs). Results showed obvious improvements in TC intensity or track forecasts due to the CNOP-based adaptive observations, which were related to the main error source of the verification area, i.e., intensity error or location error.     

基于风廓线雷达的广东登陆台风边界层高度特征研究

针对8个登陆广东省的热带气旋,利用经过数据质量控制的风廓线雷达连续、高时空分辨率的风场观测数据,对热带气旋边界层特征进行了分析。研究结果表明:热带气旋边界层中切向风速大值区垂直范围越大、风速越强、持续时间越久,则热带气旋强度越大、登陆后强度维持时间越久。眼区外入流层厚度越大,入流层气流越强,热带气旋登陆后强度维持时间则越久。风廓线雷达信噪比垂直梯度对大气湍流信息有一定的指示作用,对于入流层高度在2000 m以下的热带气旋,其入流层顶所在高度与信噪比梯度最大值所在高度相近,对于入流层较为深厚的热带气旋,用信噪比垂直梯度确定的边界层高度虽接近入流层顶高,但仍有一定差距。不同特点的热带气旋其边界层高度并不相同,对于登陆后强度迅速减弱的热带气旋边界层高度在500~1000 m;登陆后强度持续时间短的热带气旋,其边界层高度约1000~2000 m;登陆后强度持续时间长的热带气旋,其边界层高度在2000 m之上,最高可达5000~7000 m。这些结果加深了对登陆台风边界层高度演变特征的认识。     

The Uncertainty of Tropical Cyclone Intensity and Structure Based on Different Parameterization Schemes of Planetary Boundary Layer

Based on different parameterization schemes of planetary boundary layer (PBL), the uncertainty of intensity and structure of the Super-strong Typhoon Rammasun (1409) is investigated using the WRF model (v3.4) with six PBL parameterization schemes. Results indicate that PBL uncertainty leads to the uncertainty in tropical cyclone (TC) prediction, which increases with forecast time. The uncertainty in TC prediction is mainly reflected in the uncertainty in TC intensity, with significant differences in the TC intensity forecasts using various PBL schemes. The uncertainty in TC prediction is also reflected in the uncertainty in TC structures. Greater intensity is accompanied by smaller vortex width, tighter vortex structure, stronger wind in the near-surface layer and middle and lower troposphere, stronger inflow (outflow) wind at the lower (upper) levels, stronger vertical upward wind, smaller thickness of the eye wall, smaller outward extension of the eye wall, and warmer warm core at the upper levels of eye. PBL height, surface upward heat flux and water vapor flux are important factors that cause the uncertainty in TC intensity and structure. The more surface upward heat flux and water vapor flux and the lower PBL height, the faster TC development and the stronger TC intensity.     

Can Adaptive Observations Improve Tropical Cyclone Intensity Forecasts?简

In order to investigate whether adaptive observations can improve tropical cyclone （TC） intensity forecasts,observing system simulation experiments （OSSEs） were conducted for 20 TC cases originating in the western North Pacific during the 2010 season according to the conditional nonlinear optimal perturbation （CNOP） sensitivity,using the fifth version of the PSU/NCAR mesoscale model （MM5） and its 3DVAR assimilation system.A new intensity index was defined as the sum of the number of grid points within an allocated square centered at the corresponding forecast TC central position,that satisfy constraints associated with the Sea Level Pressure （SLP）,near-surface horizontal wind speed,and accumulated convective precipitation.The higher the index value is,the more intense the TC is.The impacts of the CNOP sensitivity on the intensity forecast were then estimated.The OSSE results showed that for 15 of the 20 cases there were improvements,with reductions of forecast errors in the range of 0.12％-8.59％,which were much less than in track forecasts.The indication,therefore,is that the CNOP sensitivity has a generally positive effect on TC intensity forecasts,but only to a certain degree.We conclude that factors such as the use of a coupled model,or better initialization of the TC vortex,are more important for an accurate TC intensity forecast.     

华东登陆热带气旋降水不同分布的对比分析

利用CMORPH降水资料，将热带气旋（TC）登陆后的降水分为路径左侧降水（L型）和右侧降水（R型）两类，并针对登陆华东地区TC的 L型和R型降水的大气环流场、环境水平风垂直切变以及台风环流内的动热力条件进行对比分析，结果表明:2005～2014年间登陆华东地区的20例TC中包括12例L型和8例R型。总体来看，大气环流因子对于登陆华东TC降水分布起主要作用。L型降水TC高层南亚高压主要呈纬向带状分布，在登陆过程中路径左侧维持偏东风高空辐散气流，中层西风槽偏东，西太平洋副热带高压（简称副高）偏南，环境水平风垂直切变指向西南。R型降水TC高层南亚高压断裂，呈经向分布。TC路径左侧风场较均匀，右侧东南风高空辐散气流明显。副高的位置偏北呈块状，同时环境水平风垂直切变指向东北，有利于路径右侧降水。台风环流内，低层冷暖平流输送以及水汽辐合与降水落区也有较好对应关系。L型TC低层暖平流的输送使TC西南象限低层增暖，大气稳定度降低。同时水汽辐合区也主要位于西南象限，有利于TC路径左侧降水。而R型TC副高位置偏北可将南侧的东南暖湿气流向台风环流更西部输送，东北象限维持暖平流，有利于路径右侧降水发生。     

热带气旋的路径及登陆预报

用几个非线性数学模型制作热带气旋短期路径预报及热带气旋个数、登陆时段、地段的短期气候预报。5年多的研究和预报试验结果表明：用指数曲线模型制作热带气旋路径预报，准确率较高。24h预报，199次平均误差123km，达到国内先进水平。用多项式等非线性模型，制作登陆我国及登陆广东热带气旋的年、月个数预测，经过3年实际应用检验，准确率达到70％～90％。用非线性预测模型的逐日气压场、逐日雨量场长期预测结果进行分析，制作广东热带气旋登陆时段、地段和南海海面热带气旋出现时间的预报，准确率达到70％～80％，2002年热带气旋的预报，采用长中短期预报相结合，数值预报与统计预报相结合，预报效果较佳。     

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。