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。      

GRAPES_TYM改进及其在2013年西北太平洋和南海台风预报的表现

2013年国家气象中心对GRAPES_TYM进行了改进,包括集成GRAPES-Meso模式相关改进（即基础模式升级）、对流参数化过程由Simplified Arakawa-Schubert（简称SAS）升级为Meso-SAS,并对涡旋初始化方案进行优化。7个典型个例试验统计分析表明,基础模式升级可使72 h平均路径误差减小10%,在基础模式升级的基础上对流参数化方案的升级可使72 h平均路径误差减小20%,涡旋初始化方案的优化可使72 h平均路径误差进一步减小10%。基础模式的升级和对流参数化方案的升级对GRAPES_TYM的预报路径系统右偏有明显改进;基础模式升级对强度预报的影响不明显,Meso-SAS的应用对12~48 h强度预报的改善效果较显著,而台风初始化方案的优化可以减小6~24 h预报时段内的强度预报误差。2013年全年台风回算结果表明,升级后的GRAPES_TYM其48~72 h后的路径预报误差较准业务系统减小15%~20%,最大风速预报误差减小4%~16%。      

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.     

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.     

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。      

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。     

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。     

Which Features of the SST Forcing Error Most Likely Disturb the Simulated Intensity of Tropical Cyclones?

Among all of the sources of tropical cyclone(TC) intensity forecast errors, the uncertainty of sea surface temperature(SST) has been shown to play a significant role. In the present study, we determine the SST forcing error that causes the largest simulation error of TC intensity during the entire simulation period by using the WRF model with time-dependent SST forcing. The SST forcing error is represented through the application of a nonlinear forcing singular vector(NFSV)structure. For the selected 12 TC cases, the NFSV-type SST forcing errors have a nearly coherent structure with positive(or negative) SST anomalies located along the track of TCs but are especially concentrated in a particular region. This particular region tends to occur during the specific period of the TCs life cycle when the TCs present relatively strong intensity, but are still intensifying just prior to the mature phase, especially within a TC state exhibiting a strong secondary circulation and very high inertial stability. The SST forcing errors located along the TC track during this time period are verified to have the strongest disturbing effect on TC intensity simulation. Physically, the strong inertial stability of TCs during this time period induces a strong response of the secondary circulation from diabatic heating errors induced by the SST forcing error. Consequently, this significantly influences the subsidence within the warm core in the eye region, which,in turn, leads to significant errors in TC intensity. This physical mechanism explains the formation of NSFV-type SST forcing errors. According to the sensitivity of the NFSV-type SST forcing errors, if one increases the density of SST observations along the TC track and assimilates them to the SST forcing field, the skill of TC intensity simulation generated by the WRF model could be greatly improved. However, this adjustment is most advantageous in improving simulation skill during the time period when TCs become strong but are still intensifying just prior to reaching full maturity. In light of this, the region along the TC track but in the time period of TC movement when the NFSV-type SST forcing errors occur may represent the sensitive area for targeting observation for SST forcing field associated with TC intensity simulation.     

Sensitivity of physical parameterizations on prediction of tropical cyclone Nargis over the Bay of Bengal using WRF model

Comprehensive sensitivity analyses on physical parameterization schemes of Weather Research Forecast (WRF-ARW core) model have been carried out for the prediction of track and intensity of tropical cyclones by taking the example of cyclone Nargis, which formed over the Bay of Bengal and hit Myanmar on 02 May 2008, causing widespread damages in terms of human and economic losses. The model performances are also evaluated with different initial conditions of 12?h intervals starting from the cyclogenesis to the near landfall time. The initial and boundary conditions for all the model simulations are drawn from the global operational analysis and forecast products of National Center for Environmental Prediction (NCEP-GFS) available for the public at 1° lon/lat resolution. The results of the sensitivity analyses indicate that a combination of non-local parabolic type exchange coefficient PBL scheme of Yonsei University (YSU), deep and shallow convection scheme with mass flux approach for cumulus parameterization (Kain-Fritsch), and NCEP operational cloud microphysics scheme with diagnostic mixed phase processes (Ferrier), predicts better track and intensity as compared against the Joint Typhoon Warning Center (JTWC) estimates. Further, the final choice of the physical parameterization schemes selected from the above sensitivity experiments is used for model integration with different initial conditions. The results reveal that the cyclone track, intensity and time of landfall are well simulated by the model with an average intensity error of about 8?hPa, maximum wind error of 12?m?s^?1and track error of 77?km. The simulations also show that the landfall time error and intensity error are decreasing with delayed initial condition, suggesting that the model forecast is more dependable when the cyclone approaches the coast. The distribution and intensity of rainfall are also well simulated by the model and comparable with the TRMM estimates.     

数值模式的热带气旋强度预报订正及其集成应用

提供热带气旋强度预报产品的业务数值天气预报模式有很多,并已表现出一定的预报技巧,为提高对模式热带气旋强度预报产品的定量应用能力,分析2010—2012年7个业务数值模式的西北太平洋热带气旋强度预报,发现预报误差不仅受到模式热带气旋初始强度误差的显著影响,还与热带气旋及其所处环境的初始状况有密切关系,包括热带气旋初始强度、尺度、移速、环境气压、环境风切变、热带气旋发展潜势等。根据这些因子与各模式热带气旋强度预报误差之间的相关性,采用逐步回归方法建立热带气旋强度预报误差的统计预估模型,并通过逐个热带气旋滚动式建模来进行独立样本检验。检验结果表明,基于误差预估的模式订正预报比模式直接输出的热带气旋强度预报有显著改进,在此基础上建立的热带气旋强度多模式集成预报方案相对气候持续性预报方法在12 h有28%的正技巧,在24—72 h则稳定在15%—20%,具有业务参考价值。     

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.     

Evaluation of long-term trends in tropical cyclone intensity forecasts

Summary The National Hurricane Center and Joint Typhoon Warning Center operational tropical cyclone intensity forecasts for the three major northern hemisphere tropical cyclone basins (Atlantic, eastern North Pacific, and western North Pacific) for the past two decades are examined for long-term trends. Results show that there has been some marginal improvement in the mean absolute error at 24 and 48 h for the Atlantic and at 72 h for the east and west Pacific. A new metric that measures the percent variance of the observed intensity changes that is reduced by the forecast (variance reduction, VR) is defined to help account for inter-annual variability in forecast difficulty. Results show that there have been significant improvements in the VR of the official forecasts in the Atlantic, and some marginal improvement in the other two basins. The VR of the intensity guidance models was also examined. The improvement in the VR is due to the implementation of advanced statistical intensity prediction models and the operational version of the GFDL hurricane model in the mid-1990s. The skill of the operational intensity forecasts for the 5-year period ending in 2005 was determined by comparing the errors to those from simple statistical models with input from climatology and persistence. The intensity forecasts had significant skill out to 96 h in the Atlantic and out to 72 h in the east and west Pacific. The intensity forecasts are also compared to the operational track forecasts. The skill was comparable at 12 h, but the track forecasts were 2 to 5 times more skillful by 72 h. The track and intensity forecast error trends for the two-decade period were also compared. Results showed that the percentage track forecast improvement was almost an order of magnitude larger than that for intensity, indicating that intensity forecasting still has much room for improvement.     

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.

     

涡旋强度调整半径对2016年第18号热带气旋路径预报的影响

2016年中国国家气象中心区域台风模式（GRAPES_TYM）对第18号热带气旋（记为TC 1618）的路径预报出现了较大的误差:其平均路径误差显著大于全年的平均误差。分析了涡旋初始化方案（包括涡旋重定位以及涡旋强度调整）对其路径预报的影响。结果显示,涡旋强度调整是造成TC1618预报路径平均误差偏大的主要原因。不同的强度调整半径（r₀=12°,9°,6°,3°）对TC1618路径影响的敏感性试验结果显示,强度调整半径越大,其平均路径预报误差越大。500 hPa副热带高压以及平均海平面涡旋尺度分析发现:较大的强度调整半径（r₀=12°,9°）其初始时刻的涡旋尺度较大,涡旋北侧邻近区域副热带高压等值线相对偏北,副热带高压相对偏弱。尺度大的涡旋其北移速度较大,并且在积分过程中其环流邻近区域副热带高压进一步减弱,导致涡旋环流会更早与其西北侧东移的西风槽结合,移速偏快。      

T639台风预报误差与环境场变量的相关分析和回归分析

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。     

1999—2003年西北太平洋热带气旋综合预报的误差分析

应用1999—2003年中国中央气象台 (CMO)、日本气象厅 (JMA) 以及美国联合台风警报中心 (JTWC) 发布的西北太平洋热带气旋综合预报资料, 从总误差、逐年误差趋势、不同海区误差、不同路径趋势误差、不同强度趋势误差等5个方面对各预报中心的路径及强度预报结果进行分析, 结果表明:5年总的平均误差以JTWC的路径预报误差最小, 而JMA的强度预报较准确; 在不同海域, 各预报中心的路径预报能力各有优势, 但在热带气旋的强度预报方面, JMA的方法在各海区都较稳定; 对不同路径趋势热带气旋的预报方面, 除了南海转向热带气旋的路径预报比JMA和CMO稍差一些之外, JTWC的路径预报在大多数情况下都是好于或相当于JMA和CMO; 在不同强度变化趋势热带气旋的预报方面, JTWC在大多数情况下都优于其他中心。上述结果帮助业务和科技人员全面了解各预报中心的预报能力优劣, 也为今后改进我国的热带气旋预报提供有益的参考。     

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。     

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;...     

THE IMPACTS OF INTERACTION OF A TYPHOON WITH THE MIDLATITUDE TROUGH ON ITS TRACK AFTER THE RECURVATURE

Three typhoon cases are selected to conduct a series of simulations that are initialized from sequential analyses. The results show that the forecast error in crucial area where a tropical cyclone (TC) interactes with the upstream trough is highly correlated to the track forecast error after the TC recurvature. Furthermore, sensitivity experiments confirm that the developments of the midlatitude downstream circulations and then the TC track after its recurvature are highly sensitive to the TC intensity and its location relative to the upstream trough, which can give an example or one way of sensitivity of the TC track to the TC-trough interaction. If the TC interacts with the upstream trough more strongly (e.g., the TC being intensified or getting closer to the upstream trough), the downstream circulations will be more meridional, thus the TC track will be more northerly and westerly; otherwise, the downstream circulations will be more zonal, and the TC track will be more southerly and easterly.     

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.