Seasonal climate prediction for South America with FSU Multi-model Synthetic Superensemble algorithm

Summary Objective combination schemes of predictions from different models have been applied to seasonal climate forecasts. These schemes are successful in producing a deterministic forecast superior to individual member models and better than the multi-model ensemble mean forecast. Recently, a variant of the conventional superensemble formulation was created to improve skills for seasonal climate forecasts, the Florida State University (FSU) Synthetic Superensemble. The idea of the synthetic algorithm is to generate a new data set from the predicted multimodel datasets for multiple linear regression. The synthetic data is created from the original dataset by finding a consistent spatial pattern between the observed analysis and the forecast data set. This procedure is a multiple linear regression problem in EOF space. The main contribution this paper is to discuss the feasibility of seasonal prediction based on the synthetic superensemble approach and to demonstrate that the use of this method in coupled models dataset can reduce the errors of seasonal climate forecasts over South America. In this study, a suite of FSU coupled atmospheric oceanic models was used. In evaluation the results from the FSU synthetic superensemble demonstrate greater skill for most of the variables tested here. The forecast produced by the proposed method out performs other conventional forecasts. These results suggest that the methodology and database employed are able to improve seasonal climate prediction over South America when compared to the use of single climate models or from the conventional ensemble averaging. The results show that anomalous conditions simulated over South America are reasonably realistic. The negative (positive) precipitation anomalies for the summer monsoon season of 1997/98 (2001/02) were predicted by Synthetic Superensemble formulation quite well. In summary, the forecast produced by the Synthetic Superensemble approach outperforms the other conventional forecasts.     

热带气旋路径趋势数值预报的试验研究

给出了一个嵌套于欧洲中期天气预报中心全球谱模式中的套网格模式，用于预报热带气旋路径趋势，提出了一种以欧洲中期天气预报中心提供的时距为24小时的预报场为基础的“接力预报”方法；设计了五种不同的“接力预报”方案；并对8507号和8509号两个热带气旋就各种不同预报方案进行了数值预报试验。结果表明，本模式对热带气旋路径趋势具有较强的预报能力，对疑难路径也具有一定的预报能力，为开展热带气旋的路径趋势预报提供了一个新的途径。文中还对影响热带气旋路径趋势的一些主要因子结合各预报结果进行了分析，为模式尽早投入业务提供了一定的依据。     

热带气旋研究和业务预报进展—第九届世界气象组织热带气旋国际研讨会（IWTC-9）综述

2018年12月3—7日在美国夏威夷召开的第九届世界气象组织热带气旋国际研讨会对国际热带气旋研究和预报预警业务的近期进展进行了充分回顾,并对未来的发展方向进行了系统研讨。过去4年（2015—2018年）,在热带波动和对流对热带气旋生成的影响、复杂环境影响热带气旋路径转向的机理、对流和风垂直切变对热带气旋强度变化的作用机制、双眼墙形成和替换机理、热带气旋变性过程对环境条件的响应、热带气旋气候变化特征、热带气旋多平台观测技术等诸多方面的研究取得了显著进展。同时,在热带气旋生成概率预报、全球模式中热带气旋强度预报改进、热带气旋活动次季节业务预测技术发展以及热带气旋预报不确定性理论等方面也取得积极进展。在综述此次会议的相关议题后,简要讨论中国热带气旋研究和业务发展方向。      

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.     

Advances in research and forecasting of tropical cyclones from 1963–2013

A review of progress over the past 50 years in observing and forecasting of tropical cyclones is presented. Tremendous progress has been made in track forecasting in the past 20 years with the improvement in numerical model guidance and the use of consensus forecasting, and this has contributed to a number of warning centers now issuing five-day track forecasts that are as accurate as three-day forecasts of a decade ago. Techniques are now available to specify the track forecast uncertainty for assessing the risk of a tropical cyclone. With the advent of five-day forecasts, a focus on improved understanding of formation has led to two field experiments. A recent advance has been in extended-range (5–30 days) forecasts of tropical cyclone events (formations and tracks) in the western North Pacific from the ECMWF 32-day ensemble predictions. This advance is a contribution to a goal of seamless forecasting from one day to a season for tropical cyclones. Little progress has been made in intensity forecasting, although the Hurricane Forecast Improvement Project in the United States and recent field experiments may offer some future advances. Some advances in forecasting tropical cyclone impacts such as storm surge, surface waves, and precipitation have been achieved. Future opportunities for continued advances are possible such that improved warnings can lead to reductions in losses of lives and minimizing damages from tropical cyclones.     

2013年欧洲中心台风集合预报的检验

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。     

Improving Multi-Model Ensemble Forecasts of Tropical Cyclone Intensity Using Bayesian Model Averaging

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 (P_min). 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 P_min 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.     

Assimilation of All-sky Geostationary Satellite Infrared Radiances for Convection-Permitting Initialization and Prediction of Hurricane Joaquin (2015)

Intensity forecasting is one of the most challenging aspects of tropical cyclone (TC) forecasting. This work examines the impact of assimilating high-resolution all-sky infrared radiance observations from geostationary satellite GOES-13 on the convection-permitting initialization and prediction of Hurricane Joaquin (2015) with an ensemble Kalman filter (EnKF) based on the Weather Research and Forecasting (WRF) model. Given that almost all operational global and regional models struggled to capture Hurricane Joaquin (2015)’s intensity, this study examines the potential in improving Joaquin’s prediction when assimilating all-sky infrared radiances from GOES-13’s water vapor channel. It is demonstrated that, after a few 3-hour cycles assimilating all-sky radiance, the WRF model was able to forecast reasonably well Joaquin’s intensity, including its rapid intensification (RI). The improvement was largely due to a more realistic initial hurricane structure with a stronger, warmer, and more compact inner-core. Ensemble forecasts were used to further explore the important physical mechanisms driving the hurricane’s RI. Results showed that the RI forecasts were greatly impacted by the initial inner-core vortex structure.     

热带气旋路径强度预报——SAPC法

SAPC——逐段相似气候持续性热带气旋路径、强度预报方法，既考虑了热带气旋的气候持续性规律，又考虑了与现时热带气旋状态特别相似的历史热带气旋路径、强度变化规律，用不同的相似条件和权重，把气候路径、相似路径和持续性路径作了有机的统一。该方法克服了预报路径的大曲率变化，考虑了随时间、地点变化的热带气旋的气候规律，根据热带气旋的现时状态，即可随时制作路径、强度预报。历史资料和实际应用表明该方法有实用价值。     

热带气旋的温带变性过程对下游影响的研究进展

热带气旋(TC)在向高纬度地区移动过程中往往会转变为温带气旋,称之为温带变性(ET)过程。ET过程涉及到热带系统与中纬度环流的复杂相互作用,并对局地系统直至大范围环流均产生影响,这种影响甚至向下游延伸到半球的尺度。由于ET过程及其下游影响给中纬度地区带来严重灾害性天气,而对其的预报一直是一个难题,因而关于此问题的科学研究和业务预报是近年来国际上的一个热点,国内的有关工作也已开展。从TC在ET过程中与中纬度环流的相互作用、ET过程对中纬度下游环流的影响和ET过程及其下游影响的数值预报三个方面总结和分析了近年来国内外的有关研究进展,为国内学术界进一步开展相关研究提供参考。主要进展包括:(1) TC高层出流输出低位涡(PV)空气改变温带上层结构以及TC环流直接作用于中纬度流是TC-中纬度流相互作用的主要方式;TC相对于上游槽的位置对ET过程及其下游影响很关键;各种物理过程在相互作用中起到不同的作用;(2) TC所激发的Rossby波在与急流相联系的上层PV梯度上向下游频散是下游发展的主要方式;下游发展具有显著的边界俘获和上下层耦合发展的特征;(3) 目标观测、集合预报和变分同化等技术的发展提高了ET及其下游影响的数值预报水平。      

Rainfall anomaly prediction using statistical downscaling in a multimodel superensemble over tropical South America

This study addresses the predictability of rainfall variations over South America and the Amazon basin. A primary factor leading to model inaccuracy in precipitation forecasts is the coarse resolution data utilized by coupled models during the training phase. By using MERRA reanalysis and statistical downscaling along with the superensemble methodology, it is possible to obtain more precise forecast of rainfall anomalies over tropical South America during austral fall. Selective inclusion (and exclusion) of member models also allows for increased accuracy of superensemble forecasts. The use of coupled atmospheric–ocean numerical models to predict the rainfall anomalies has had mixed results. Improvement in individual member models is also possible on smaller spatial scales and in regions where substantial topographical changes were not handled well under original model initial conditions. The combination of downscaling and superensemble methodologies with other research methods presents the potential opportunity for increased accuracy not only in seasonal forecasts but on shorter temporal scales as well.     

2002年西北太平洋和南海热带气旋路径主客观预报评价

利用目前中央气象台热带气旋路径实时业务预报中使用的各种主客观预报产品资料，对2002年西北太平洋和南海热带气旋路径实时业务预报中的主客观预报进行对比分析检验。结果显示：虽然在整体上主观预报要优于客观模式的结果，但客观模式的预报能力已接近主观预报，有时甚至还好于主观预报，特别是48小时以上时效的客观模式较主观预报具有一定的优势；而在客观模式中，全球模式优于台风模式；热带气旋路径数值模式产品的使用对提高热带气旋路径业务预报水平具有十分重要的作用。     

热带气旋研究和业务预报技术的发展

过去半个世纪, 我国对热带气旋作了深入和系统的研究。研究内容涉及热带气旋的运动机理和路径预报方法、发生发展及结构和强度变化、登陆和变性过程、登陆后的衰减和维持机制及其引起的暴雨分布等。在此院庆之际, 该文主要对中国气象科学研究院在热带气旋领域的研究作一回顾, 与此发生关联的国内其他单位的工作也可能提及, 但决非全面总结。采用的研究方法包括数理统计、天气动力机理分析、数值模式发展和模拟研究、物理诊断分析及外场科学试验等, 这些研究方法和取得的成果在不同时期对推动国内热带气旋研究起了积极的作用。上述研究工作的另一个特点是与实际紧密结合, 研究成果在实际台风预报业务中应用并不断改进, 研究成果不断转化为业务能力, 对改进预报技术、提高业务预报能力作出了重要贡献。     

辽宁省热带气旋模式预报业务系统

介绍了在MM5模式基础上建立起来的辽宁省热带气旋模式预报业务系统及2005年的预报情况。系统以T213L31产品为背景场和侧边界,初始场中同化了常规探空报、地面报及一些卫星反演资料,模式的初值中还嵌入人造热带气旋进行模式运算。系统每日自动运行2次;模式输出结果经后处理后,编写到通用绘图软件GrADs中,以图形显示,并在沈阳区域气象中心局域网的中尺度数值预报网页上显示。2005年汛期热带气旋预报表明,系统对热带气旋的路径和暴雨的预报效果较好。     

Multimodel based superensemble forecasts for short and medium range NWP over various regions of Africa

Summary This study examines the predictability of weather over several regions in Africa using a multimodel superensemble technique developed at the Florida State University, which is an objective means of combining daily forecasts from multilevel global models. It is referred to as FSUSE and up to 7 different models are used to construct the superensemble. The benchmark reanalysis fields used are the precipitation data sets from CMORPH and all other global fields from ECMWF daily operational analysis. The FSUSE works by using multiple linear regression to derive weights from a comparison of each member model forecast to the benchmark analysis during a training period of the most recent 120 days, and these weights are passed to the forecast phase. This procedure removes the bias of each model and allows for an optimal linear combination of the individual model forecasts by taking account of the relative skill of each model to give a consensus forecast that is superior to the ensemble mean and all the members. Results show that bad models and poor analysis fields used during the training phase degrade the skill of the FSUSE. In the forecasts of rainfall events over all regions of Africa, the FSUSE root-mean-square (R M S) error, equitable threat skill score (E T S), and bias on the daily forecasts of rainfall were invariably superior to the best member model. The skills deteriorate as the forecast lead time in days increases, with the degradation being most significant beyond day 3. In all cases, the bias score of the FSUSE was approximately 1, while the anomaly correlation scores were to the order of 0.9. These scores indicate the robustness of the FSUSE forecasts. Over East Africa, the FSUSE forecasts were consistent with the spatial-temporal pattern of the Intertropical Convergence Zone (ITCZ), the main rain bearing synoptic mechanism across tropical Africa. Thus, in addition to superior forecasts, the use of FSUSE based data sets may provide a better understanding of the dynamical processes within the ITCZ over the region. These results could be further improved if the daily series of operational analysis had included gauge data and if the resolution were higher. It is hardly possible to get uniformly consistent and continuous daily observations over these diverse regions of Africa. However, given the availability of the satellite based estimates of daily rainfall, such as CMORPH and global analysis that are exchanged very fast nowadays, the FSUSE scheme for numerical weather predictions (N W P) provides useful medium range weather forecasts in real-time.     

目标圆方法在船舶导航中的应用

根据多年指挥海上船舶绕避热带气旋的经验,提出了一种基于热带气旋预报目标圆的绕避热带气旋方法。文中给出了目标圆方法的基本原理、操作流程和关键技术,介绍了实际使用此方法成功指挥船舶绕避热带气旋的实例。统计结果表明,近年来此方法的使用效果和效益评估情况良好,具有较高的使用价值。这种绕避热带气旋的方法同样适用于船舶绕避爆发性气旋。     

Forecasting hurricane winds in extratropical cyclones in Russia

In contrast to the common opinion, hurricane winds in extratropical cyclones are a quite frequent phenomenon followed by huge damage, especially in densely populated areas. This phenomenon has been poorly studied and is hardly predictable so far. The features of hurricane winds in extratropical cyclones, and the similarity and difference in their structure as compared to those in tropical cyclones are revealed.     

Application of evidence theory to quantify uncertainty in hurricane/typhoon track forecasts

Summary In the paper, a new technique to quantify the accuracy of models for weather prediction in forecasting tracks of tropical cyclones using the available best track database is presented. Also a new approach to quantify and improve the accuracy of tropical cyclone track forecasts where no best track positions are available is suggested. Both techniques rely on the mathematical tools of evidence theory, which are customized here for application to total uncertainty in track forecasts.     

Tropical and extratropical cyclone damages under climate change

This paper provides the first quantitative synthesis of the rapidly growing literature on future tropical and extratropical cyclone damages under climate change. We estimate a probability distribution for the predicted impact of changes in global surface air temperatures on future storm damages, using an ensemble of 478 estimates of the temperature-damage relationship from nineteen studies. Our analysis produces three main empirical results. First, we find strong but not conclusive support for the hypothesis that climate change will cause damages from tropical cyclones and wind storms to increase, with most models predicting higher future storm damages due to climate change. Second, there is substantial variation in projected changes in losses across regions. Potential changes in damages are greatest in the North Atlantic basin, where the multi-model average predicts that a 2.5 °C increase in global surface air temperature would cause hurricane damages to increase by 63 %. The ensemble predictions for Western North Pacific tropical cyclones and European wind storms (extratropical cyclones) are +28 % and +23 %, respectively. Finally, our analysis shows that existing models of storm damages under climate change generate a wide range of predictions, ranging from moderate decreases to very large increases in losses.     

北半球中纬度地区地面气温的超级集合预报

基于TIGGE资料中的ECMWF、JMA、NCEP和UKMO四个中心2007年6月1日-8月31日北半球中纬度地区地面气温24～168 h集合预报资料,分别利用固定训练期超级集合(SUP, Superensemble)和滑动训练期超级集合(R-SUP, Running Training Period Superensemble )对2007年8月8-31日预报期24 d进行超级集合预报试验.采用均方根误差对预报结果进行检验评估,比较了两种超级集合方法与最好的单个中心模式预报、多模式集合平均的预报效果.结果表明,SUP预报有效降低了预报误差,24～144 h的预报效果优于多模式集合平均(EMN, Ensemble Mean)和最好的单个中心预报,168 h的预报效果略差于EMN.R-SUP预报进一步改善了预报效果.对于24～168 h的预报,R-SUP预报效果都要优于EMN.尤其对于168 h的预报,R-SUP改进了预报效果,优于EMN.