MJO预报研究进展

热带大气季节内振荡 (Madden-Julian oscillation,MJO) 是次季节-季节时间尺度气候变率的支配模态。它不仅对低纬度地区天气气候产生重要影响,还能够通过经向传播和激发大气遥相关波列对中高纬度地区产生影响,是延伸期尺度最重要的可预报性来源。因此,MJO预报是次季节-季节气候预测中极为重要的部分,近年来受到国际学术界广泛关注。该文回顾了MJO预报发展历史,概述了当前国际上主要科研业务机构的MJO预报发展现状。目前基于统计方法和气候模式的MJO预报研究取得了较大进展,特别是多个耦合气候模式和一种基于时空投影方法的统计模型均能够显著提升MJO预报技巧 (有效预报可达20 d以上)。该文还介绍了中国气象局国家气候中心在MJO预报技术发展和业务系统研制方面的新进展,当前基于第2代大气环流模式的MJO业务预报填补了国内空白,技巧为16~17 d,而耦合气候模式试验的技巧已达到约20 d。总体来看,利用耦合模式预报MJO是未来发展的主要方向,其中,面向MJO的模式初始化和集合预报新方法研究将是关注重点。     

世界气象中心(北京)全球预报服务共享平台设计与实现

世界气象中心(北京)建设是中国气象局承担世界气象组织(WMO)的全球数据处理和预报系统(GDPFS)要求的任务,为全球实时气象预报预测业务提供高效丰富的无缝隙天气气候监测、预报、预测分析指导产品及数据产品服务共享,提高区域性国际天气业务会商交流效率,国家气象中心设计并实现了世界气象中心(北京)全球预报服务共享平台,通过分析全球监测、预报预测等业务数据海量、异构、实时性强等特征,采用浏览器/服务器(B/S结构)多层架构和分布式实时处理、任务调度等关键技术实现了全球实况监测、天气模式、气候模式、模式检验数据的高效加工预处理、产品分析制作、产品自动流转、网络服务共享和业务指导等全流程业务功能,并提供了国际天气预报会商等专业化功能。平台自2018年6月6日业务运行以来,已有13个国家和地区注册会商用户,超过15万次全球访问量,为全球专业用户高效提供了全球实时天气监测、预报服务产品业务指导,未来将成为中国气象局对外气象业务指导和气象服务的重要窗口和纽带。     

国家气候中心MJO监测预测业务产品研发及应用

热带大气低频振荡 (MJO) 和北半球夏季季节内振荡 (BSISO) 对全球范围天气气候事件有重要影响,是次季节-季节 (S2S) 预报最主要的可预报性来源之一。国家气候中心 (BCC) 基于我国完全自主的T639全球分析场数据、风云三号气象卫星射出长波辐射 (OLR) 资料以及BCC第2代大气环流模式系统的实时预报,发展了MJO实时监测预测一体化业务技术,建立了ISV/MJO监测预测业务系统 (IMPRESS1.0),已投入实时业务运行,在全国气象业务系统得到应用。该文着重介绍该系统提供的MJO和BSISO指数监测预测数据和图形产品,并描述了这些业务产品在2015年对MJO典型个例的实时监测预测应用情况。监测分析和预报检验表明,基于我国自主资料的监测结果能够较为准确地表征MJO和BSISO指数的振荡和演变过程,该系统对MJO和BSISO事件分别至少具备16 d和10 d左右的预报技巧。因此,基于IMPRESS1.0的MJO/BSISO监测预测一体化业务产品可为制作延伸期预报提供重要的参考依据。     

MJO ensemble prediction in BCC-CSM1.1 (m) using different initialization schemes

热带大气季节内振荡(MJO)预报是国际研究热点,我国尚处于起步阶段。近些年国际上MJO预报水平得到大幅提升,主要得益于包含海气耦合过程的气候模式的使用,这其中模式预报初始化和集合扰动生成方法至关重要。本文发展了适用于国家气候中心第二代气候预测业务模式BCC-CSM1.1(m)的MJO初始化方案,并在此基础上提出了基于不同初始化方案形成扰动的集合预报新方法,可以将MJO有技巧预报时效延长到约20天,为次季节-季节预报提供重要依据。     

气候变化对延伸期预报的影响

10～30 d时效的延伸期预报,作为无缝隙预报预测体系中至关重要的一环,连接着天气预报和短期气候预测。受不断加剧的气候变化的影响,延伸期预报将面临更为重大的挑战。首先概述国内外延伸期预报现状,然后分析了全球气候变化对极端天气气候事件分布特征、关键环流系统可预报性等方面的影响,发现气候变化将导致延伸期预报难度加大、需求更加旺盛,同时也更加突显延伸期预报在防灾减灾方面的作用。进一步展望延伸期预报将面临的新挑战以及未来业务发展的新动向,提出了适应气候变化的应对措施和建议,如大力发展数值预报模式、深入开展延伸期预报机理研究、大力发展动力—统计相结合的预报方法以及尝试多学科交叉协作等。     

新型天气预报业务系统框架

在兰州区域气象中心ＤＥＣ业务网络下运行的新型天气预报业务系统,对西北地区东部的重要天气,按中短期预报时效,以模块的方式建立预报系统;以引进人工智能神经元网络技术,预报甘肃省降水天气。该系统经试运行,具有业务实用性强、预报效果较好等特点     

ECWMF高分辨率模式2m温度预报在六盘水市的误差分析及订正指标

采用气候概率统计和多时效平均的思路,对2018—2019年的欧洲中期天气预报中心（ECWMF）高分辨率模式2 m温度产品在六盘水市的预报误差进行统计分析,并对采用指标订正后的2020年度模式预报准确率进行检验评估。结果表明：ECWMF高分辨率模式对六盘水市的温度预报误差随时效的增加而逐渐减小,且各时效平均的最高温度年均预报误差和误差标准差要明显高于最低温度;对于六盘水而言,模式的温度预报在初夏（6月）可靠性最高,而在春季（3—4月）最低;通过采用预报误差最大占比对逐月多时效平均的模式最低温度预报进行订正,以及根据天气类型采用不用订正方式与订正指标对模式24 h最高温度预报进行订正,能够大幅提升全市未来5 d（120 h）综合最低温度和24 h内的最高温度预报准确率,分别稳定在90%和70%以上;经过订正后,全市的2020年度平均最低温度预报准确率与实际相当,而24 h最高温度预报准确率要高于实际预报准确率。     

ECMWF未来10年“2+4+1”战略:将天气气候预报引向极致

正2016年7月,欧洲中期天气预报中心(ECMWF)推出了其未来10年(2016—2025年)战略。这份36页的文件,让更多的人对未来10年天气气候预报能力的提升充满期待。这份新的10年战略,其最重要的,ECMWF在报道中用"苛刻"来形容的目标,可以用"2+4+1"来概括:即到2025年,1)高影响天气的有效集合预报提前2周;2)大尺度形势和机制转化预报提前4周;3)全球尺度异常预测提前1年。     

西北天气预报业务历程和发展机遇

西北天气预报业务历程和发展机遇夏建平，陈敏连（兰州中心气象台７３００２０）１９９３年９月兰州区域气象中心宣告成立，标志着西北气象业务上了一个新的台阶。一批现代化业务设备为天气气候工作创造了较为良好的工作环境，尤其对实时性较强的天气分析和预报服务工作提...     

加拿大气象中心的数值预报模式和有关研究

加拿大气象中心(CMC)主要从事中短期数值天气预报业务和有关研究.下面我们分别进行叙述.第一部分中短期数值天气预报业务制作中短期数值天气预报业务的模式有两个,即有限区域半隐式半拉格朗日有限元模式和半球谱模式.前者主要作48小时以内的天气和形势预报;后者主要作3到5天的天气和形势预报.     

Skill Assessment of Copernicus Climate Change Service Seasonal Ensemble Precipitation Forecasts over Iran

Medium to long-term precipitation forecasting plays a pivotal role in water resource management and development of warning systems.Recently,the Copernicus Climate Change Service(C3S)database has been releasing monthly forecasts for lead times of up to three months for public use.This study evaluated the ensemble forecasts of three C3S models over the period 1993-2017 in Iran’s eight classified precipitation clusters for one-to three-month lead times.Probabilistic and non-probabilistic criteria were used for evaluation.Furthermore,the skill of selected models was analyzed in dry and wet periods in different precipitation clusters.The results indicated that the models performed best in western precipitation clusters,while in the northern humid cluster the models had negative skill scores.All models were better at forecasting upper-tercile events in dry seasons and lower-tercile events in wet seasons.Moreover,with increasing lead time,the forecast skill of the models worsened.In terms of forecasting in dry and wet years,the forecasts of the models were generally close to observations,albeit they underestimated several severe dry periods and overestimated a few wet periods.Moreover,the multi-model forecasts generated via multivariate regression of the forecasts of the three models yielded better results compared with those of individual models.In general,the ECMWF and UKMO models were found to be appropriate for one-month-ahead precipitation forecasting in most clusters of Iran.For the clusters considered in Iran and for the long-range system versions considered,the Météo France model had lower skill than the other models.     

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.     

Integration of synoptic and hydrodynamic monthly air temperature forecasts

The results of experiments on the integration of synoptic and hydrodynamic forecasts of monthly air temperature for the northwestern part of Eurasia for the period of 2011–2015 are presented. The comprehensive comparison of skill scores of individual and integrated forecasts is provided. It is demonstrated that during the cold season hydrodynamic forecasts have the highest skills among the other forecasts. It is revealed that empirical methods are characterized by the forecast skill increase in summer and by its decrease in winter and during the period of spring transformation of atmospheric circulation. In most cases the integration of diverse methods allows combining their benefits and improving the resultant forecast skill. The synchrony was detected in the forecast skill variations. It is shown that the forecast skill mainly depends on the persistence of macrocirculation patterns.     

Improving multimodel weather forecast of monsoon rain over China using FSU superensemble

In this paper we present the current capabilities for numerical weather prediction of precipitation over China using a suite of ten multimodels and our superensemble based forecasts. Our suite of models includes the operational suite selected by NCARs TIGGE archives for the THORPEX Program. These are: ECMWF, UKMO, JMA, NCEP, CMA, CMC, BOM, MF, KMA and the CPTEC models. The superensemble strategy includes a training and a forecasts phase, for these the periods chosen for this study include the months February through September for the years 2007 and 2008. This paper addresses precipitation forecasts for the medium range i.e. Days 1 to 3 and extending out to Day 10 of forecasts using this suite of global models. For training and forecasts validations we have made use of an advanced TRMM satellite based rainfall product. We make use of standard metrics for forecast validations that include the RMS errors, spatial correlations and the equitable threat scores. The results of skill forecasts of precipitation clearly demonstrate that it is possible to obtain higher skills for precipitation forecasts for Days 1 through 3 of forecasts from the use of the multimodel superensemble as compared to the best model of this suite. Between Days 4 to 10 it is possible to have very high skills from the multimodel superensemble for the RMS error of precipitation. Those skills are shown for a global belt and especially over China. Phenomenologically this product was also found very useful for precipitation forecasts for the Onset of the South China Sea monsoon, the life cycle of the mei-yu rains and post typhoon landfall heavy rains and flood events. The higher skills of the multimodel superensemble make it a very useful product for such real time events.     

OPERATIONAL ENSEMBLE FORECASTING AND ANALYSIS OF TROPICAL CYCLONES OVER THE WESTERN NORTH PACIFIC (INCLUDING THE SOUTH CHINA SEA)

Based on the tropical cyclone data from the Central Meteorological Observatory of China, Japan Meteorological Agency, Joint Typhoon Warning Center and European Centre for Medium-Range Weather Forecasts （ECMWF） during the period of 2004 to 2009, three consensus methods are used in tropical cyclone （TC） track forecasts. Operational consensus results show that the objective forecasts of ECMWF help to improve consensus skill by 2%, 3%-5% and 3%-5%, decrease track bias by 2.5 kin, 6-9 km and 10-12 km for the 24 h, 48 h and 72 h forecasts respectively over the years of 2007 to 2009. Analysis also indicates that consensus forecasts hold positive skills relative to each member. The multivariate regression composite is a method that shows relatively low skill, while the methods of arithmetic averaging and composite （in which the weighting coefficient is the reciprocal square of mean error of members） have almost comparable skills among members. Consensus forecast for a lead time of 96 h has negative skill relative to the ECMWF objective forecast.     

NCEP/CFS模式对东亚夏季延伸预报的检验评估

利用NCEP的气候预报系统（Climate Forecast System, CFS）所提供的1981—2004年历史回报试验结果,检验和评估了该系统对夏季东亚地区大气环流的预报技巧和系统误差;在此基础上通过提取模式预报和观测的10~20 d及30~60 d低频振荡分量,重点对我国南方3次典型持续性暴雨过程的预报技巧进行检验和诊断分析。结果表明:CFS系统对东亚整体大气环流逐日预报的可靠时效为5 d左右,60°N以北的对流层中高层高度场预报系统性偏低,而在40°~60°N则为系统性偏高。系统性误差随预报时间的延长而增加,但10 d以上预报的系统性误差大小和空间分布逐渐趋于稳定;CFS系统对低频分量的延伸期预报技巧好于对其整体大气环流的预报技巧,并且在典型持续性暴雨过程中,CFS系统对影响强降水过程的主要环流系统低频振荡特征有一定预报能力。     

Dust storm ensemble forecast experiments in East Asia

The ensemble Kalman filter (EnKF), as a unified approach to both data assimilation and ensemble forecasting problems, is used to investigate the performance of dust storm ensemble forecasting targeting a dust episode in the East Asia during 23–30 May 2007. The errors in the input wind field, dust emission intensity, and dry deposition velocity are among important model uncertainties and are considered in the model error perturbations. These model errors are not assumed to have zero-means. The model error me...     

基于TIGGE资料的地面气温多模式超级集合预报

基于TIGGE资料, 采用均方根误差分别对欧洲中期天气预报中心、日本气象厅、美国国家环境预报中心和英国气象局4个中心集合预报的地面气温场集合平均结果进行检验评估, 比较各中心地面气温的预报效果。并利用超级集合、多模式集合平均和消除偏差集合平均3种方法对4个中心的地面气温预报进行集成, 同时对预报结果进行分析。结果表明: 2007年夏季日本气象厅与欧洲中期天气预报中心在北半球大部分地区预报效果最好, 各中心在不同地区预报效果不同。超级集合与消除偏差集合平均降低了预报误差, 预报效果优于最好的单个中心预报和多模式集合平均。对于较长的预报时效, 消除偏差集合平均表现出了更好的预报性能。     

Operative Scheme for the Short-range Complex Forecasting of Surface Air Temperature and Humidity

The statistical scheme is proposed for the forecast of surface air temperature and humidity using operative weather forecasts with 3–5-day lead time from the best forecasting hydrodynamic models as well as the archives of forecasts of these models and observational data from 2800 weather stations of Russia, Eastern Europe, and Central Asia. The output of the scheme includes the forecasts of air temperature for the standard observation moments with the period of 6 hours and extreme temperatures with the lead times of 12–120 hours. The accuracy of temperature and humidity forecasts for the period from July 2014 till June 2017 is much higher than that for the forecasts of original hydrodynamic models. The skill scores for extreme temperature forecasts based on the proposed method are compared with the similar results of the Weather Element Computation (WEC) forecasting scheme and forecasts by weathermen.     

Western North Pacific Tropical Cyclone Intensity Guidance Evaluations Using an Alternative Verification Technique

In this study, six intensity forecast guidance techniques from the East China Regional Meteorological Center are verified for the 2008 and 2009 typhoon seasons through an alternative forecast verification technique. This technique is used to verify intensity forecasts if those forecasts call for a typhoon to dissipate or if the real typhoon dissipates. Using a contingency table, skill scores, chance, and probabilities are computed. It is shown that the skill of the six tropical cyclone intensity guidance techniques was highest for the 12-h forecasts, while the lowest skill of all the six models did not occur in 72-h forecasting. For both the 2008 and 2009 seasons, the average probabilities of the forecast intensity having a small error (6 m s-1) tended to decrease steadily. Some of the intensity forecasts had small skill scores, but the associated probabilities of the forecast intensity errors > 15 m s-1 were not the highest.