基于集合Kalman滤波数据同化的热带气旋路径集合预报研究

构建了一个基于集合Kalman滤波数据同化的热带气旋集合预报系统,通过积云参数化方案和边界层参数化方案的9个不同组合,采用MM5模式进行了不同时间的短时预报。对预报结果使用“镜像法”得到18个初始成员,为同化提供初始背景集合。将人造台风作为观测场,同化后的结果作为集合预报的初值,通过不同参数组合的MM5模式进行集合预报。对2003～2004年16个台风个例的分析表明,初始成员产生方法能够对热带气旋的要素场、中心强度和位置进行合理扰动。同化结果使台风强度得到加强,结构更接近实际。基于同化的集合路径预报结果要优于未同化的集合预报。使用“镜像法”增加集合成员提高了预报准确度,路径预报误差在48小时和72小时分别低于200 km和250 km。     

热带气旋路径集合预报试验

以MM5模式为试验模式,分别用增长模繁殖法（BGM）和模式物理过程扰（MPP）形成12个集合成员,对2005年登陆我国的8个热带气旋进行了52次路径集合预报试验,以寻找适合西北太平洋热带气旋路径的集合预报方法。结果表明：BGM方法的集合预报结果总体上好于控制试验结果,其中对强度较弱的热带气旋的集合预报效果更好。MPP方法的集合预报结果总体上不如控制试验结果,但对初始时刻强度达到台风的热带气旋的集合预报效果较好,集合预报相对于控制试验的改进效果明显。基于BGM方法和MPP方法集合预报的不同特点,将两种方法相结合形成扰动成员,这一综合方法的集合预报效果好于单一方法的集合预报效果。BGM方法和MPP方法的系统发散度总体上都偏小。     

Sample Optimization of Ensemble Forecast to Simulate a Tropical Cyclone Using the Observed Track

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.     

Sensitivity to Tendency Perturbations of Tropical Cyclone Short-range Intensity Forecasts Generated by WRF

The present study uses the nonlinear singular vector(NFSV) approach to identify the optimally-growing tendency perturbations of the Weather Research and Forecasting(WRF) model for tropical cyclone(TC) intensity forecasts. For nine selected TC cases, the NFSV-tendency perturbations of the WRF model, including components of potential temperature and/or moisture, are calculated when TC intensities are forecasted with a 24-hour lead time, and their respective potential temperature components are dem...     

基于路径相似的登陆热带气旋降水之动力-统计集合预报模型

数值天气预报(NWP)过去几十年在热带气旋(TC)预报方面的最大进步是越来越准确的路径预报。对于登陆TC降水的预报,目前以数值模式为代表的技术手段预报能力还十分有限。围绕动力-统计结合之方法研究,初步发展了登陆热带气旋降水(LTP)预报的一种新方法:基于路径相似的登陆热带气旋降水之动力统计集合预报(LTP_DSEF)模型。该方法主要分为五步:TC路径预报、相似路径TC识别、其他特征相似性的判别、TC降水集合预报和最佳预报方案选择;涉及两个关键技术:TC降水分离的客观天气图分析法(OSAT)和TC路径相似面积指数(TSAI)。LTP DSEF模型对2012-2016年影响华南地区出现最大日降水量≥100 mm的21个TC的定量降水预报(QPF)试验结果显示,该模型对登陆TC过程降水的预报结果优于动力模式。登陆TC过程降水≥50 mm情况下,建模样本和独立样本平均TS评分均高于动力模式(EC、GFS、T639)相应的最好表现。对LTP_DSEF模型三个最佳方案的参数取值分析显示,起报时刻参数设定为最临近影响时刻即TC对陆地产生降水的前一天12:00 UTC、集合参数取最大值时预报效果稳定趋好。     

Inducing Unstable Grassland Equilibrium States Due to Nonlinear Optimal Patterns of Initial and Parameter Perturbations: Theoretical Models

Due to uncertainties in initial conditions and parameters,the stability and uncertainty of grassland ecosystem simulations using ecosystem models are issues of concern.Our objective is to determine the types and patterns of initial and parameter perturbations that yield the greatest instability and uncertainty in simulated grassland ecosystems using theoretical models.We used a nonlinear optimization approach,i.e.,a conditional nonlinear optimal perturbation related to initial and parameter perturbations (CNOP) approach,in our work.Numerical results indicated that the CNOP showed a special and nonlinear optimal pattern when the initial state variables and multiple parameters were considered simultaneously.A visibly different complex optimal pattern characterizing the CNOPs was obtained by choosing different combinations of initial state variables and multiple parameters in different physical processes.We propose that the grassland modeled ecosystem caused by the CNOP-type perturbation is unstable and exhibits two aspects:abrupt change and the time needed for the abrupt change from a grassland equilibrium state to a desert equilibrium state when the initial state variables and multiple parameters are considered simultaneously.We compared these findings with results affected by the CNOPs obtained by considering only uncertainties in initial state variables and in a single parameter.The numerical results imply that the nonlinear optimal pattern of initial perturbations and parameter perturbations,especially for more parameters or when special parameters are involved,plays a key role in determining stabilities and uncertainties associated with a simulated or predicted grassland ecosystem.     

The Roles of Spatial Locations and Patterns of Initial Errors in the Uncertainties of Tropical Cyclone Forecasts

In this study,a series of sensitivity experiments were performed for two tropical cyclones (TCs),TC Longwang (2005) and TC Sinlaku (2008),to explore the roles of locations and patterns of initial errors in uncertainties of TC forecasts.Specifically,three types of initial errors were generated and three types of sensitive areas were determined using conditional nonlinear optimal perturbation (CNOP),first singular vector (FSV),and composite singular vector (CSV) methods.Additionally,random initial errors in randomly selected areas were considered.Based on these four types of initial errors and areas,we designed and performed 16 experiments to investigate the impacts of locations and patterns of initial errors on the nonlinear developments of the errors,and to determine which type of initial errors and areas has the greatest impact on TC forecasts.Overall,results from the experiments indicate the following:(1) The impact of random errors introduced into the sensitive areas was greater than that of errors themselves fixed in the randomly selected areas.From the perspective of statistical analysis,and by comparison,the impact of random errors introduced into the CNOP target area was greatest.(2) The initial errors with CNOP,CSV,or FSV patterns were likely to grow faster than random errors.(3) The initial errors with CNOP patterns in the CNOP target areas had the greatest impacts on the final verification forecasts.     

Evaluation of Tropical Cyclone Intensity Forecasts from Five Global EnsemblePrediction Systems During 2015-2019

This study presented an evaluation of tropical cyclone (TC) intensity forecasts from five global ensemble prediction systems (EPSs) during 2015-2019 in the western North Pacific region. Notable error features include the underestimation of the TC intensity by ensemble mean forecast and the under-dispersion of the probability forecasts.The root mean square errors (brier scores) of the ensemble mean (probability forecasts) generally decrease consecutively at long lead times during the five years, but fluctuate between certain values at short lead times.Positive forecast skill appeared in the most recent two years (2018-2019) at 120 h or later as compared with the climatology forecasts. However, there is no obvious improvement for the intensity change forecasts during the 5-yearperiod, with abrupt intensity change remaining a big challenge. The probability forecasts show no skill for strongTCs at all the lead times. Among the five EPSs, ECMWF-EPS ranks the best for the intensity forecast, while NCEP-GEFS ranks the best for the intensity change forecast, according to the evaluation for ensemble mean and dispersion. As for the other probability forecast evaluation, ECMWF-EPS ranks the best at lead times shorter than 72 h, while NCEP-GEFS ranks the best later on.     

基于非静力模式物理扰动的中尺度集合预报试验

以GRAPES中尺度有限区模式作为试验模式, 从模式的不确定性方面来构造中尺度的集合预报, 重点考虑物理因子与初始条件的扰动作用。针对2004年7月10日北京城区的突发性暴雨过程进行了36 h的集合预报试验。结果表明:GRAPES模式可有效地捕捉到中尺度过程的信息; 中尺度集合预报是可行的, 可改进中尺度暴雨过程落区、强度的预报; 不同集合方案的预报结果各不相同, 同一方案各个成员的预报结果也有差异, 即存在适宜的离散度; 在离散度分析中发现在北京附近存在一个明显大值区, 且在大气中低层的垂直结构表现出一致性, 表明这一区域的预报不确定性很大。从集合检验结果中得到:单纯考虑模式物理扰动来构造中尺度集合预报系统有一定难度, 当加入初始场不确定信息后, 同时考虑模式的不确定性和初始场的不确定性, 有助于捕捉更多的中尺度系统的不确定信息, 有助于构造更为有效的中尺度集合预报系统。     

2007年西北太平洋热带气旋定位和预报精度评定

依据<台风业务和服务规定>分析2007年TC业务定位和业务预报精度,结果表明:各方法的平均定位误差均小于25km,强度预报的24小时和48小时近中心最大风速平均误差为3～7m·s-1和5～11m·s-1,均与往年相当;综合预报的24小时和48小时路径平均距离误差分别为129.8km和215.0km.虽然路径数值预报的能力仍然不能与综合预报相比,但是多模式集成方法相对于综合预报有正技巧,说明这类方法可能成为改善路径预报的途径之一.强度预报的主要参考仍然是统计类预报方法.     

Growth and Interactions of Multi-Source Perturbations in Convection-Allowing Ensemble Forecasts

This study investigated the growth of forecast errors stemming from initial conditions (ICs), lateral boundary conditions (LBCs), and model (MO) perturbations, as well as their interactions, by conducting seven 36 h convection- allowing ensemble forecast (CAEF) experiments. Two cases, one with strong-forcing (SF) and the other with weak-forcing (WF), occurred over the Yangtze-Huai River basin (YHRB) in East China, were selected to examine the sources of uncertainties associated with perturbation growth under varying forcing backgrounds and the influence of these back- grounds on growth. The perturbations exhibited distinct characteristics in terms of temporal evolution, spatial propagation, and vertical distribution under different forcing backgrounds, indicating a dependence between perturbation growth and forcing background. A comparison of the perturbation growth in different precipitation areas revealed that IC and LBC perturbations were significantly influenced by the location of precipitation in the SF case, while MO perturbations were more responsive to convection triggering and dominated in the WF case. The vertical distribution of perturbations showed that the sources of uncertainties and the performance of perturbations varied between SF and WF cases, with LBC perturbations displaying notable case dependence. Furthermore, the interactions between perturbations were considered by exploring the added values of different source perturbations. For the SF case, the added values of IC, LBC, and MO perturbations were reflected in different forecast periods and different source uncertainties, suggesting that the combination of multi-source perturbations can yield positive interactions. In the WF case, MO perturbations provided a more accurate estimation of uncertainties downstream of the Dabie Mountain and need to be prioritized in the research on perturbation development.     

基于位置误差的分布制作热带气旋路径袭击概率预报

为了探讨热带气旋路径预报的不确定性,利用2004-2007年4年中央气象台综合预报的误差分布状况,建立热带气旋路径综合预报的统计集合模型,制作热带气旋路径的袭击概率预报及产品,并为警报发布工作中有关登陆地段的预报提供有意义的参考.     

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。     

基于TIGGE资料的西太平洋热带气旋多模式集成预报方法比较

基于TIGGE资料中CMA、ECMWF、JMA和NCEP四中心2010、2011和2012年3年的资料,采用集合平均（EMN）、加权集合平均（WEMN）、消除偏差集合平均（BREM）和加权消除偏差集合平均（即超级集合,SUP）四种方法,对西太平洋地区热带气旋路径与中心气压进行时效为24、48、72、96和120 h的多模式集成预报,评估了不同单中心预报结果,并分析了不同多模式集成预报方法的特点,对比了不同多模式集成方法的效果。结果表明,对于热带气旋路径和中心气压预报,各中心预报技巧不同,其中3年的CMA预报效果均较差,2010、2011年的ECMWF预报和2012年的NCEP预报效果最优;总体上几种多模式集成方法在120 h预报时效内均优于单模式预报,其中EMN作为一种最简单的集成预报方法,具有一定的局限性,而WEMN由于给不同单模式预报赋予了权重,因此相对于EMN能够得到更好的多模式集成预报结果;BREM方案由于消除了模式预报中的系统性偏差,因此集成预报效果也优于EMN;由于去除了模式预报偏差,同时给不同模式赋予了权重,SUP方案得到的集成预报效果最优。     

数值预报发展的新方向——集合数值预报

数值预报走过了百年的历史(V.Bjerknes,1904)[1],取得了了不起的成就,预报准确率有了很大的提高。但是,考虑到大气的非线性作用以及初值和模式造成的数值预报不确定性,要提高传统的单一确定性预报的技巧越来越难。基于大气初值的敏感性试验,Lorenz提出了数值预报发展的新方向——集合数值预报。通过介绍集合数值预报的基本思想和方法;并针对初值和模式的不确定性,概述现有集合数值预报成员的产生方法及国内外的研究进展;同时解释怎样检验集合预报的结果的论述,如何从众多的集合预报产品中提炼有用的信息及预报产品的释用。     

数值预报发展的新方向——集合数值预报

数值预报走过了百年的历史（V．Bjerknes，1904），取得了了不起的成就，预报准确率有了很大的提高。但是，考虑到大气的非线性作用以及初值和模式造成的数值预报不确定性，要提高传统的单一确定性预报的技巧越来越难。基于大气初值的敏感性试验，Lorenz提出了数值预报发展的新方向——集合数值预报。 通过介绍集合数值预报的基本思想和方法；并针对初值和模式的不确定性，概述现有集合数值预报成员的产生方法及国内外的研究进展；同时解释怎样检验集合预报的结果的论述，如何从众多的集合预报产品中提炼有用的信息及预报产品的释用。     

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.     

数值预报对热带气旋移动路径的预报能力的检验

作者利用１９９５年６－１０月影响南中国海的１０个热带气旋实况资料以及５００ｈＰａ天气图，对日本地面２４小时数值预报和ＥＣＭＷＦ５００ｈＰａ为数值预报产品对热带气旋移动路径的预报能力进行检验和分析，结果表明；１．日本的２４小时地面数值预报对热带气旋的路径趋势有一定的预报能力，它对路径稳定的热带气旋预报能力较好，对热带气旋的突变转折预报能力较差。２．ＥＣＭＷＦ５００ｈＰａ数值预报对热带气旋的移动路长有     

Algorithm Studies on How to Obtain a Conditional Nonlinear Optimal Perturbation (CNOP)

The conditional nonlinear optimal perturbation (CNOP), which is a nonlinear generalization of the linear singular vector (LSV), is applied in important problems of atmospheric and oceanic sciences, including ENSO predictability, targeted observations, and ensemble forecast. In this study, we investigate the computational cost of obtaining the CNOP by several methods. Differences and similarities, in terms of the computational error and cost in obtaining the CNOP, are compared among the sequential quadratic programming (SQP) algorithm, the limited memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) algorithm, and the spectral projected gradients (SPG2) algorithm. A theoretical grassland ecosystem model and the classical Lorenz model are used as examples. Numerical results demonstrate that the computational error is acceptable with all three algorithms. The computational cost to obtain the CNOP is reduced by using the SQP algorithm. The experimental results also reveal that the L-BFGS algorithm is the most effective algorithm among the three optimization algorithms for obtaining the CNOP. The numerical results suggest a new approach and algorithm for obtaining the CNOP for a large-scale optimization problem.     

热带气旋过程(动态)相似路径选取

热带气旋路径相似预报在目前的业务预报中仍占有很重要的地位，本系统采用各种历史资料及实时资料，结合主要天气系统和５００ｈＰａ数值预报形势场，选取热气旋路径０小时、２４小时、４８小时的相似个例，即它不但可以用实况场选取热带气旋的相似过程，而且可以根据数值预报形势场（包括预报热带低压位置）来动态的选取相似过程。