9403号热带气旋综合分析

从天气形势、能量场的角度分析９４０３号热带气旋移动路径发生转向的原因有：（１）冷空气西路南下，阻止热带气旋向西移动；（２）高空槽东移、副高减弱东撤、引导气流发生变化；（３）热带气旋沿高能轴（舌）移动。造成玉林地区出现大暴雨的主要原因是：（１）热带气旋中心从玉林地区经过；（２）出现了典型的北槽南台的形势；（３）偏北、偏东、偏西南气流的强辐合；（４）热带气旋移速慢。     

应用数值产品作热带气旋登陆地段释用预报

本方法是在对数值预告图作大量统计的基础上,将数值产品中５００ｈＰａ涡度场、实时５００ｈＰａ华南区域高度场、能量场,广东沿海各指标站气压变量等有机结合,制作出热带气旋未来３６～４８小时移动路径和可能登陆的地段。这是一种较客观的预报方法,简便易操作,自９０年代初使用至今,效果较好,尤其对一些路径异常的热带风暴,有很好的预报能力。１ 技术规定 （１）当热带气旋进人江门市热带气旋警戒区第二防区（或在该区域生成的热带气旋）作为进防。 （２）热带气旋进防当日为起报日,作出热带气旋移动路径和登陆点及登陆地段预报…     

西北太平洋热带气旋路径时间标度律的研究

时间标度计算表明，西北太平洋热带气旋路径是一个无标度性的系统，其关联方差谱遵从频率的－２￣－３次方幂律，不同背景下的路径系统均如此。由此得到的不同季节、不同地域的热带气旋路径可预报时间尺度基本上为３￣４ｄ，但异常热带气旋路径的可预报时间尺度则为１￣２ｄ。     

用统计动力方法作盛夏南海中北部热带气旋强度预报

对1960～2002年盛夏（7～9月）在南海中北部海域活动的热带气旋，引入欧洲中心（ECMWF）数值预报格点资料，采用移动坐标，选用有关热带气旋自身特征变量及环境场等物理量动力因子，用多元回归方法，建立热带气旋强度的动力统计预报模式，结果表明该模式较单纯靠天气学经验的预报能力有明显提高。     

斜压涡旋中的通风气流与热带气旋移动的关系

应用准地转斜压模式数值模拟了热带气旋的移动。将热带气旋的流场分解为轴对称分量和非对称分量，研究非对称流场中的通风气流矢量与热带气旋移动矢量的关系。数值试验结果表明：（１）在热带气旋的非对称流场中，不但有大尺度β涡旋，而且还有小尺度涡旋。（２）小尺度涡旋与大尺度β涡旋之间的相互作用导致热带气旋移向的摆动和移速的振荡。（３）应用Ｆｉｏｒｉｎｏ和Ｅｌｓｂｅｒｒｙ的方法计算的通风气流矢量与热带气旋移动矢量有很大偏差。（４）应用改进的方法计算的通风气流矢量与热带气旋移动矢量相关密切。     

一段计算台风移向移速的程序

在热带气旋预报服务中，常常遇到要计算从一点到另一点的方向和距离（或移速）的问题。例如，热带气旋用at的时间从点从中（A）移到点B，其移动的距离是多少，移向移速又是多少？又如，热带气旋位于点，为海上作业平台提供服务的预报员又如何能准确说出其位于作业点的什么方位，距离多少公里呢？国家气象局天气预报警报管理司1991年5月制定的（台风业务服务规定）附件6－2“台风（热带风暴）定位和预报质量评定办法”中给出了评定热带气旋定位或预报位置误差和方向误差的计算公式。计算位置误差R的公式为：这里a—637Ibm，地球半径。方向…     

登陆辽宁热带气旋特征的统计分析

利用1949-2010年热带气旋年鉴资料和常规气象观测资料,对62a来登陆辽宁热带气旋的生成源地、移动路径、登陆地点、登陆强度、登陆后影响时间等进行统计分析,揭示登陆辽宁热带气旋活动特征。结果表明：1949-2010年共有18个热带气旋登陆影响辽宁,66℅以热带低压（TD）的强度登陆,61℅在08-20时之间登陆,78℅在辽宁境内活动时间为6-12h,89℅是在其他地区登陆进入黄渤海后在辽宁再次登陆,大连是登陆次数最多的地区,33℅登陆辽宁后减弱消失,登陆后移动路径主要有向东北向、偏北向、西北向3种移动路径。在此基础上,根据业务需求建立了基于副热带高压、气旋源地和热带气旋前期路径等因子,预报登陆辽宁热带气旋后期走向[0]的预报关键区,为热带气旋预报工作提供参考。     

数值预报产品检验和评估

通过国家级数值预报T213模式、EC模式下发产品对影响海南的热带气旋主观性检验结果表明,T213模式不管是对稳定路径还是转折路径的热带气旋在生成、移动路径以及登陆点都与实况相差很大;而EC模式对不管是转折还是稳定路径的热带气旋,都能够对移动路径、登陆点以及转折点都能够做出准确的预报;而在客观性检验的结果中也可看出T213模式和EC模式的预报能力的优劣性。因此,总体来说,在热带气旋的数值预报产品中,EC模式的预报能力明显比T213模式强,具有很高的参考意义。另外在温度场的预报中,T213模式相对于MM5模式,其预报能力具有一定的可信度,在日常预报中具有参考价值。     

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     

不同物理过程参数化对模式台风的影响及其动力结构的研究

文章介绍了国家气象中心的台风路径数值预报模式（以下简称台风模式）,在不同物理过程参数化下的数值试验及其结果的诊断分析。对1992年第10号热带气旋和1996年第8号热带气旋个例的数值试验结果表明,该模式能较好地预报热带气旋移动路径和登陆地点,且考虑复杂物理过程的台风模式较简单过程的模式能更好地描述热带气旋中心附近高低层的热力状况。研究还发现,500或700 hPa湿位涡第一项MPV1负值中心的绝对值大小的变化可反映热带气旋的强弱;且850 hPa上升运动最大中心的位置对未来6～12 h热带气旋的移向有较好     

Determination of the Backward Predictability Limit and Its Relationship with the Forward Predictability Limit

In this work, two types of predictability are proposed—forward and backward predictability—and then applied in the nonlinear local Lyapunov exponent approach to the Lorenz63 and Lorenz96 models to quantitatively estimate the local forward and backward predictability limits of states in phase space. The forward predictability mainly focuses on the forward evolution of initial errors superposed on the initial state over time, while the backward predictability is mainly concerned with when the given state can be predicted before this state happens. From the results, there is a negative correlation between the local forward and backward predictability limits. That is, the forward predictability limits are higher when the backward predictability limits are lower, and vice versa. We also find that the sum of forward and backward predictability limits of each state tends to fluctuate around the average value of sums of the forward and backward predictability limits of sufficient states.Furthermore, the average value is constant when the states are sufficient. For different chaotic systems, the average value is dependent on the chaotic systems and more complex chaotic systems get a lower average value. For a single chaotic system,the average value depends on the magnitude of initial perturbations. The average values decrease as the magnitudes of initial perturbations increase.     

Predictability of the atmosphere

This paper makes a review on the predictability of the atmosphere. The essential problems of predictability theo-ry, i.e., how a deterministic system changes to an undeterministic system (chaos) and how is the opposite (order within chaos), are discussed. Some applications of predictability theory are given.     

On the chaotic behavior and predictability of the real atmosphere

In this paper the concept of Chaos and its applications to the study of predictability theory is introduced. The au-thor’s attempt is to give a general overview of ideas and methods involved in this problem to scientists, who are inter-ested in the problem of predictability but not familiar with the theory of chaos. The problem is discussed in 4 sections. In the first section, the concept of chaos and the study methods are outlined briefly; in the second section, the methods of quantitatively measuring the main characteristics of chaos which are the basis for the predictability theory are in-troduced; the third section discusses the time series analysis for directly studying chaotic phenomena in practical prob-lems; and the last section presents some research results on the chaotic characteristics and the predictability of the real atmosphere.     

气候系统可预报性理论研究

介绍了作者近年来关于气候系统可预报性理论研究的一些工作,包括:非线性最快增长扰动理论以及在气候预测的可预报性研究中的应用;从一个新的角度研究了2类可预报性问题,并提出可预报性的3类子问题;根据计算不确定性原理,讨论了模式可预报性与机器精度的关系;探讨了可预报性与时空尺度的关系,建立了可预报性的相对观.     

随机误差对混沌系统可预报性的影响

根据非线性局部Lyapunov指数的方法, 以Logistic映射和Lorenz系统的试验数据序列为例, 研究了在初始误差存在的情况下, 随机误差对混沌系统可预报性的影响。结果表明: 初始误差和随机误差对可预报期限影响所起的作用大小主要取决于两者的相对大小。当初始误差远大于随机误差时, 系统的可预报期限主要由初始误差决定, 可以不考虑随机误差对预报模式可预报性的影响; 反之, 当随机误差远大于初始误差时, 系统的可预报期限主要由随机误差决定; 当初始误差和随机误差量级相当时, 两者都对系统的可预报期限起重要作用。在后两种情况下, 在考虑初始误差对可预报性影响的同时还必须考虑随机误差的作用。此外, 我们在已知系统精确的控制方程和误差演化方程的条件下, 研究了随机误差对可预报性的影响, 理论所得结果与试验数据所得结果相似。这表明在随机误差较小的情况下, 对系统可预报期限的估计相对准确, 但在随机误差较大的情况下, 可预报期限的估计误差也较大。本文利用三种不同的滤波方法对序列进行了试验, 结果表明, Lanczos高通滤波得到的高频序列与原始加入的噪声序列无论是在强度上还是在演变趋势上都表现得相当一致, 其能有效地去除高频噪音继而提高对系统的可预报期限的估计, 这对实际气象观测资料如何有效地去除噪音具有一定的启发意义。     

Relationships between the Limit of Predictability and Initial Error in the Uncoupled and Coupled Lorenz Models

In this study, the relationship between the limit of predictability and initial error was investigated using two simple chaotic systems:the Lorenz model, which possesses a single characteristic time scale, and the coupled Lorenz model, which possesses two different characteristic time scales. The limit of predictability is defined here as the time at which the error reaches 95% of its saturation level; nonlinear behaviors of the error growth are therefore involved in the definition of the limit of predictability. Our results show that the logarithmic function performs well in describing the relationship between the limit of predictability and initial error in both models, although the coefficients in the logarithmic function were not constant across the examined range of initial errors. Compared with the Lorenz model, in the coupled Lorenz model-in which the slow dynamics and the fast dynamics interact with each other-there is a more complex relationship between the limit of predictability and initial error. The limit of predictability of the Lorenz model is unbounded as the initial error becomes infinitesimally small; therefore, the limit of predictability of the Lorenz model may be extended by reducing the amplitude of the initial error. In contrast, if there exists a fixed initial error in the fast dynamics of the coupled Lorenz model, the slow dynamics has an intrinsic finite limit of predictability that cannot be extended by reducing the amplitude of the initial error in the slow dynamics, and vice versa. The findings reported here reveal the possible existence of an intrinsic finite limit of predictability in a coupled system that possesses many scales of time or motion.     

Decadal predictability of the Atlantic meridional overturning circulation and climate in the IPSL-CM5A-LR model

This study explores the decadal potential predictability of the Atlantic Meridional Overturning Circulation (AMOC) as represented in the IPSL-CM5A-LR model, along with the predictability of associated oceanic and atmospheric fields. Using a 1000-year control run, we analyze the prognostic potential predictability (PPP) of the AMOC through ensembles of simulations with perturbed initial conditions. Based on a measure of the ensemble spread, the modelled AMOC has an average predictive skill of 8 years, with some degree of dependence on the AMOC initial state. Diagnostic potential predictability of surface temperature and precipitation is also identified in the control run and compared to the PPP. Both approaches clearly bring out the same regions exhibiting the highest predictive skill. Generally, surface temperature has the highest skill up to 2 decades in the far North Atlantic ocean. There are also weak signals over a few oceanic areas in the tropics and subtropics. Predictability over land is restricted to the coastal areas bordering oceanic predictable regions. Potential predictability at interannual and longer timescales is largely absent for precipitation in spite of weak signals identified mainly in the Nordic Seas. Regions of weak signals show some dependence on AMOC initial state. All the identified regions are closely linked to decadal AMOC fluctuations suggesting that the potential predictability of climate arises from the mechanisms controlling these fluctuations. Evidence for dependence on AMOC initial state also suggests that studying skills from case studies may prove more useful to understand predictability mechanisms than computing average skill from numerous start dates.     

近二十年来暴雨和强对流可预报性研究进展

大气可预报性研究是开展天气、气候预测的基础科学问题。全球变暖背景下,近年暴雨和强对流等中小尺度灾害性天气频发,如何深入认识其可预报性问题成为了天气领域研究热点,也是制约数值天气预报模式能力提升的重要因素。本文在简要回顾国内外大气可预报性研究历程的基础上,重点对近二十年（1999～2018）国际上关于暴雨和强对流可预报性方面的最新研究进展进行了系统的综述和归纳。主要包括:中小尺度可预报性研究的主要方法和评估手段及其与传统大尺度天气可预报性研究的差异,初始误差增长机制的几种主要观点及其争论（误差升尺度、误差降尺度、升降尺度并存）,数值模式误差和对流环境误差对实际预报性的影响,以及最近的中尺度可预报性科学观测试验进展等。最后,对暴雨、强对流可预报性研究存在的问题、未来发展方向进行了简要的讨论和展望。     

Estimating the Predictability Limit of Tropical Cyclone Tracks over the Western North Pacific Using Observational Data

In this study, the nonlinear local Lyapunov exponent (NLLE) approach was used to quantitatively determine the predictability limit of tropical cyclone (TC) tracks based on observed TC track data obtained from the Joint Typhoon Warning Center. The results show that the predictability limit of all TC tracks over the whole western North Pacific (WNP) basin is about 102 h, and the average lifetime of all TC tracks is about 174 h. The predictability limits of the TC tracks for short-, medium-, and long-lived TCs are approximately 72 h, 120 h, and 132 h, respectively. The predictability limit of the TC tracks depends on the TC genesis location, lifetime, and intensity, and further analysis indicated that these three metrics are closely related. The more intense and longer-lived TCs tend to be generated on the eastern side of the WNP (EWNP), whereas the weaker and shorter-lived TCs tend to form in the west of the WNP (WWNP) and the South China Sea (SCS). The relatively stronger and longer-lived TCs, which are generated mainly in the EWNP, have a longer travel time before they curve northeastwards and hence tend to be more predictable than the relatively weaker and shorter-lived TCs that form in the WWNP region and SCS. Furthermore, the results show that the predictability limit of the TC tracks obtained from the best-track data may be underestimated due to the relatively short observational records currently available. Further work is needed, employing a numerical model to assess the predictability of TC tracks.     

Recent Advances in Predictability Studies in China （1999-2002）

Since the last International Union of Geodesy and Geophysics (IUGG) General Assembly (1999), the predictability studies in China have made further progress during the period of 1999-2002. Firstly, three predictability sub-problems in numerical weather and climate prediction are classified, which are concerned with the maximum predictability time, the maximum prediction error, and the maximum allowable initial error, and then they are reduced into three nonlinear optimization problems. Secondly, the concepts of the nonlinear singular vector (NSV) and conditional nonlinear optimal perturbation (CNOP) are proposed,which have been utilized to study the predictability of numerical weather and climate prediction. The results suggest that the nonlinear characteristics of the motions of atmosphere and oceans can be revealedby NSV and CNOP. Thirdly, attention has also been paid to the relations between the predictability and spatial-temporal scale, and between the model predictability and the machine precision, of which the investigations disclose the importance of the spatial-temporal scale and machine precision in the study of predictability. Also the cell-to-cell mapping is adopted to analyze globally the predictability of climate,which could provide a new subject to the research workers. Furthermore, the predictability of the summer rainfall in China is investigated by using the method of correlation coefficients. The results demonstrate that the predictability of summer rainfall is different in different areas of China. Analysis of variance, which is one of the statistical methods applicable to the study of predictability, is also used to study the potential predictability of monthly mean temperature in China, of which the conclusion is that the monthly mean temperature over China is potentially predictable at a statistical significance level of 0.10. In addition,in the analysis of the predictability of the T106 objective analysis/forecasting field, the variance and the correlation coefficient are calculated to explore the distribution characteristics of the mean-square errors.Finally, the predictability of short-term climate prediction is investigated by using statistical methods or numerical simulation methods. It is demonstrated that the predictability of short-term climate in China depends not only on the region of China being investigated, but also on the time scale and the atmospheric internal dynamical process.