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1.
在动力相似预报中引入多个参考态的更新 总被引：7，自引：2，他引：7
针对如何更有效地利用历史资料中的相似信息提高预报水平的问题,在已有相似-动力模式研究基础上,进一步探讨了相似误差订正方法(ACE)的若干理论和技术问题,分析表明,ACE是对以相似离差方程和相似误差订正方程为理论依据的方法的再发展。在此基础上,提出了相似的更新问题和多个参考态的引入,并进而发展出一种考虑多参考态更新的动力相似预报新方法(MRSU)。这一方法通过引入相似更新周期的新概念,在预报进行到相似更新周期时重新选取多个参考态,并采用超平面近似法将相似-动力模式产生的多个预报估计成最佳预报向量,这样的“选取-估计”过程循环往复,从而完成整个时段的预报。Lorenz模式试验显示,相比于以往的相似-动力模式预报,MRSU能更有效减小预报误差,提高预报技巧,并且,ACE的理论优势应用前景也被初步证实。综合诸多研究结果,给出了MRSU的概念流程,这里针对复杂数值模式采用了ACE,能够等价实现相似-动力模式预报过程,无需重建模式,更易于推广。 相似文献
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通过讨论省 (甚至地、市) 气象部门要不要开展数值天气预报工作的问题, 认为不是所有的地方都要开展, 只是那些希望搞科研型业务、迫切要求提高当地高影响天气的预报准确率的地方要开展。对于如何开展的问题, 提出不是去重复类似于主流途径的做法, 而是开辟另类途径, 并阐述了另类途径的内容、方法和意义。强调开展另类途径无需构建模式 (这是非常困难的工作), 只需运转现成的模式, 借助所关心的现象的历史数据来改造现成模式, 使之本地化, 是完全可行的。 相似文献
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Initial condition and model errors both contribute to the loss of atmospheric predictability. However, it remains debatable which type of error has the larger impact on the prediction lead time of specific states. In this study, we perform a theoretical study to investigate the relative effects of initial condition and model errors on local prediction lead time of given states in the Lorenz model. Using the backward nonlinear local Lyapunov exponent method, the prediction lead time,also called local backward predictability limit(LBPL), of given states induced by the two types of errors can be quantitatively estimated. Results show that the structure of the Lorenz attractor leads to a layered distribution of LBPLs of states. On an individual circular orbit, the LBPLs are roughly the same, whereas they are different on different orbits. The spatial distributions of LBPLs show that the relative effects of initial condition and model errors on local backward predictability depend on the locations of given states on the dynamical trajectory and the error magnitudes. When the error magnitude is fixed, the differences between the LBPLs vary with the locations of given states. The larger differences are mainly located on the inner trajectories of regimes. When the error magnitudes are different, the dissimilarities in LBPLs are diverse for the same given state. 相似文献
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Analogue Correction Method of Errors by Combining Statistical and Dynamical Methods 总被引：1，自引：0，他引：1 
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下载免费PDF全文 Based on the atmospheric analogy principle, the inverse problem that the information of historical analogue data is utilized to estimate model errors is put forward and a method of analogue correction of errors (ACE) of model is developed in this paper. The ACE can combine effectively statistical and dynamical methods, and need not change the current numerical prediction models. The new method not only adequately utilizes dynamical achievements but also can reasonably absorb the information of a great many analogues in historical data in order to reduce model errors and improve forecast skill. Furthermore, the ACE may identify specific historical data for the solution of the inverse problem in terms of the particularity of current forecast. The qualitative analyses show that the ACE is theoretically equivalent to the principle of the previous analogue-dynamical model, but need not rebuild the complicated analogue-deviation model, so has better feasibility and operational foreground. Moreover, under the ideal situations, when numerical models or historical analogues are perfect, the forecast of the ACE would transform into the forecast of dynamical or statistical method, respectively. 相似文献
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Due to the increasing requirement for high-level weather and climate forecasting accuracy, it is necessary to exploit a strategy for model error correction while developing numerical modeling and data assimilation techniques. This study classifies the correction strategies according to the types of forecast errors, and reviews recent studies on these correction strategies. Among others, the analogue-dynamical method has been developed in China, which combines statistical methods with the dynamical model, corrects model errors based on analogue information, and effectively utilizes historical data in dynamical forecasts. In this study, the fundamental principles and technical solutions of the analogue-dynamical method and associated development history for forecasts on different timescales are introduced. It is shown that this method can effectively improve medium- and extended-range forecasts, monthly-average circulation forecast, and short-term climate prediction. As an innovative technique independently developed in China, the analogue- dynamical method plays an important role in both weather forecast and climate prediction, and has potential applications in wider fields. 相似文献
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提高月预报业务水平的动力相似集合方法 总被引：3，自引：0，他引：3
针对基于大气环流模式的月预报问题,提出了一种能有效减小预报误差并提高预报技巧的动力相似集合预报新方法。该方法着眼于动力模式与统计经验的内在结合,在模式积分过程中通过提取大气环流历史相似性信息,对模式误差进行参数化处理,形成多个时变的相似强迫量来扰动生成预报的集合成员。将这一集合新方法应用到中国国家气候中心业务大气环流模式(BCC AGCM1.0),一组10 a准业务环境下回报试验结果显示,相比于业务集合预报,动力相似集合预报方法能有效改进模式对于大气环流的纬向平均、超长波和长波预报,从而有效提高了月平均环流预报技巧(几乎达到业务可用标准)和逐日环流预报技巧,并显著降低了预报误差,合理增加集合离散度,使二者配置关系得以改善,有望在业务预报中应用。 相似文献
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Application of the Analogue-Based Correction of Errors Method in ENSO Prediction 总被引：2，自引：0，他引：2 下载免费PDF全文
下载免费PDF全文 In this study, a method of analogue-based correction of errors（ACE） was introduced to improve El Ni？o-Southern Oscillation（ENSO） prediction produced by climate models. The ACE method is based on the hypothesis that the flow-dependent model prediction errors are to some degree similar under analogous historical climate states, and so the historical errors can be used to effectively reduce such flow-dependent errors. With this method, the unknown errors in current ENSO predictions can be empirically estimated by using the known prediction errors which are diagnosed by the same model based on historical analogue states. The authors first propose the basic idea for applying the ACE method to ENSO prediction and then establish an analogue-dynamical ENSO prediction system based on an operational climate prediction model. The authors present some experimental results which clearly show the possibility of correcting the flow-dependent errors in ENSO prediction, and thus the potential of applying the ACE method to operational ENSO prediction based on climate models. 相似文献
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华北汛期降水多因子相似订正方案与预报试验 总被引：4，自引：2，他引：2
本文基于动力—相似预报的基本原理, 在已初步建立的华北汛期降水模式的动态最优多因子组合相似订正方案工作基础上, 研究前期关键因子之间的相互配置对夏季降水的影响, 挑选关键的大气环流预报因子。根据预报年前期气候因子的异常状况, 通过EOF压缩自由度进行相似年选取, 进一步构建了基于前期异常信号的汛期降水相似订正预报方案。研究发现, 预报年前期大气环流中异常因子个数的偏多或偏少与该年华北降水的多寡呈现较好的对应关系, 并以异常因子的个数状况作为判断该年是否为异常年的标准, 将异常多因子方案与动态最优多因子方案相结合, 建立模式误差相似订正的多因子综合预报方案。通过诊断分析发现, 该方案对降水异常年有着较好的针对性。2003～2009年7年的独立样本回报结果表明: 该方法进一步提高了模式对华北汛期降水的预报能力, 将华北汛期降水预报的距平相关系数 (ACC) 平均分从系统订正结果的0.38提高至0.61, 具有良好的业务应用前景。 相似文献
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统计-动力相结合的相似误差订正法 总被引：28，自引：6，他引：22
根据大气相似性原理,提出了利用历史资料的相似信息估计模式误差的反问题,并发展了一种相似误差订正(ACE)方法。该方法将统计和动力两种方法有机结合,在不改变现有数值预报模式的前提下,既充分利用了动力学发展的成就,又能够有效提取大量历史资料中的相似信息,达到减小模式误差、改进当前预报的目的。而且,ACE方法能够针对当前预报的特殊性来区分所利用过去资料的特殊性,提取历史相似信息间接求解反问题。定性分析表明,ACE方法与以往相似-动力模式原理是等价的,但无需重新建立复杂的相似离差预报模式,更具可行性和业务应用前景。在理想化的极限情形下,当数值模式或历史相似完全准确时,ACE方法的预报结果将分别蜕变为动力或统计学方法的预报结果。 相似文献
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The breeding method has been widely used in studies of data assimilation, predictability and instabilities. The bred vectors(BVs), which are the nonlinear difference between the control and perturbed runs, represent the time-evolving rapidly growing errors in dynamic systems. The Lorenz(1963) model(hereafter Lorenz63 model) has chaotic dynamics similar to weather and climate. This study investigates the features of BVs of the Lorenz63 model and its impact on regime prediction of the Lorenz63 model. The results show that the Lorenz63 model has two different BVs for each breeding cycle, and the two BVs approach being identical when growth rate is high. The duration of the current and next regime is associated with the relative directions between the BV with high growth rate and the model trajectory. 相似文献
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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. 相似文献
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It has been demonstrated that ensemble mean forecasts, in the context of the sample mean, have higher forecasting skill than deterministic(or single) forecasts. However, few studies have focused on quantifying the relationship between their forecast errors, especially in individual prediction cases. Clarification of the characteristics of deterministic and ensemble mean forecasts from the perspective of attractors of dynamical systems has also rarely been involved. In this paper, two attractor statistics—namely, the global and local attractor radii(GAR and LAR, respectively)—are applied to reveal the relationship between deterministic and ensemble mean forecast errors. The practical forecast experiments are implemented in a perfect model scenario with the Lorenz96 model as the numerical results for verification. The sample mean errors of deterministic and ensemble mean forecasts can be expressed by GAR and LAR, respectively, and their ratio is found to approach2~(1/2) with lead time. Meanwhile, the LAR can provide the expected ratio of the ensemble mean and deterministic forecast errors in individual cases. 相似文献
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数值模式预报时效对计算精度和时间步长的依赖关系 总被引：6，自引：0，他引：6
通过数值计算研究Lorenz非线性动力系统,探讨了非线性动力系统中初值问题的解对时间步长和计算精度的依赖关系,从新的角度研究动力系统的预报时效问题,讨论了评价舍入误差对预报时效影响程度的方法。实验结果表明:动力系统的预报时效不仅与初值误差有关,而且在一定条件下敏感地依赖于计算采用的时间步长和计算精度。 相似文献
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为了在动力季节预测中更好地运用统计经验来改进预报, 从研究气候系统物理因子影响模式预报误差的角度入手, 探讨了与气候模式有关的统计经验获取问题, 并利用国家气候中心海-气耦合模式的历史回报数据, 考察了动力季节预测中夏季环流和降水的预报误差与主要物理因子, 包括Ni?o3区海温指数、太平洋年代际振荡指数、南北半球环状模指数以及北大西洋涛动指数相关关系。分析结果显示:上述物理因子与模式预报的夏季环流和降水误差之间存在前期或同期的某种显著相关关系, 并且显著关系分布随因子的不同而表现出明显不同的区域性特征, 这为发展一种基于预报因子的误差订正新方法提供了新思路。 相似文献
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GRAPES全球奇异向量方法改进及试验分析 总被引：4，自引：0，他引：4
基于总能量模的奇异向量扰动常用于构造集合预报的初始条件。以建立GRAPES（Global and Regional Assimilation PrEdiction System）全球集合预报系统为目的,基于前期研发的GRAPES全球模式奇异向量方法,在GRAPES全球切线性模式和伴随模式2.0版的框架下,开展了引入线性化边界层方案来改善奇异向量结构,并提高奇异向量计算效率的研究。通过连续试验,从奇异向量的扰动能量结构、扰动能量谱及扰动空间分布等方面,综合分析改进GRAPES全球奇异向量的结构及演变特征。试验结果表明,改进后的GRAPES奇异向量方法有效抑制了之前扰动能量在近地面层不合理的快速增长,同时,奇异向量最优扰动的结构更客观地体现了中高纬度区域大气初始条件中的斜压不稳定扰动及其演变,如在初始时刻奇异向量扰动能量主要位于对流层中层,并呈现出随高度向西倾斜的大气斜压特征;经过线性化演变,扰动能量向较大水平尺度转移,并在垂直结构上表现出向对流层高层上传及向对流层低层下传的特征等。针对GRAPES奇异向量迭代求解中伴随模式计算耗时为主的情况,改进伴随模式中广义共轭余差方案的调用方式,并采用大内存存储法来提高其计算效率,进而将奇异向量总计算时间缩短了25%。总之,改进后的GRAPES奇异向量方法,可应用于构建面向业务应用的GRAPES全球集合预报系统。 相似文献
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一个ENSO动力-相似误差订正模式及其后报初检验 总被引：5，自引：1，他引：4
为有效利用历史资料中的相似信息,减小模式误差对ENSO这类跨季节-年际尺度预测问题的影响提高动力模式的预测水平.作者利用一种基于统计相似的模式误差订正方法,以国家气候中心简化海气耦合模式为平台建立了相应的动力-相似误差订正(DAEC)模式,并着重探讨了系统相似程度(全相似或部分相似)、误差重估周期以及相似样本个数等因素对预报效果的影响.结果表明,利用该方法可以有效地改善原有模式的预报性能,其中 "全相似" 比 "部分相似" 更能反映海气耦合系统的相似程度,从而对模式误差做出更为准确的估计,使预报误差明显减小.海洋和大气的误差重估周期对结果也有较大影响,在不同相似程度下分别存在着某种最优配置使得预报效果达到最佳.另外,在对相似样本存在状况及影响的研究中则发现在当前资料长度内整体上只存在着有限个相似样本,在此范围内随着样本取样数目的增加DAEC模式的预报性能逐渐提高. 相似文献
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THE SENSITIVITY INFLUENCE OF NUMERICAL MODEL INITIAL VALUES ON FOUR-DIMENSIONAL ASSIMILATION—STUDY BASED ON LORENZ SYSTEM 下载免费PDF全文
下载免费PDF全文 Numerical experiments of adjoint variational assimilation have been performed using the knownLorenz system.With the increase of sensitivity of model's initial values,it is more and more difficultto use the adjoint method to get the initial values which are consistent with the dynamics of the fore-cast model.Under some circumstances the algorithm completely fails.This shows that four-dimen-sional assimilation is related to the limit of predictability.On the other hand.with the increase ofmodel equation's error,the result of variational assimilation may become worse and worse so that theprediction has no meaning.But if the model parameters are corrected when variational assimilation ismade,the forecast results can be greatly improved based on Lorenz model. 相似文献