动力相似预报的策略和方法
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摘要
本文基于对数值天气预报和短期气候预测研究的全面回顾,指出发展预报策略和方法研究是除了改善资料和改进模式之外提高预报水平的重要途径,并强调动力预报中对历史相似信息的利用在实现统计-动力有机结合方面的重要价值。为此,本文在前人研究基础上,紧紧围绕“动力相似预报”这一新框架,沿着“如何在动力预报中有效地运用相似性信息”这一研究主线,在数值预报订正、集合预报、模式后处理技术以及可预报性研究等方面,全面引入相似的观点,提出了创新性的策略和方法,并进行理论分析和数值试验,得到了令人鼓舞的结果,从而证实其具有广泛的研究和应用前景。主要结果和结论如下:
(1) 从物理上深入研究了“相似预报——频流型——可预报性”关系,数值试验和诊断分析都证实理论模型和实际大气不同尺度的动力预报结果及其误差行为具有相似性,通过比较和探讨统计和动力相似预报的差别,归纳并提出了三类相似性问题和动力相似预报的物理基础,进而提出动力预报的相似性原理。
(2) 提出了利用历史资料中相似信息估计模式误差的反问题和对预报误差进行预报的新思路;依据动力预报的相似性原理,提出和发展了一种统计动力相结合的相似误差订正方法,可针对当前预报特殊性来区分所利用过去资料的特殊性。找到了动力相似预报方程相对于相似离差方程和相似误差订正方程的理论优势所在。提出了误差订正间隔和相似更新周期的新概念。
(3) Lorenz模式的全局预报试验表明,相似更新周期、误差订正间隔和观测样本间隔都对相似误差订正影响很大;相似个数、系统性和随机观测误差也会产生明显影响;误差的简单线性估计算法可很好地代替超平面近似法应用于实际。进一步发展了“重启”的误差诊断新方案。T63模式预报试验显示了不错的改进效果。海温相似性问题可以影响到上述方法的实际预报效果。
(4) 针对初始相似的有限持续性问题,并考虑在动力预报中引入多个历史相似信息,提出了基于多个参考态更新的动力相似预报新方法。该方法既可将相似-动力模式或者相似误差订正法分别作为动力预报核,又能在最小二乘意义下将不同参考态的预报结果重新估计出最佳预报向量。利用Lorenz模式和T63模式进行数值试验表明,预报技巧得到明显提高。
(5) 按照相似误差订正思路发展了一种模式误差参数化方案,并基于这一方案发展了相似-动力集合预报的新方法,提出将多个动力相似预报的结果由简单算术平均发展为考虑相似性差异的加权集合,以及引入相似更新理念的过程集合新思路。将新的集合方法应用到相似-动力延伸预报中,初步发展了一个相似-动力集合预报试验性系统,实时准业务月预报试验显示出令人鼓舞的结果。
(6) 深入探讨了事后相似误差订正方法在月、季短期气候预测中应用的理论问题和误差估计方法,证实了这一尺度上由历史相似预报误差重新估计当前预报误差的可行性。以一个可预报性研究验证了该方法的应用潜力,月平均环流和夏
Based on a comprehensive review for numerical weather prediction and short-term climate prediction, it is pointed out in the present dissertation that the development of prediction strategy and methodology is an important approach to increase prediction performance besides improving observation and developing model. It is further emphasized the important values in the effective combination of statistical and dynamical methods by utilizing historical analogue information in dynamical prediction. So, on the basis of previous researches, some innovative strategies and methods, which are associated with numerical forecast correction, ensemble forecast, model post-processing technique, and predictability, et al., are put forward under the new framework of dynamical analogue prediction (DAP) by introducing analogy idea. Many exciting results related theoretical analyses and numerical experiments are achieved, which indicate the wide perspective of studies and applications on these strategies and methods. The major conclusions of this study may be summarized as follow:(1) The relationship of "analogue prediction—low-frequency flow regimes (LFFRs)—predictability" is physically examined. Both numerical experiments and diagnostic analyses show that the behaviors of forecast and its error are characterized by analogy both in theoretical and real atmospheric model at different timescale. By comparing statistical and dynamical analogue prediction, three classes of analogy problems and the physical basis of DAP are first raised, and the analogy principle of dynamical prediction are put forward.(2) The inverse problem that information of historical analogue data is utilized to estimate model errors, and the new idea on prediction of prediction errors, are raised. Based on the analogy principle of dynamical prediction, an analogue correction method of errors (ACE) is put forward and developed, which can identify specific historical data for the solution of the inverse problem in terms of the particularity of current prediction. Furthermore, the theoretical superiority of DAP equation to either analogue deviation equation or analogue correction equation of errors is found out. The new concepts such as period of analogue updating (PAU) and interval of correcting errors (ICE) are also raised.(3) Global forecasting experiments on Lorenz model show that, PAU, ICE, and interval of observation samples have significant impact on analogue correction of errors, as well as analogue number, systematical and random observation errors. It is found that the simple linear estimation method can well replace the hyperplane approximation method in actual application of ACE. Forecasting experiments on T63 model exhibit evident improvement of prediction skill and a new errors diagnosis procedure by rerunning is developed. Actual predictive efficiency may be influenced by the analogy problem of sea surface temperature.(4) Focused on finite persistence of initial analogue, a new method of DAP based on multi-reference-state updating is put forward by introducing information of multi historical analogues. In this method, not only analogue-dynamical model and ACE may be regarded as dynamical prediction kernel, but also the optimal forecast vector
can be estimated from those forecasts based on different reference states. The considerable predictive skill is shown both in the experiment results of Lorenz model and T63 model.(5) On the basis of analogue correction of errors, a model error parameterization (MEP) is developed, and a new method of analogue-dynamical ensemble forecast (ADEF) is further raised by employing MEP. The new technique associating with weighted ensemble which is developed from simple arithmetical mean of multi results of DAP, and in-process ensemble by introducing analogue updating, is also put forward. An ADEF experimental system by applying this new ensemble method to analogue-dynamical extended-range forecasting is primarily established and developed, by which experiments of real-time quasi-operational monthly forecast show exciting results.(6) The theoretical problems and errors estimate methods on which the final ACE is applied to monthly and seasonal short-term climate prediction are deep discussed, which documents the feasibility of estimating current forecast errors from historical forecast errors based on analogues. The potential capability of final ACE applied to actual prediction is successful validated in a predictability study and it is shown that this post-processing method has the well performance of improving predictive skill and reproducing prediction variance in the forecast experiments of both monthly mean circulation and summer circulation and rainfall.(7) Some key problems in selecting analogues such as defining analogue indices, selecting analogue variables, determining analogue metric and analogue region range, et al., are deep examined. A two-level method for selecting analogue and an integrated analogue index are raised in ocean-atmospheric system, and related problems of evolution analogue and tendency analogue are discussed, and a spectrum-coefficient-based analogue index is developed. The impacts of analogue metric on prediction with different timescales and the influences of spatial degree of freedom on selecting analogue and predicting problem are discussed, respectively. It is also found that there exists a significant relationship of anti-correlation between analogue quality and predictive skill on analogue correction of errors.(8) The EOF dataset with a few degrees of freedom is primarily established. In order to investigate the close linkage among analogue prediction, the LFFRs and predictability, the classification studies of summer LFFRs in northern hemispheric extratropics are performed, as well as the large-scale low-frequency rainfall regimes in summertime over China which is the important component of LFFRs. All these theoretical and diagnostic studies are helpful to improve the relative process of selecting analogue.
(1) 从物理上深入研究了“相似预报——频流型——可预报性”关系,数值试验和诊断分析都证实理论模型和实际大气不同尺度的动力预报结果及其误差行为具有相似性,通过比较和探讨统计和动力相似预报的差别,归纳并提出了三类相似性问题和动力相似预报的物理基础,进而提出动力预报的相似性原理。
(2) 提出了利用历史资料中相似信息估计模式误差的反问题和对预报误差进行预报的新思路;依据动力预报的相似性原理,提出和发展了一种统计动力相结合的相似误差订正方法,可针对当前预报特殊性来区分所利用过去资料的特殊性。找到了动力相似预报方程相对于相似离差方程和相似误差订正方程的理论优势所在。提出了误差订正间隔和相似更新周期的新概念。
(3) Lorenz模式的全局预报试验表明,相似更新周期、误差订正间隔和观测样本间隔都对相似误差订正影响很大;相似个数、系统性和随机观测误差也会产生明显影响;误差的简单线性估计算法可很好地代替超平面近似法应用于实际。进一步发展了“重启”的误差诊断新方案。T63模式预报试验显示了不错的改进效果。海温相似性问题可以影响到上述方法的实际预报效果。
(4) 针对初始相似的有限持续性问题,并考虑在动力预报中引入多个历史相似信息,提出了基于多个参考态更新的动力相似预报新方法。该方法既可将相似-动力模式或者相似误差订正法分别作为动力预报核,又能在最小二乘意义下将不同参考态的预报结果重新估计出最佳预报向量。利用Lorenz模式和T63模式进行数值试验表明,预报技巧得到明显提高。
(5) 按照相似误差订正思路发展了一种模式误差参数化方案,并基于这一方案发展了相似-动力集合预报的新方法,提出将多个动力相似预报的结果由简单算术平均发展为考虑相似性差异的加权集合,以及引入相似更新理念的过程集合新思路。将新的集合方法应用到相似-动力延伸预报中,初步发展了一个相似-动力集合预报试验性系统,实时准业务月预报试验显示出令人鼓舞的结果。
(6) 深入探讨了事后相似误差订正方法在月、季短期气候预测中应用的理论问题和误差估计方法,证实了这一尺度上由历史相似预报误差重新估计当前预报误差的可行性。以一个可预报性研究验证了该方法的应用潜力,月平均环流和夏
Based on a comprehensive review for numerical weather prediction and short-term climate prediction, it is pointed out in the present dissertation that the development of prediction strategy and methodology is an important approach to increase prediction performance besides improving observation and developing model. It is further emphasized the important values in the effective combination of statistical and dynamical methods by utilizing historical analogue information in dynamical prediction. So, on the basis of previous researches, some innovative strategies and methods, which are associated with numerical forecast correction, ensemble forecast, model post-processing technique, and predictability, et al., are put forward under the new framework of dynamical analogue prediction (DAP) by introducing analogy idea. Many exciting results related theoretical analyses and numerical experiments are achieved, which indicate the wide perspective of studies and applications on these strategies and methods. The major conclusions of this study may be summarized as follow:(1) The relationship of "analogue prediction—low-frequency flow regimes (LFFRs)—predictability" is physically examined. Both numerical experiments and diagnostic analyses show that the behaviors of forecast and its error are characterized by analogy both in theoretical and real atmospheric model at different timescale. By comparing statistical and dynamical analogue prediction, three classes of analogy problems and the physical basis of DAP are first raised, and the analogy principle of dynamical prediction are put forward.(2) The inverse problem that information of historical analogue data is utilized to estimate model errors, and the new idea on prediction of prediction errors, are raised. Based on the analogy principle of dynamical prediction, an analogue correction method of errors (ACE) is put forward and developed, which can identify specific historical data for the solution of the inverse problem in terms of the particularity of current prediction. Furthermore, the theoretical superiority of DAP equation to either analogue deviation equation or analogue correction equation of errors is found out. The new concepts such as period of analogue updating (PAU) and interval of correcting errors (ICE) are also raised.(3) Global forecasting experiments on Lorenz model show that, PAU, ICE, and interval of observation samples have significant impact on analogue correction of errors, as well as analogue number, systematical and random observation errors. It is found that the simple linear estimation method can well replace the hyperplane approximation method in actual application of ACE. Forecasting experiments on T63 model exhibit evident improvement of prediction skill and a new errors diagnosis procedure by rerunning is developed. Actual predictive efficiency may be influenced by the analogy problem of sea surface temperature.(4) Focused on finite persistence of initial analogue, a new method of DAP based on multi-reference-state updating is put forward by introducing information of multi historical analogues. In this method, not only analogue-dynamical model and ACE may be regarded as dynamical prediction kernel, but also the optimal forecast vector
can be estimated from those forecasts based on different reference states. The considerable predictive skill is shown both in the experiment results of Lorenz model and T63 model.(5) On the basis of analogue correction of errors, a model error parameterization (MEP) is developed, and a new method of analogue-dynamical ensemble forecast (ADEF) is further raised by employing MEP. The new technique associating with weighted ensemble which is developed from simple arithmetical mean of multi results of DAP, and in-process ensemble by introducing analogue updating, is also put forward. An ADEF experimental system by applying this new ensemble method to analogue-dynamical extended-range forecasting is primarily established and developed, by which experiments of real-time quasi-operational monthly forecast show exciting results.(6) The theoretical problems and errors estimate methods on which the final ACE is applied to monthly and seasonal short-term climate prediction are deep discussed, which documents the feasibility of estimating current forecast errors from historical forecast errors based on analogues. The potential capability of final ACE applied to actual prediction is successful validated in a predictability study and it is shown that this post-processing method has the well performance of improving predictive skill and reproducing prediction variance in the forecast experiments of both monthly mean circulation and summer circulation and rainfall.(7) Some key problems in selecting analogues such as defining analogue indices, selecting analogue variables, determining analogue metric and analogue region range, et al., are deep examined. A two-level method for selecting analogue and an integrated analogue index are raised in ocean-atmospheric system, and related problems of evolution analogue and tendency analogue are discussed, and a spectrum-coefficient-based analogue index is developed. The impacts of analogue metric on prediction with different timescales and the influences of spatial degree of freedom on selecting analogue and predicting problem are discussed, respectively. It is also found that there exists a significant relationship of anti-correlation between analogue quality and predictive skill on analogue correction of errors.(8) The EOF dataset with a few degrees of freedom is primarily established. In order to investigate the close linkage among analogue prediction, the LFFRs and predictability, the classification studies of summer LFFRs in northern hemispheric extratropics are performed, as well as the large-scale low-frequency rainfall regimes in summertime over China which is the important component of LFFRs. All these theoretical and diagnostic studies are helpful to improve the relative process of selecting analogue.
引文
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