在动力相似预报中引入多个参考态的更新

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。

INTRODUCING THE UPDATING OF MULTI-REFERENCE STATES INTO DYNAMICAL ANALOGUE PREDICTION

In order to effectively utilize the analogue information of historical observations,some theoretical and technical problems of the analogue correction of errors(ACE) are further explored in this paper based on the previous studies on analogue-dynamical models.Analyses show that the ACE is the redevelopment of methods based on the analogue-deviation equation and analogue-correction equation of errors.On the basis of such idea,a new scheme of dynamical analogue prediction allowing for multi-reference-state updating(MRSU) has been developed.In this scheme,when model integration proceeds to the period of analogue updating(PAU), multiple reference states are re-selected and optimal forecast vectors are estimated from multi-forecasts produced by the analogue-dynamical model using the hyperplane approximation method.Such a "selection-estimation" procedure is periodically repeated until the entire forecast is completed.The MRSU experiments of Lorenz model have shown that the MRSU is effective in reducing forecast errors and raising forecast skill,thus preliminarily confirming the application prospect of ACE theory.Furthermore,in the conceptual flow chart of the MRSU,introducing the ACE into the complicated numerical model is equivalent to realize the forecast process of analogue-dynamical model without necessity to re-establish the model equation.