王斌,谭晓伟. 2009. 一种求解条件非线性最优扰动的快速算法及其在台风目标观测中的初步检验[J]. 气象学报, 67(2):175-188, doi:10.11676/qxxb2009.018
一种求解条件非线性最优扰动的快速算法及其在台风目标观测中的初步检验
A fast algorithm to obtain CNOP and its preliminary tests in a target observation experiment of typhoon.
投稿时间:2008-10-17  修订日期:2009-01-08
DOI:10.11676/qxxb2009.018
中文关键词:  快速算法,条件非线性最优扰动,目标观测,观测系统模拟实验
英文关键词:Fast algorithm, CNOP, Target observation, OSSE
基金项目:国家973项目(2004CB418304)和公益性行业(气象)科研专项(GYHY(QX)2007-6-15)
作者单位
王斌 中国科学院大气物理研究所LASG北京100029 
谭晓伟 中国科学院大气物理研究所LASG北京100029 
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中文摘要:
      条件非线性最优扰动(CNOP)是Mu等2003年提出的一个新的理论方法,它是线性奇异向量在非线性情形的推广,克服了线性奇异向量不能代表非线性系统最快发展扰动的缺陷,成为非线性系统可预报性和敏感性等研究新的有效工具。然而,由于以往CNOP的求解需要采用伴随技术,计算量相当巨大,限制了该方法的推广应用。为了克服这一困难,本文基于经验正交分解(EOF),提出了一种求解CNOP的快速算法,利用GRAPES区域业务预报模式实现了CNOP快速计算,并在台风“麦莎”的目标观测研究中得到初步检验,通过观测系统模拟实验(OSSE)检验了该方法确定敏感性区域(瞄准区)的有效性和可行性。试验结果表明,用快速算法求解的CNOP,其净能量随时间快速地发展,而且发展呈非线性。在台风“麦莎”个例的目标观测试验中,用快速算法得到的预报时间为24 h的CNOP可以有效地识别瞄准区,并通过瞄准区内初值的改善,可明显减少目标区域(检验区)内24 h累计降水预报误差。尤其,累计降水预报的这种改进效果能够延伸到更长时间(如72 h),尽管检验时间是设在第24 小时。进一步分析发现,24 h累计降水预报误差的减少是通过利用瞄准区内改善的初值改进初始时刻台风暖心结构、高空相对涡度以及水汽条件等而得以实现的。
英文摘要:
      The conditional nonlinear optimal perturbation (CNOP) is a new theoretical method proposed by Mu,et al in 2003, which is an extension of the linear singular vector (LSV) to nonlinear regimes. It has become a powerful tool to study some issues of nonlinear systems like predictability, sensitivity and so on, because it overcomes the defect of LSV for not representing the fastest developing perturbation of a nonlinear system. However, the wide application of this method has been limited due to its large computational cost caused by the use of adjoint technique in its solution. In order to greatly reduce the computational cost of the solution to CNOP, we propose a fast algorithm for it based on empirical orthogonal function (EOF). The algorithm is preliminarily tested in a target observation experiment of the typhoon “Matsa” using the Global and Regional Assimilation Prediction System (GRAPES), a regional operational forecast model. The effectivity and feasibility of the algorithm to determine the sensitive (targeting) area in target observation is evaluated through an observing system simulation experiment (OSSE). The results from the OSSE show that the energy of the CNOP obtained by the new algorithm develops quickly and nonlinearly. In the experiment of target observation of the typhoon “Matsa”, the sensitivity area is effectively identified using the CNOP obtained from the new method with 24 hours as the prediction time length, and the 24 h accumulated rainfall prediction errors in the verification area are reduced significantly comparing with the “true states” when the initial conditions in the sensitivity area are replaced by the “observations”. Especially, the decrease of accumulated rainfall prediction errors can be extended to longer time (e.g. 72 hour), although the verification is just at the time 24 hours after the initial time. Further analyses reveal that the decrease of 24 h accumulated rainfall prediction errors in the verification area benefits from the improvements of initial structure of warm core of typhoon, upper-layer relative vorticity, water vapor conditions and so on due to the update of the initial conditions in the sensitivity area.
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