摘要：This study investigated the impact of different verification-area designs on the sensitive areas identified using the conditional nonlinear optimal perturbation （cnop） method for tropical cyclone targeted *** sensitive areas identified using the first singular vector （FSV） method,which is the linear approximation of cnop,were also investigated for *** analyzing the validity of the sensitive areas,the proper design of a verification area was *** cyclone Rananim,which occurred in August 2004 in the northwest Pacific Ocean,was *** sets of verification areas were designed;one changed position,and the other changed both size and *** cnop and its identified sensitive areas were found to be less sensitive to small variations of the verification areas than those of the FSV and its sensitive *** larger variations of the verification area,the cnop and the FSV as well as their identified sensitive areas changed *** terms of reducing forecast errors in the verification area,the cnop-identified sensitive areas were more beneficial than those identified using *** design of the verification area is important for cyclone *** verification area should be designed with a proper size according to the possible locations of the cyclone obtained from the ensemble forecast *** addition,the development trend of the cyclone analyzed from its dynamic mechanisms was another *** the general position of the verification area was determined,a small variation in size or position had little influence on the results of cnop.

摘要：简要但系统地介绍了条件非线性最优扰动(cnop)方法在台风目标观测方面的研究进展。cnop方法是线性奇异向量(SV)方法在非线性领域的一个拓展。在台风目标观测的研究中,该方法主要用来识别对台风预报有重要影响的敏感区,从而可以在这些敏感区内增加观测,改进初始场以提高预报技巧。首先回顾了cnop方法在台风目标观测中应用的理论基础,接着阐述了cnop识别的敏感区受模式分辨率、验证区域的设计、优化时长的选取等因素的影响,并给出了利用观测系统模拟试验(OSSE)和观测系统试验(OSE)对cnop识别的敏感区有效性检验的结果,进一步评述了将cnop方法应用于实际天气业务预报中进行敏感区识别的可能性,最后对cnop方法在台风目标观测中的深入应用进行了总结和讨论。