条件非线性最优扰动法在大气与海洋目标观测研究中的应用

对近年来用条件非线性最优扰动法研究大气与海洋目标观测问题的部分工作进行了总结，主要涉及厄尔尼诺-南方涛动（ENSO）事件、黑潮路径变异事件以及阻塞事件。通过研究这些事件发生的最优前期征兆（OPR）和最快增长初始误差（OGE），发现这些事件的最优前期征兆和最快增长初始误差分别具有空间的高度相似性及其伴随的局地性特征。理想回报试验表明，如果在ENSO事件和黑潮路径变异事件的最快增长初始误差和最优前期征兆所确定的扰动大值区减小初始场误差，上述事件的预报技巧会大幅度提高；最优前期征兆和最快增长初始误差的空间相似性使得在同一敏感区域增加额外观测，不仅有助于捕捉上述异常事件的前期信号，还可以有效减小初始误差，从而提高对该事件的预报技巧。阻塞事件爆发的最优前期征兆和最快增长初始误差的空间相似性和局地性特征在其目标观测研究中的应用，应该是深入研究的课题。

Application of conditional nonlinear optimal perturbation to targeted observation studies of the atmosphere and ocean

This paper reviews progress in the application of conditional nonlinear optimal perturbation to targeted observation studies of the atmosphere and ocean in recent years, with a focus on the El Niño-Southern Oscillation (ENSO), Kuroshio path variations, and blocking events. Through studying the optimal precursor (OPR) and optimally growing initial error (OGE) of the occurrence of the above events, the similarity and localization features of the OPR and OGE spatial structures have been found for each event. Ideal hindcasting experiments have shown that, if initial errors are reduced in the areas with the largest amplitude for the OPR and OGE for ENSO and the Kuroshio path variations, the forecast skill of the model for these events is significantly improved. Due to the similarity between patterns of the OPR and OGE, additional observations implemented in the same sensitive region would help to not only capture the precursors, but also reduce the initial errors in the predictions, greatly increasing the forecast abilities. The similarity and localization of the spatial structures of the OPR and OGE during the onset of blocking events have also been investigated,but their application to targeted observation requires further study.