Application of Conditional Nonlinear Optimal Perturbation to Targeted Observation Studies of the Atm

来源 :Journal of Meteorological Research | 被引量 : 0次 | 上传用户:wangyabing
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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 Nino-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 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 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. 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 Nino-Southern Oscillation (ENSO), Kuroshio path variations, and blocking events. Studying the optimal precursor (OPR) and optimally growing initial error (OGE) of the occurrence of the above events, the similarity and localization features of 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 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 forecas t 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.
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