In this study, the initial perturbations that are the easiest to trigger the Kuroshio Extension （KE） transition connecting a basic weak jet state and a strong, fairly stable meandering state, are investigated using ...In this study, the initial perturbations that are the easiest to trigger the Kuroshio Extension （KE） transition connecting a basic weak jet state and a strong, fairly stable meandering state, are investigated using a reduced-gravity shallow water ocean model and the CNOP （Conditional Nonlinear Optimal Perturbation） approach. This kind of initial perturbation is called an optimal precursor （OPR）. The spatial structures and evolutionary processes of the OPRs are analyzed in detail. The results show that most of the OPRs are in the form of negative sea surface height （SSH） anomalies mainly located in a narrow band region south of the KE jet, in basic agreement with altimetric observations. These negative SSH anomalies reduce the merid- ional SSH gradient within the KE, thus weakening the strength of the jet. The KE jet then becomes more convoluted, with a high-frequency and large-amplitude variability corresponding to a high eddy kinetic energy level; this gradually strengthens the KE jet through an inverse energy cascade. Eventually, the KE reaches a high-energy state characterized by two well defined and fairly stable anticyclonic meanders. Moreover, sensitivity experiments indicate that the spatial structures of the OPRs are not sensitive to the model parameters and to the optimization times used in the analysis.展开更多
The influence of Arctic sea ice concentration (SIC) on the subseasonal prediction of the North Atlantic Oscillation (NAO) event is investigated by utilizing the Community Atmospheric Model version 4. The optimal Arcti...The influence of Arctic sea ice concentration (SIC) on the subseasonal prediction of the North Atlantic Oscillation (NAO) event is investigated by utilizing the Community Atmospheric Model version 4. The optimal Arctic SIC perturbations which exert the greatest influence on the onset of an NAO event from a lead of three pentads (15 days) are obtained with a conditional nonlinear optimal perturbation approach. Numerical results show that there are two types of optimal Arctic SIC perturbations for each NAO event, with one weakening event (marked as type-1) and another strengthening event (marked as type-2). For positive NAO events, type-1 optimal SIC perturbations mainly show positive SIC anomalies in the Greenland, Barents, and Okhotsk Seas, while type-2 perturbations mainly feature negative SIC anomalies in these regions. For negative NAO events, the optimal SIC perturbations have almost opposite patterns to those in positive events, although there are some differences among these SIC perturbations due to different atmospheric initial conditions. Further diagnosis reveals that the optimal Arctic SIC perturbations first modify the surface turbulent heat flux and the temperature in the lower troposphere via diabatic processes. Afterward, the temperature in the low troposphere is mainly affected by dynamic advection. Finally, potential vorticity advection plays a crucial role in the 500-hPa geopotential height prediction in the northern North Atlantic sector during pentad 4, which influences NAO event prediction. These results highlight the importance of Arctic SIC on NAO event prediction and the spatial characteristics of the SIC perturbations may provide scientific support for target observations of SIC in improving NAO subseasonal predictions.展开更多
基金supported by the National Natural Science Foundation of China (Grant Nos. 41576015, 41306023, 41490644 and 41490640)the Natural Science Foundation Of China (NSFC) Innovative Group (Grant No. 41421005)+1 种基金the NSFC–Shandong Joint Fund for Marine Science Research Centers (Grant No. U1406401)support from the University of Naples Parthenope (Grant No. DSTE315)
文摘In this study, the initial perturbations that are the easiest to trigger the Kuroshio Extension （KE） transition connecting a basic weak jet state and a strong, fairly stable meandering state, are investigated using a reduced-gravity shallow water ocean model and the CNOP （Conditional Nonlinear Optimal Perturbation） approach. This kind of initial perturbation is called an optimal precursor （OPR）. The spatial structures and evolutionary processes of the OPRs are analyzed in detail. The results show that most of the OPRs are in the form of negative sea surface height （SSH） anomalies mainly located in a narrow band region south of the KE jet, in basic agreement with altimetric observations. These negative SSH anomalies reduce the merid- ional SSH gradient within the KE, thus weakening the strength of the jet. The KE jet then becomes more convoluted, with a high-frequency and large-amplitude variability corresponding to a high eddy kinetic energy level; this gradually strengthens the KE jet through an inverse energy cascade. Eventually, the KE reaches a high-energy state characterized by two well defined and fairly stable anticyclonic meanders. Moreover, sensitivity experiments indicate that the spatial structures of the OPRs are not sensitive to the model parameters and to the optimization times used in the analysis.
基金the National Natural Science Foundation of China(Grant Nos.42288101,41790475,42005046,and 41775001).
文摘The influence of Arctic sea ice concentration (SIC) on the subseasonal prediction of the North Atlantic Oscillation (NAO) event is investigated by utilizing the Community Atmospheric Model version 4. The optimal Arctic SIC perturbations which exert the greatest influence on the onset of an NAO event from a lead of three pentads (15 days) are obtained with a conditional nonlinear optimal perturbation approach. Numerical results show that there are two types of optimal Arctic SIC perturbations for each NAO event, with one weakening event (marked as type-1) and another strengthening event (marked as type-2). For positive NAO events, type-1 optimal SIC perturbations mainly show positive SIC anomalies in the Greenland, Barents, and Okhotsk Seas, while type-2 perturbations mainly feature negative SIC anomalies in these regions. For negative NAO events, the optimal SIC perturbations have almost opposite patterns to those in positive events, although there are some differences among these SIC perturbations due to different atmospheric initial conditions. Further diagnosis reveals that the optimal Arctic SIC perturbations first modify the surface turbulent heat flux and the temperature in the lower troposphere via diabatic processes. Afterward, the temperature in the low troposphere is mainly affected by dynamic advection. Finally, potential vorticity advection plays a crucial role in the 500-hPa geopotential height prediction in the northern North Atlantic sector during pentad 4, which influences NAO event prediction. These results highlight the importance of Arctic SIC on NAO event prediction and the spatial characteristics of the SIC perturbations may provide scientific support for target observations of SIC in improving NAO subseasonal predictions.
