Search

Utilizing the Community Atmosphere Model, version 4, the influence of Arctic sea-ice concentration (SIC) on the extended-range prediction of three simulated cold events (CEs) in East Asia is investigated. Numerical results show that the Arctic SIC is crucial for the extended-range prediction of CEs in East Asia. The conditional nonlinear optimal perturbation approach is adopted to identify the optimal Arctic SIC perturbations with the largest influence on CE prediction on the extended-range time scale. It shows that the optimal SIC perturbations are more inclined to weaken the CEs and cause large prediction errors in the fourth pentad, as compared with random SIC perturbations under the same constraint. Further diagnosis reveals that the optimal SIC perturbations first modulate the local temperature through the diabatic process, and then influence the remote temperature by horizontal advection and vertical convection terms. Consequently, the optimal SIC perturbations trigger a warming center in East Asia through the propagation of Rossby wave trains, leading to the largest prediction uncertainty of the CEs in the fourth pentad. These results may provide scientific support for targeted observation of Arctic SIC to improve the extended-range CE prediction skill. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]