Influence of Arctic Sea-ice Concentration on Extended-range Forecasting of Cold Events in East Asia

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.