| Summary: | It is traditionally considered that the predictability of atmosphere reaches approximately 2 weeks due to its chaotic features. Considering boundary conditions, the lead prediction time can exceed 2 weeks in certain cases. We find that the Arctic sea ice concentration (SIC) is crucial for extended-range prediction of strong and long-lasting Ural blocking (UB) formation. By applying the rotated empirical orthogonal function-based particle swarm optimization algorithm, the conditional nonlinear optimal perturbation is calculated with the Community Atmosphere Model, version 4, to identify the optimally growing boundary errors in extended-range prediction of strong and long-lasting UB formation. It is found that SIC perturbations in the Greenland Sea (GS), Barents Sea (BS), and Okhotsk Sea (OKS) are important for strong and long-lasting UB formation prediction in four pentads. Further analysis reveals that the SIC perturbations in these areas first influence the local temperature field through the diabatic heating process and further affect the temperature field in the Ural sector mainly by advection and convection processes. Moreover, the zonal winds in the Ural sector are adjusted by the thermal wind balance, thus affecting UB formation. The local characteristics of the SIC perturbations indicate that the GS, BS, and OKS may be sensitive areas in regard to extended-range prediction of strong and long-lasting UB formation, which can provide scientific support for the SIC target observations in the future.
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