Complex networks as a diagnostic framework for seasonal organization and spatial connectivity in the Arctic atmosphere.

Understanding how Arctic climate variability is organized internally and how it connects to large-scale atmospheric variability remains a challenge. Approaches based on indices or dominant modes are well-suited to identifying coherent patterns but offer limited insight into localized connectivity, pathway structure, and the timing of interactions across regions.  Here, we apply a climate network approach to examine the seasonal organization of Arctic atmospheric connectivity using mid-tropospheric circulation (500 hPa geopotential height, Z500) and near-surface air temperature (T2M) over 1940–2024. The analysis focuses on winter (DJF) and summer (JJA), and examines both instantaneous and time-lagged relationships in the free atmosphere and at the surface.  We find a pronounced seasonal dependence in Arctic connectivity. Within the Arctic, Z500 networks exhibit strong and spatially extensive connectivity in winter, consistent with basin-scale coherence in the mid-tropospheric circulation. In summer, this structure weakens and becomes more fragmented. In both seasons, betweenness centrality is broadly distributed, suggesting that Arctic circulation variability is not dominated by a small number of preferred internal pathways. In contrast, T2M networks are more heterogeneous, with spatially uneven connectivity and localized regions of higher importance, highlighting the role of surface conditions in shaping near-surface variability.  When only the strongest links (99th percentile threshold) are considered, direct Arctic large-scale connectivity is weak in both Z500 and T2M. However, time-lagged analysis shows that connectivity can emerge on delayed timescales, particularly in winter, and is more clearly expressed in the circulation field (Z500) than at the surface (T2M). Overall, this study presents a network-based diagnostic perspective on Arctic atmospheric variability, highlighting the seasonal organization and spatial connectivity that complement traditional mode-based analyses.