Dominant time scales of tropical–extratropical coupling in atmospheric rivers over the Southern Ocean and coastal Antarctica

Atmospheric rivers (ARs) are increasingly recognized as key contributors to moisture and heat transport into Antarctica, yet their dominant time scales of variability and links to large-scale climate modes remain insufficiently quantified. We analyze sector-resolved AR frequency and integrated vapor transport around the Antarctic margin using band-pass filtering and canonical correlation analysis applied to reanalysis-based circulation and thermodynamic fields. The results show a pronounced scale dependence of AR variability, with weak and spatially incoherent signals at interannual (6–18-month) time scales, but robust and hemispherically organized patterns at multiyear (36–72-month) periods.

At these longer time scales, AR activity is strongly coupled to tropical–extratropical modes, in particular ENSO, the Indian Ocean Dipole, and the Southern Annular Mode, through their modulation of storm-track intensity, subtropical jet position, and meridional moisture transport. The strongest canonical responses occur in the Weddell Sea and Atlantic–Indian sectors, characterized by negative sea-level pressure anomalies, enhanced westerlies, and intensified poleward integrated vapor transport. In contrast, the East Antarctic and Ross–Bellingshausen sectors exhibit weaker and more localized circulation anomalies, indicating a strong modulation by regional geometry and background flow.

The associated wind and pressure patterns reveal preferred pathways for AR intrusions, involving strengthened midlatitude westerlies, anticyclonic anomalies over the Amundsen–Bellingshausen Seas, and shifts in the subtropical jet that facilitate tropical–polar moisture exchange. These results demonstrate that Antarctic ARs are organized by large-scale tropical–extratropical coupling acting predominantly at multiyear time scales, with pronounced sectoral contrasts. Such scale-dependent behavior has important implications for understanding and predicting variability in Antarctic precipitation, surface temperature, and surface mass balance.