While sea surface temperature anomalies (SSTAs) are known drivers of terrestrial heat extremes, a unified quantitative understanding of the SSTAs’ impacts across seasons, ocean basins, and lead times remains lacking. Here, we apply a complex network framework to systematically investigate the linkage between extreme terrestrial temperature and SSTAs at a global scale and over four seasons. Based on this data-driven framework, the signal propagation from tropical Pacific, Atlantic and Indian Ocean to terrestrial regions could be assessed quantitatively. Short-lagged influences are observed in the tropical Indian Ocean, while longer-lagged modulations persisting for up to 6 months are observed in the tropical Pacific and Atlantic. Notably, robust teleconnections are detectable over 90% of the land areas even at 12-month lead times, exposing a substantial source of long-term predictability that are overlooked by traditional statistical analysis. Furthermore, multiple climate models demonstrate skillful simulation of these lag-dependent teleconnections, with a clear inter-model relationship showing that greater interannual SSTA variability corresponds to stronger modulations on extreme terrestrial high temperature. This network-based framework provides a novel approach for elucidating ocean-to-land modulations, which deepen our knowledge of the predictability of the climate system.

Complex Network, Sea Surface Temperature Anomalies, Extreme Terrestrial Heat