Complex Networks Reveal Climate Models' Capability in Simulating Global Synchronized Extreme Precipitation

Spatially synchronized extreme precipitation events are intensifying under anthropogenic warming. Accurate simulation of such compound extremes by global climate models underpins reliable climate projections for spatially compound risk assessment. Using complex network analysis combined with event synchronization, here we evaluate the performance of 11 Coupled Model Intercomparison Project Phase 6 (CMIP6) models in representing global synchronized structures of extreme precipitation during 1981–2014. Compared to state-of-the-art reanalysis data, CMIP6 models effectively capture the scale-dependent behavior of synchronized event pairs, particularly for teleconnections beyond 2,500 km. While the CMIP6 multi-model ensemble mean overestimates short-range (300–2,500 km) synchronization frequency by 5.7%, it well reproduces the overall network topology of global extreme precipitation. However, significant regional biases emerge in monsoon regions, where models systematically underestimate node connectivity by more than 20% during boreal summer, highlighting key areas for model improvement in simulating long-distance synchronized precipitation events.