Spatiotemporal analysis of extreme precipitation and sea surface temperature events in the northern hemisphere via complex network theory

Abstract

Climate variables can be synchronized across broad spatial and temporal scales, with regional, continental, and global patterns. Investigating the topological patterns and underlying mechanisms of extreme precipitation and sea surface temperature events (EPEs and ESSTEs) is crucial to forecast weather conditions and understand the impacts of climate change on natural hazards, such as floods and hurricanes. In the study, we propose integrative spatiotemporal analysis of inland EPEs and ESSTEs to better understand our dynamic atmosphere in the face of global climate change. More specifically, we focus on the region between 0 and 60 degrees latitude in the northern hemisphere. We collected gridded gauge-and-interpolation-based monthly precipitation and temperature data from 1930 to 2020 and detected extreme events based on the 95th percentile threshold. To quantify synchronization between extreme events, we used the event synchronization (ES) method and applied a null model distribution to ensure that links were non-random. We then constructed EPEs and ESSTEs complex networks and calculated different network metrics including degree centrality, mean geographic distance and clustering coefficient. Results showed that the frequency of extreme precipitation and sea surface temperature events increased over the past nine decades, with significant spatial variability. Key synchronization hubs emerged in Mexico, the African Sahel, and parts of Asia for precipitation, while extreme SST events were concentrated in regions influenced by major ocean currents, highlighting distinct spatial patterns for terrestrial and marine extremes.