Compound Extreme Events Propagation Over China: A Complex Network Analysis

Compared with univariate extreme climate events, such as extreme precipitation, droughts, cold spells, and heat waves, Compound Extreme Events (CEEs) have greater impacts on human activities and economic development. Gaining a deeper insight into the topological structure and evolutionary direction of CEEs is crucial for understanding their potential responses to altered thermodynamics and dynamics in a warming climate. Graph theory-based complex networks can effectively represent the relationships among various elements of complex dynamical systems, such as the atmosphere. They are thus used to analyze the directionality and topological structure of CEEs over a 60-year period across mainland China. Specifically, the CEEs are constructed by the combinations of univariate temperature and precipitation extreme events, with each univariate extreme event identified by fixed percentiles of the daily precipitation and temperature data. Our results reveal important structural and dynamical information about the topology of the CEEs and improve the understanding of the dominant meteorological patterns. The initiation and propagation of CEEs from source to sink zones are discerned, and their topological structure and spatial dynamics are influenced by topography, wind patterns, and moisture sources.