This theme connects critical phenomena, percolation theory, and climate-network methods, highlighting representative work on atmospheric-river criticality, universal gap scaling, and the changing tropical climate-network component under global warming.
The climate system is not a collection of isolated local processes. It is shaped by multiscale interactions, long-range connections, and transitions that can resemble critical behavior in complex systems.
This research theme asks how tools from statistical physics and network science can reveal organizing principles in climate dynamics: What signals appear near critical transitions? How do climate-network structures change under external forcing? Can atmospheric rivers be interpreted through the lens of self-organized criticality?
Self-Organized Criticality in Atmospheric Rivers studies atmospheric-river events from a statistical-physics perspective and identifies critical-dynamics features in these key water-vapor transport structures.
Universal gap scaling in percolation investigates the statistics of the largest jump gaps during percolation transitions and develops a universal scaling picture for complex-system phase transitions.
Climate network percolation reveals the expansion and weakening of the tropical component under global warming applies percolation ideas to climate networks and reveals the poleward expansion of the largest tropical component, weakening link strength, and connections to the expansion and weakening of the Hadley circulation.
Together, these studies show how methods from statistical physics can be translated into Earth-system science, turning complex climate fields into interpretable structures, transitions, and risk-relevant signals.