In the last decade, there has been a growing body of literature addressing the utilization of
complex network methods for the characterization of dynamical systems based on time …

Understanding how climate change will affect oceanic fluid transport is crucial for
environmental applications and human activities. However, a synoptic characterization of …

Global climate models (GCMs) are generally used to forecast weather, understand the
present climate, and project climate change. Their reliability usually rests on their capability …

We explore the mechanisms of heat transfer in a turbulent constant heat flux-driven Rayleigh–
Bénard convection flow, which exhibits a hierarchy of flow structures from granules to …

Transport and mixing processes in fluid flows can be studied directly from Lagrangian
trajectory data, such as those obtained from particle tracking experiments. Recent work in …

Downscaling aims to take large-scale information and map it to smaller scales to reproduce
local climate signals. An essential step in implementing a parsimonious downscaling model …

To identify barriers to transport in a fluid domain, community detection algorithms from
network science have been used to divide the domain into clusters that are sparsely …

Unraveling the relationship between humidity, wind, and rainfall is vitally important to
understand the dynamics of water vapor transport. In recent years, the use of causal …

Mitigating climate change and reducing emissions of greenhouse gases to net-zero by mid-
century is a huge global challenge. The renewable energy transition is one of the key pillars …

Complex networks are widely used to describe the interactions of real systems such as
technological, social and biological systems. Compressed sensing method is one of the …