  Global climate warming poses a significant challenge to humanity; it is
associated with, e.g., rising sea level and declining Arctic sea ice.
Increasing extreme events are also considered to be a result of climate
warming~\cite{pachauri2014climate,ogorman_contrasting_2014} and they may have
widespread and diverse effects on health, agriculture, economics and political
conflicts
\cite{hsiang2011civil,helbing_globally_2013,schleussner_armed-conflict_2016,carleton_social_2016}.
Still, the detection and quantification of climate change, both in observations
and climate models, constitute a main focus of the scientific community. Here
we develop a new approach based on network and percolation frameworks
\cite{cohen2010complex} to study the impacts of climate changes in the past
decades using historical models and reanalysis records, and we analyze the
expected upcoming impacts using various future global warming scenarios. More
specifically, we classify the globe area into evolving percolation clusters and
find a discontinuous phase transition, which indicates a consistent poleward
expansion of the largest (tropical) cluster, as well as the weakening of the
link's strength. This is found both in the reanalysis data and in the Coupled
Model Intercomparison Project Phase 5 (CMIP5) twenty-first century climate
change simulations~\cite{taylor2012overview}. The analysis is based on high
resolution surface (2~m) air temperature field records. We discuss the
underlying mechanism for the observed expansion of the tropical cluster and
associate it with changes in atmospheric circulation represented by the
weakening and expansion of the Hadley cell. Our framework can also be useful
for forecasting the extent of the tropical cluster in order to detect its
influence on different areas in response to global warming.
