Abstract
Understanding the mechanics of climate changes on time and space scales is a difficult undertaking. According to the current literature on the subject, this endeavour is unfeasible in the near future, yet it is critical for forecasting both short-term weather and long-term climate change. Many problems impede the study of earth climate data, including non-stationarity (e.g., abrupt vs. slow variations), chaotic dynamics, non-linear dynamics, high-dimensionality, and natural vs. anthropogenic effects. The analytical approaches of descriptive and inferential statistics could benefit from network analysis techniques for investigating a complicated system like the climate. This study suggests an analysis that could help much more complex and refined, and ultimately enormously more informative, analyses could be based on an calculation of the centrality measures of an imaginary graph connecting the different continents and climatic zones of the Earth.