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Climate change by its very nature epitomizes the necessity and usefulness of the global-to-local-to-global (GLG) paradigm. It is a global problem with the potential to affect local communities and ecosystems. Accumulation of local impacts and responses to climate change feeds back to regional and global systems creating feedback loops. Understanding these complex impacts and interactions is key to developing more resilient adaptation measures and designing more efficient mitigation policies. To this date, however, GLG interactions have not yet been an integrative part of the decision-support toolkit. The typical approach either traces the impacts of global action on the local level or estimates the implications of local policies at the global scale. The first approach misses cumulative feedback of local responses that can have regional, national or global impacts. In the second case, one undermines a global context of the local actions most likely misrepresenting the complexity of the local decision-making process. Potential interactions across scales are further complicated by the presence of cascading impacts, connected risks and tipping points. Capturing these dimensions is not always a straightforward task and often requires a departure from conventional modeling approaches. In this paper, we review the state-of-the-art approaches to modeling GLG interactions in the context of climate change. We further identify key limitations that drive the lack of GLG coupling cases and discuss what could be done to address these challenges.