Our most powerful constraints on the climate system are developed through combining observational data with models and theory. Together these tools allow us to test hypotheses, quantify the limits of knowledge, develop the next generation of models and data retrievals, and ultimately advance the foundational principles that underpin our understanding of the climate system. This session will feature intersections among these approaches in advancing paleoclimatology. Highlighted topics include developments in relating environmental variables to paleoclimate proxies, techniques for combining numerical models and data (including data assimilation and machine learning methods), and integration of idealized models and model hierarchies. We invite submissions related to the design and incorporation of new proxy system models, reconstructions of past ecosystems and climates, uncertainty quantification, and data-model intercomparison to address key paleoclimate questions. These questions may include but are not limited to characterizing climate variability, large-scale dynamics, and extremes, and assessing climate sensitivity.