As the number of palaeoclimate data from glacial, marine, and continental archives is growing continuously, large-scale compilation and cross-comparison of these data is the imperative next phase in paleoclimate research. Large data sets require meticulous database management and new analysis methodologies to unlock their potential for revealing supra-regional and global trends in palaeoclimate conditions. The compilation of large scale datasets from proxy archives faces challenges related to record quality and data stewardship. This requires record screening and formulation of principles for quality check, as well as transparent communication.

This session aims to bring together contributions from paleoclimatic studies benefiting from the existence of such large data sets, e.g., providing a novel perspective on a proxy and the represented climate variables from the local to the global scale. We want to bridge the gap between data generation and modelling studies. In particular, comparing such large proxy-based datasets with climate modelling data is crucial for improving our understanding of palaeoclimate archives (e.g., bias effects and internal processes), to identify signal and noise components and their temporal dynamics, and to gain insight into the quality of model data comparisons.

We encourage submissions on data compilations, cross-comparison and modelling studies utilizing data repositories and databases (e.g., SISAL, PAGES2k, ACER, EPD), including, but not limited to:
-Comparative studies using one or several archives (e.g., including tests of temporal and spatial synchronicity of past regional to global climate changes)
-Proxy system models (and their tuning)
-Model data comparisons (including isotope enabled models or local calibration studies)
-Integrative multi-proxy/multi archive approaches at multiple study sites
-Large scale age model comparisons and record quality assessment studies, including methods aimed at cross validation between different records and variable spatial and temporal scales.