Climatic variations at decadal scales, such as phases of accelerated warming, weak monsoons, or widespread subtropical drought, have profound effects on society and the economy. Understanding such variations re-quires insights from the past. However, no data sets of past climate are available to study decadal variability of large-scale climate with state-of-the-art diagnostic methods. Previously available data sets were limited to statistical reconstructions of local or regional surface climate. The PALAEO-RA project produced the first ever comprehensive, 3-dimensional, physically consistent reconstruction of the global climate system at a monthly scale for the past six centuries. This palaeoreanalysis is based on combining information from early instrumental measurements, historical documents, and proxies (e.g. tree rings) with a large ensemble of climate model simulations. To achieve this novel combination, a completely new data assimilation system for palaeoclimatological data was developed. The product is a family of three data sets, termed ModE-RA (the full reanalsysis using the full model simulations and all observations), ModE-RAclim (a reanalysis based only on a model climatology but all observations) and ModE-Sim (the full model simulations without assimilating observations). Analysing all three allows disentangling the the role of observations and model in the full product. The data sets produced in this project allow studying past climatic variations in greater detail than before, providing a multi-variable, 3-dimensional view of past climatic anomalies and allowing to address dynamical causes behind climatic anomalies. We analysed decadal cold periods, decadal drought periods, variations in the Indian monsoons, and effects of volcanic eruptions. Theses analyses provide new insights into the processes governing decadal variability of weather and climate.