Uncertainty quantification in climate change studies requires observational validation datasets that have known error characteristics. This will allow estimates of uncertainty in climate change simulations to be assessed rigorously and to separate natural variability, which leads to uncertainty, from model error. The historical reanalysis dataset generated by the University of Colorado/CIRES and NOAA/ESRL, the Twentieth Century Reanalysis version 2 (20CRv2), is a comprehensive global atmospheric circulation dataset spanning 1871-2011 that responds to this need. It assimilates only surface pressure and uses monthly Hadley Centre SST and sea ice distributions (HadISST1.1) as boundary conditions. It provides the first reanalysis dataset spanning more than 100 years, with quantified uncertainties, for assessments of climate model simulations of the 20th century, with emphasis on the statistics of daily weather. It uses, together with an NCEP global numerical weather prediction (NWP) land/atmosphere model to provide background first guess"" fields an Ensemble Kalman Filter (EnKF) data assimilation method. This yields a global analysis every 6 hours as the most likely state of the atmosphere and also yields the uncertainty of that analysis. The 20CRv2 dataset provides the first estimates of global tropospheric variability and of the dataset's time-varying quality spanning 1871 to the present at 2 degree spatial resolution. Intercomparisons with independent radiosonde and station temperature data indicate that the reanalyses are of high quality. Overall the quality is approximately that of current three-day NWP forecasts. It is anticipated that the 20CRv2 will be useful to the climate research community for both diagnostic studies and model validations. Some surprising results are already evident such as weak or non-existent trends in the Walker Circulation. Following 20CRv2 with GCOS WCRP and ACRE we are investigating 20CR version 3: an improved version of the historical reanalysis dataset. Results illustrating the effects of higher spatial resolution and increased observational density compared to 20CRv2 will be presented. Reanalysis feasibility for years preceding 20CRv2 (before 1871) have also be investigated. 20CRv3 will have a companion ocean reanalysis generated by Texas A&M University using the Simple Ocean Data Assimilation system. The effects of using SODA boundary conditions compared to HadISST in 20CRv3 will be investigated. The potential for 20CRv3 and SODA to provide global states of the atmosphere land and ocean back to 1850 will be presented.