Stochastic and deterministic tendency adjustments are applied to multiple experiments in the community atmosphere model version 6. The tendency adjustments are gleaned from the DART data assimilation system and a linear relaxation towards ERA-interim reanalysis. In this preprint , Will Chapman and Judith Berner show that the tendency adjustment significantly enhances the representation of the background state climatology for key prognostic and surface variables. Additionally, they show that stochastic tendencies are essential to accurately represent model variability of major atmospheric modes when making tendency adjustments.