Vertical air motion influences cloud formation, mixing and transport processes. Due to limitations in spatial resolution, global atmospheric models cannot resolve the sub-kilometer scale component of this motion. Instead it is represented using the standard deviation in vertical wind velocity within a grid cell, σW. Using a novel deep learning model constrained by observational data, we reveal significant trends in σW over the period 1980-2023. These trends, reaching up to 1% yr-1 in low and mid-level oceanic regions, indicate a more turbulent atmosphere with enhanced cloud formation over the last few decades. We attribute these trends to global shifts in water vapor, temperature and convection, suggesting a connection between enhanced warming, turbulence and cloud microphysics. Over the industrial era we estimate that increased cloud formation from enhanced σW yields a radiative forcing of about -0.1 ± 0.21 W m-2, slightly mitigating greenhouse warming.