Sub-cloud turbulent kinetic energy has been used to parameterize the cloud-base updraft velocity (w_b) in cumulus parameterizations. The validity of this idea has never been proved in observations. Instead, it was challenged by recent Doppler lidar observations showing a poor correlation between the two. We argue that the low correlation is likely caused by the difficulty of a fixed-point lidar to measure ensemble properties of cumulus fields. Taking advantage of the stationarity and ergodicity of early-afternoon convection, we developed a lidar sampling methodology to measure w_b of a shallow cumulus (ShCu) ensemble (not a single ShCu). By analyzing 128 ShCu ensembles over the Southern Great Plains, we show that the ensemble properties of sub-cloud turbulence explain nearly half of the variability in ensemble-mean w_b, demonstrating the ability of sub-cloud turbulence to dictate w_b. The derived empirical formulas will be useful for developing cumulus parameterizations and satellite inference of w_b.