Parameterizations of physical processes in climate models are highly dependent on the spatial and temporal resolution and must be tuned for each resolution under consideration. At high spatial resolutions, objective methods for parameter tuning are computationally prohibitive. Our work has focused on calibrating parameters in the Community Atmosphere Model 5 (CAM5) at three spatial resolutions: 4, 2 and 1 degrees. Using perturbed-parameter ensembles and uncertainty quantification methodology, we have identified input parameters at each resolution level that minimize discrepancies of key output quantities simulated by CAM5 with respect to satellite data. Our approach makes it possible to calibrate the high-resolution version of CAM5 by leveraging cheaper, low-resolution simulations and statistical models.