Inferring Cloud Feedbacks from ARM Continuous Forcing, ISCCP, and ARSCL Data

Single Column Model (SCM) versions of parent general circulation models (GCMs), accompanied by cloud-resolving models (CRMs) that crudely resolve cloud-scale dynamics, have increasingly been used to simulate limited time periods of observations, driven not so much by specific science questions but by the availability of field experiment data or enhanced soundings during Intensive Observation Periods (IOPs). These exercises have provided limited insights about either climate or cloud parameterization, because it usually cannot be determined whether model-data discrepancies are due to inaccurate largescale advective forcing or inaccurate model physics, and in any case the errors revealed may not be climatically representative or indicative of a shortcoming in the model’s cloud feedback prediction