Continuous Single-column Model Evaluation at a Permanent Meteorological Supersite

U ncertainties in numerical predictions of global weather and climate can often be linked to the representation of fast diabatic processes that act on such small scales that they remain unresolved by the general circulation model (GCM). Such processes include turbulence, convection, clouds, and radiative transfer (e.g., Bony and Dufresne 2005). The functional relationships included in a GCM to statistically represent the impact of these subgrid processes on the larger-scale circulation, as a deterministic function of the resolved model state, are often referred to as “parameterizations.” The necessity to evaluate and improve these parameterization schemes has motivated intense scientific research in the last few decades, and has in fact created its own active branch within the atmospheric sciences that is dedicated to this purpose. Good examples are international research projects such as the Global Energy and Water Cycle Experiment (GEWEX) Cloud System Study (GCSS; Browning et al. 1993) and various working groups within the Atmospheric System Research (ASR) program of the U.S. Department of Energy (e.g., Stokes and Schwartz 1994; Ackerman and Stokes 2003). Two research tools have often been applied in the evaluation and development of parameterizations for GCMs. The first is the numerical simulation of turbulence, convection, and clouds in a three-dimensional domain at high resolutions; this technique is known as cloud-resolving modeling (CRM) or large-eddy simulation (LES; e.g., Deardorff 1972; Sommeria 1976). The capacity of CRM and LES to resolve turbulence and convective clouds at high resolutions allows its application as a virtual laboratory, in which small-scale behavior can be studied and understood, CONTINUOUS SINGLE-COLUMN MODEL EVALUATION AT A PERMANENT METEOROLOGICAL SUPERSITE