Evaluating Mesoscale Model Predictions and Parameterizations Against SGP ARM Data on a Seasonal Timescale

A major objective of the Atmospheric Radiation Measurement (ARM) Program is to test and improve parameterizations for cloud and radiative processes. A common strategy adopted for this purpose within the ARM science team is to utilize single-column models (SCMs) driven by appropriate boundary conditions derived from observations, so as to isolate the parameterizations themselves. In practice, accurate boundary conditions are very difficult to retrieve from observations, therefore limiting the SCM approach to relatively short intensive operational periods (IOPs), while leaving the overwhelming bulk of the ARM observations virtually untouched. An alternative approach is developed hereafter, which makes use of the continuous data stream provided by ARM. It consists of directly evaluating the predictions and parameterizations of the National Center for Atmospheric Research (NCAR)/Penn State Mesoscale Model (MM5) at the location where observed data are available. The analysis is performed for a long series of daily runs, on a seasonal timescale, i.e., a time period long enough to be relevant to the climate goals of ARM.