Analysis of forcing methods for single-column models

The single-column model (SCM) is a diagnostic model resembling a single vertical column of a 3-dimensional general circulation model (GCM). The SCM includes physical parameterizations which are currently used in modern GCMs. Due to the one-dimensionality of the SCM, the horizontal advection of heat, moisture and momentum are supplied to the model from either observations or 3-dimensional numerical analyses. Single-column models are being used increasingly to both develop and evaluate parameterizations and are an integral component of the Atmospheric Radiation Measurement (ARM) Program research strategy.

Despite the rapid increase in the use of SCMs, there remain important questions concerning the best method of forcing or "running" the SCM. A recent study has found that the temperature and humidity evolution from a particular SCM displayed significant sensitivity to perturbations in the initial conditions. It is not known if this sensitivity is unique to the particular model tested or is an inherent feature of all SCMs. An additional issue is that of relaxation. It is often desirable to perform model runs over periods of several days or more in order to sufficiently evaluate parameterization performance. Unfortunately, errors in the observational data used to force the model can at times lead to large errors in the model temperature and humidity profiles. In order to properly test and evaluate parameterizations it is sometimes necessary to apply a relaxation technique to insure that the model temperature and humidity profiles do not depart significantly from observations. Several alternative methods of relaxation, including re-initialization, are available and there appears to be no general consensus within the SCM community as to which method should be employed.

In this study, we utilize observational data from the ARM Southern Great Plains (SGP) site to investigate the above questions. In one experiment, a series of model runs are performed, each run containing a small random perturbation of the initial conditions. The results from these runs are used to examine the sensitivity of model results from our SCM to the initial conditions. The model results that we will present include the temperature, humidity, surface and TOA radiative flux budget evolution. We also performed several model runs using various methods of relaxation. The results from these runs are analyzed to determine the sensitivity of several model diagnostic quantities to the method of relaxation.