Usefulness of Single Column Model Diagnosis through Short-Term Predictions

Abstract

Single column models (SCMs) provide an economical framework for developing and diagnosing representations of diabatic processes in weather and climate models. Their economy is achieved at the price of ignoring interactions with the circulation dynamics and with neighboring columns. It has recently been emphasized that this decoupling can lead to spurious error growth in SCM integrations that can totally obscure the error growth due to errors in the column physics that one hopes to isolate through such integrations. This paper suggests one way around this ?existential crisis? of single column modeling. The basic idea is to focus on short-term SCM forecast errors, at ranges of 6 h or less, before a grossly unrealistic model state develops and before complex diabatic interactions render a clear diagnosis impossible. To illustrate, a short-term forecast error diagnosis of the NCAR SCM is presented for tropical conditions observed during the Tropical Ocean and Global Atmosphere (TOGA) Coupled Ocean?Atmosphere Response Experiment (COARE). The 21-day observing period is divided into 84 6-h segments for this purpose. The SCM error evolution is shown to be nearly linear over these 6-h segments and, indeed, apart from a vertical mean bias, to be mainly an extrapolation of initial tendencies. The latter are then decomposed into contributions by various components of the column physics, and additional 6-h integrations are performed with each component separately and in combination with others to assess its contribution to the 6-h errors. Initial tendency and 6-h error diagnostics thus complement each other in diagnosing column physics errors by this approach. Although the SCM evolution from one time step to the next is nearly linear, the finite-amplitude adjustments made multiple times within each time step to the temperature and humidity to remove supersaturation and convective instabilities make it necessary to consider nonlinear interactions between the column physics components. One such particularly strong interaction is identified between vertical diffusion and deep convection. The former, though nominally small, is shown to have a profound impact on both the amplitude and timing of the latter, and thence on the small imbalance between the total diabatic heating and adiabatic cooling of ascent in the column. The SCM diagnosis thus suggests that misrepresentation of this interaction, in addition to that of the interacting components themselves, might be a major contributor to the NCAR GCM's tropical simulation errors.