Predictability in Wet and Dry Convective Turbulence

There is a growing interest in understanding the role that moisture plays in atmospheric dynamics, particularly in its effect on predictability. Current research indicates that when moisture effects are added to an atmospheric model, the error growth produced by the new moist dynamics reduces the predictability times, especially at the scales of moist convection. The issue of moist convection's effect on predictability is addressed herein. By performing high-resolution large-ensemble runs, it is shown that although nonprecipitating moist convection is less predictable than dry convection resulting from the same forcing, this effect can be explained by the energy injected into the system through the latent heating and cooling arising from the convective motion. This extra energy is spread evenly over most scales of the convective dynamics. When the predictability times are scaled to account for the extra kinetic energy, and the resulting earlier growth of error energy, wet and dry convection have very similar error growth characteristics. Sensitivity tests are performed to ensure that the results from the large ensembles have converged and that they are consistent with either changing resolution, diffusion levels, initial error energy length scales, or forcing amplitude.