The Impact of Dimensionality on Long-Term Cloud-Resolving Model Simulations

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Abstract
Cloud-resolving model simulations of radiative–convective equilibrium are conducted in both two and three dimensions (2D and 3D) to examine the effect of dimensionality on the equilibrium statistics. Convection is forced by a fixed imposed profile of radiative cooling and surface fluxes from fixed temperature ocean. In the control experiment, using the same number of grid points in both 2D and 3D and a zero mean wind, the temperature and moisture profiles diverge considerably after a few days of simulations. Two mechanisms are shown to be responsible for this. First, 2D geometry causes higher perturbation surface winds resulting from deep convective downdrafts, which lead to a warmer, moister boundary layer and a warmer tropospheric mean temperature state. Additionally, 2D geometry encourages spontaneous large-scale organization, in which areas far away from convection become very dry and thus inhibit further convection there, leading to a drier mean atmosphere. Further experiments were conducted in which horizontal mean winds were applied, adopting both constant and sheared vertical profiles. With mean surface winds that are of the same magnitude as downdraft outflow velocities or greater, convection can no longer increase mean surface fluxes, and the temperature differences between 2D and 3D are greatly reduced. However, the organization of convection still exists with imposed wind profiles. Repeating the experiments on a small 2D domain produced similar equilibrium profiles to the 3D investigations, since the limited domain artificially reduces surface wind speeds, and also restricts mesoscale organization. The main conclusions are that for modeling convection that is highly two-dimensionally organized, such as squall lines or Walker-type circulations over strong SST gradients, and for which a reasonable mean surface wind exists, it is possible that a 2D model can be used. However, for random or clustered convection, and especially in low wind environments, it is highly preferable to use a 3D cloud model.

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