2. 1. Introduction Boundary-layer clouds are parameterized in general circulation model (GCM), but simulated in Multi-scale Modeling Framework (MMF) and global cloud resolving model (GCRM). The dimensionality, resolution and domain size that are used to determine them are very different. For example, these clouds are simulated in 3- D in GCRM with a horizontal grid size of 3.5 x 3.5 km 2, in 2-D with a horizontal grid size of 4 km in MMF, but represented as 1-D clouds in GCM. It is important to understand the effects of resolution, domain, dimensionality on the simulation of the boundary-layer clouds in order to better understand the utility of GCM, MMF, and GCRM for representing the boundary-layer processes. The GEWEX (Global Energy and Water-cycle Experiment) Cloud System Study (GCSS) cases provide a well-defined testbed to investigate these effects. The poster shows the results from the tests of the RICO (Rain In Cumulus over the Ocean) precipitating shallow cumulus cloud case. 2. Experiment Design All simulations to be described below use the same initial condition and forcing as the standard GCSS specification. The horizontal and vertical grid spacings used for 2-D and 3-D simulations vary from half of the GCSS spacings to the spacings currently used by 2-D CRM in MMF, as shown in Fig. 1. The domain size used for each simulation (each point in Fig.1) is determined when no sensitivity to increased domain size is obtained. The UCLA Large eddy simulation (LES) model was used for most of the 3-D simulations, while System for Atmospheric Modeling (SAM) LES was used for all 2-D simulations and a few 3-D simulations. An advantage of using the UCLA-LES is that it has both double- and single-moment microphysics, which give us more freedom for sensitivity tests. Single column model (SCM) with intermediately prognostic higher-order turbulence closure (IPHOC) was used for all 1-D simulations. Effects of Resolution, Domain, and Dimensionality on Simulation of Shallow Cumulus Clouds Anning Cheng 1, Kuan-Man Xu 2, Bjorn Stevens 3 1. AS&M, Inc., 2. NASA Langley Research Center, Hampton, VA, 3. University of California, Los Angeles, CA Fig. 2. Selected mean profiles averaged over the last four hours of RICO simulations using the UCLA-LES, showing the sensitivity to horizontal grid spacing (50 m - 2 km). The domain size for the 1 km and 2 km simulations is enlarged to 128 km x 128 km from the standard GCSS domain size (16 km x 16 km). Fig. 7. Dependency of selected mean profiles averaged over the last four hours of simulations on the domain size, using grid spacings of 1 km x 40 m. Fig. 1. A schematic of the grid-spacing sensitivity testing strategy for the GCSS cases. Here ∆x and ∆z refer to the standard GCSS grid sizes in x and z directions, respectively. Fig. 6. Dependency on the horizontal and vertical grid spacings in a) height of the largest  gradient, b) TKE, c) the largest vertical velocity, and d) surface latent heat flux. Fig. 3. Same as Fig. 2 except for showing the sensitivity to vertical grid spacing (20 - 320 m). The domain size is 16 km x 16 km for all simulations. Fig. 4. Sensitivity of the power spectra of vertical velocity at 900 m altitude to a) horizontal (100 m - 2 km) and b) vertical (40 - 320 m) grid spacings. Fig. 5. Sensitivity of cloud size and cloud frequency at 900 m altitude to a) horizontal and b) vertical grid spacings. Fig. 8: Same as Fig. 2 except from 2-D SAM and 1-D IPHOC simulations. The horizontal domain is 256 km for all 2-D simulations. Fig. 9. Same as Fig. 3 except from 2-D SAM simulations. Small transport above surface layer 4. Conclusions When the grid size becomes larger, there is generally an upscale energy shift (Fig. 4). Cloud size increases, but clouds appears less frequently (Fig. 5). Less energetic updrafts, associated with larger cloud water, cloud fraction and precipitation, are produced (Figs. 2, 3 and 6). These sensitivities are stronger for the horizontal grid spacing than for the vertical grid spacing. A small domain size with large grid spacings results in lower cloud top, less cloud water, cloud fraction and precipitation (Fig. 7). The total grid points must be more than 20 in each horizontal direction of 3-D CRM in order to represent a reasonable circulation. The dependence of mean profiles and cloud properties on the resolution for 3-D can apply to 2-D except for precipitation (Figs. 8 and 9). The cloud top is higher in 2-D, due to the relatively strong circulations. With proper parameterizations, the 1-D results are reasonably well compared with the 3-D LES results. 3. Results