Large-Scale Forcing Impact on the Development of Shallow Convective Clouds Revealed From LASSO Large-Eddy Simulations

Real-world large-eddy simulations (LES) are driven by time-varying large-scale forcings (LSF)-e.g., temperature advection, moisture advection, and subsidence-derived from large-scale weather models. This study investigates the impact of the uncertainty in LSF on real-world LES in terms of the development of shallow convection at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) atmospheric observatory for the June 11, 2016 case using LES provided by the U.S. Department of Energy's LES ARM Symbiotic Simulation and Observation (LASSO) activity. The LASSO data set provides an ensemble of LES for the selected case, which consists of LES runs that were driven by different LSF. The two contrasting LES runs investigated here generate different types of convective clouds, i.e., nonprecipitating shallow clouds and precipitating cumulus congestus, mainly due to the difference of LSF in temperature advection in the free troposphere. The temperature advection modulates the strength of the capping inversion and therefore the buoyancy of the air parcels rising from the atmospheric boundary layer (ABL). The inversion, together with large-scale updrafts, controls the penetration of the ABL thermals into the free troposphere, leading to cumulus congestus in the case of a weaker inversion. In contrast, clouds remain shallow in the case of a strong inversion. Differences between the two simulations are amplified over time, as mixed-phase clouds are formed near the top of the congestus in the weaker inversion case. This high dependency of LES results to LSF stresses the importance of accurate LSF by large-scale models to real-world LES simulations. Plain Language Summary Shallow convective clouds play an important role in weather and climate systems by changing the global energy budget and water cycle of the atmosphere. These shallow convective clouds have horizontal spatial scales of 1 km or smaller, while the initiation, development, and decay of these clouds are affected by weather systems at much larger scales. Therefore, to accurately simulate the shallow convective clouds using computer models, detailed simulations are needed that use very fine model grid spacings and are driven by accurate large-scale weather forcings. However, the forcings are usually derived from numerical weather prediction outputs at much coarser model resolutions, which are unavoidably uncertain. Here, we investigate how the uncertainty in large-scale forcings impact the fine-scale detailed simulations of shallow convective clouds. Our case study shows that the uncertainty in large-scale forcings has big impacts on the detailed cloud simulations by changing the depth, water/ice contents, and surface precipitation of the simulated convective clouds.