The Impact of Variable Land‐Atmosphere Coupling on Convective Cloud Populations Observed During the 2016 HI‐SCALE Field Campaign

We use a large‐eddy simulation model with a nested domain configuration (297 and 120 km wide) and an interactive land surface parameterization to simulate the complex population of shallow clouds observed on 30 August 2016 during the Holistic Interactions of Shallow Clouds, Aerosols, and Land‐Ecosystems campaign conducted in north‐central Oklahoma. Shallow convective clouds first formed over southeast Oklahoma and then spread toward the northwest into southern Kansas. By the early afternoon, the relatively uniform shallow cloud field became more complex in which some regions became nearly cloud free and in other regions larger shallow clouds developed with some transitioning to deeper, precipitating convection. We show that the model reproduces the observed heterogeneity in the cloud populations only when realistic variations in soil moisture are used to initialize the model. While more variable soil moisture and to a lesser extent cool lake temperatures drive the initial spatial heterogeneity in the cloud populations, precipitation‐driven cold pools become an important factor after 1300 CST. When smoother soil moisture variations are used in the model, more uniform shallow cloud populations are predicted with far fewer clouds that transition to deeper, precipitating convection that produce cold pools. An algorithm that tracks thousands of individual cumulus show that the more realistic soil moisture distributions produces clouds that are larger and have a longer lifetime. The results suggest that shallow and deep convection parameterizations used by mesoscale models need to account for the effects of variable land‐atmosphere interactions and cold pools.