Using SGP data to evaluate forecasts of central U.S. mesoscale convective systems in a GCM with explicit embedded convection

Description

Using observations from the Southern Great Plains (SGP) site, we show that organized nocturnal eastward-propagating convection in the central U.S. can be captured in a prototype multi-scale global climate model (GCM). Such a model uses embedded cloud-resolving models (CRMs) in each GCM grid volume instead of statistical parameterizations to represent sub-grid convection. This approach is often called super-parameterization, and the model we use is a Super-Parameterized version of the Community Atmospheric Model (SPCAM). The ability to simulate these phenomena is a surprising result, because the CRM in SPCAM is idealized in two dimensions with periodic boundary conditions, which restricts fast-manifold storm propagation mechanisms to the horizontal scale of a GCM grid box and constrains CRM shear organization to a fixed horizontal plane. Nonetheless, these simulated storms are qualitatively characterized as having realistic propagation speeds and may result from slow-manifold pathways linking large-scale dynamics with a prognostic convective life cycle including CRM “memory.” However, limitations in the technique, such as a fixed CRM orientation, and apparent discrepancies in the simulated storm relative flow structure are unresolved issues requiring closer analysis. The Cloud-Associated Parameterizations Testbed (CAPT) approach to evaluating GCM error statistics in forecast mode is applied here to test the sensitivity of this result to CRM orientation and to quantitatively compare the simulations with well-observed storm systems that passed over high-value ground-based sensors at the SGP site. A Newtonian relaxation "nudging" technique has been developed to initialize both the GCM- and the CRM-resolved scales in SPCAM for forecast simulations. This nudging technique spins up the CRM while constraining the large-scale GCM fields with analyzed observations. Propagating storms are captured in SPCAM with any of three different CRM orientations (zonal, meridional, or diagonal). Although the basic convective phenomenon is captured in the model, detailed comparisons with observations reveal that some features of the storm location, thermodynamic structure, and condensate fields are not well simulated.