Long‐Lived Mesoscale Convective Systems of Superparameterized CAM and the Response of CAM

Mesoscale organized convection is generally misrepresented in the large‐scale convective parameterizations used in contemporary climate models. This impacts extreme weather events (e.g., Madden‐Jullian Oscillation) and the general circulation driven by the significant amount of latent heat released from mesoscale organized convection. Studies show that the missing processes could be partially recovered by embedding a 2‐D cloud‐resolving model in each general circulation model columns, that is, superparameterization. To enable analysis of mesoscale convective systems (MCSs) in the multiscale modeling framework, we apply a detection and hierarchical clustering algorithm on the 3‐hourly 2‐D cloud‐resolving model embedded in the superparameterized Community Atmosphere Model (SPCAM) 5.2. We then examine the fields of a long‐lived and large MCS cluster at the central Pacific. The MCS cluster shows a squall line‐like circulation throughout the life cycle in SPCAM. We simultaneously obtain the 3‐hourly CAM parameterized convection outputs based on the time step‐wise perfect initial conditions given by SPCAM. This allows pure model physics comparison without introducing initial condition errors. The results show that CAM has a systematically biased stratiform cooling and moistening response below 3 km to the given SPCAM deep convection favoring conditions. We show that this bias is mainly due to the CAM's stratiform microphysics scheme. The mesoscale organization in SPCAM thus provides a baseline for improvements of convective parameterization of CAM.