Influence of Superparameterization and a Higher‐Order Turbulence Closure on Rainfall Bias Over Amazonia in Community Atmosphere Model Version 5. Issue 18 (21st September 2017) - Zhang, Kai; Fu, Rong; Shaikh, Muhammad J.; Ghan, Steven; Wang, Minghuai; Leung, L. Ruby; Dickinson, Robert E.; Marengo, Jose
Abstract: We evaluate the Community Atmosphere Model Version 5 (CAM5) with a higher‐order turbulence closure scheme, named Cloud Layers Unified By Binomials (CLUBB), and a Multiscale Modeling Framework, referred to as the "superparameterization" (SP) with two different microphysics configurations to investigate their influences on rainfall simulations over southern Amazonia. The two different microphysics configurations in SP are the one‐moment cloud microphysics without aerosol treatment (SP1) and two‐moment cloud microphysics coupled with aerosol treatment (SP2). Results show that both SP2 and CLUBB effectively reduce the low biases of rainfall, mainly during the wet season, and reduce low biases of humidity in the lower troposphere with further reduced shallow clouds and increased surface solar flux. These changes increase moist static energy in the lower atmosphere and contribute to stronger convection and more rainfall. SP2 appears to realistically capture the observed increase of relative humidity prior to deep convection, and it significantly increases rainfall in the afternoon; CLUBB significantly delays the afternoon peak rainfall and produces more precipitation in the early morning, due to more gradual transition between shallow and deep convection. In CAM5 and CAM5 with CLUBB, occurrence of more deep convection appears to be a result of stronger heating rather than higher relative humidity. Key Points: Superparameterization and CLUBB improve CAM5 rain rate and diurnal cycle in Amazonian wet season Superparameterization realistically captures the relationships between environmental conditions and rainfall Improved lower tropospheric moisture, shallow‐to‐deep transition, and cloud microphysics with aerosol effect are likely responsible