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Effects of a Simple Convective Organization Scheme in a Two-Plume GCM
Baohua Chen 1 , Brian E. Mapes 2
1  Department of Mathematics and Statistics; Texas A&M University at Corpus Christi; Corpus Christi TX USA
2  Rosenstiel School of Marine and Atmospheric Sciences; University of Miami; Miami FL USA

Published: 30 March 2018 by Wiley in Journal of Advances in Modeling Earth Systems
Wiley, Volume 10; 10.1002/2017ms001106
Abstract: A set of experiments is described with the Community Atmosphere Model (CAM5) using a two-plume convection scheme. To represent the differences of organized convection from General Circulation Model (GCM) assumptions of isolated plumes in uniform environments, a dimensionless prognostic “organization” tracer Ω is invoked to lend the second plume a buoyancy advantage relative to the first, as described in Mapes and Neale (2011). When low-entrainment plumes are unconditionally available (Ω = 1 everywhere), deep convection occurs too easily, with consequences including premature (upstream) rainfall in inflows to the deep tropics, excessive convective vs. large-scale rainfall, poor relationships to the vapor field, stable bias in the mean state, weak and poor tropical variability, and midday peak in diurnal rainfall over land. Some of these are shown to also be characteristic of CAM4 with its separated deep and shallow convection schemes. When low-entrainment plumes are forbidden by setting Ω = 0 everywhere, some opposite problems can be discerned. In between those extreme cases, an interactive Ω driven by the evaporation of precipitation acts as a local positive feedback loop, concentrating deep convection: In areas of little recent rain, only highly entraining plumes can occur, unfavorable for rain production. This tunable mechanism steadily increases precipitation variance in both space and time, as illustrated here with maps, time-longitude series, and spectra, while avoiding some mean state biases as illustrated with process-oriented diagnostics such as conserved variable profiles and vapor-binned precipitation curves.
Keywords: entrainment rate, Evaporation of Precipitation, Mean State Bias, Parameterization of Convective Organization, variability
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