Parametric behaviors of CLUBB in simulations of low clouds in the Community Atmosphere Model (CAM). (3rd July 2015)

• Record Type: Journal Article
• Authors: Guo, Zhun; Wang, Minghuai; Qian, Yun; Larson, Vincent E.; Ghan, Steven; Ovchinnikov, Mikhail; A. Bogenschutz, Peter; Gettelman, Andrew; Zhou, Tianjun
• Is Part Of: Journal of advances in modeling earth systems. Volume 7:Number 3(2015:Sep.)
• Page Start: 1005
• Page End: 1025
• Publication Date: 2015-07-03
• Subjects: CLUBB -- higher‐order closure -- stratocumulus -- shallow convection; Geological modeling -- Periodicals; Climatology -- Periodicals; Geochemical modeling -- Periodicals; 551.5011
• DOI: 10.1002/2014MS000405
• Languages: English
• ISSNs: 1942-2466

Abstract

Abstract: In this study, we investigate the sensitivity of simulated low clouds to 14 selected tunable parameters of Cloud Layers Unified By Binormals (CLUBB), a higher‐order closure (HOC) scheme, and four parameters of the Zhang‐McFarlane (ZM) deep convection scheme in the Community Atmosphere Model version 5 (CAM5). A Quasi‐Monte Carlo (QMC) sampling approach is adopted to effectively explore the high‐dimensional parameter space and a generalized linear model is applied to study the responses of simulated cloud fields to tunable parameters. Our results show that the variance in simulated low‐cloud properties (cloud fraction and liquid water path) can be explained by the selected tunable parameters in two different ways: macrophysics itself and its interaction with microphysics. First, the parameters related to dynamic and thermodynamic turbulent structure and double Gaussian closure are found to be the most influential parameters for simulating low clouds. The spatial distributions of the parameter contributions show clear cloud‐regime dependence. Second, because of the coupling between cloud macrophysics and cloud microphysics, the coefficient of the dissipation term in the total water variance equation is influential. This parameter affects the variance of in‐cloud cloud water, which further influences microphysical process rates, such as autoconversion, and eventually low‐cloud fraction. This study improves understanding of HOC behavior associated with parameter uncertainties and provides valuable insights for the interaction of macrophysics and microphysics. Key Points: Influential parameters show strong regime dependence Parameters related to turbulent structure are the most influential ones The parameter related to the cloud water variance is influential