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Title: Parametric behaviors of CLUBB in simulations of low clouds in the C ommunity A tmosphere M odel ( CAM )

Journal Article · · Journal of Advances in Modeling Earth Systems
DOI:https://doi.org/10.1002/2014MS000405· OSTI ID:1402218
 [1];  [2];  [3];  [4];  [3];  [3];  [5];  [5];  [6]
  1. Pacific Northwest National Laboratory, Richland Washington USA, State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences Beijing China, Climate Change Research Center, Chinese Academy of Sciences Beijing China, Institute for Climate and Global Change Research, School of Atmospheric Sciences, Nanjing University Nanjing China, Collaborative Innovation Center of Climate Change Jiangsu Province China
  2. Pacific Northwest National Laboratory, Richland Washington USA, Institute for Climate and Global Change Research, School of Atmospheric Sciences, Nanjing University Nanjing China, Collaborative Innovation Center of Climate Change Jiangsu Province China
  3. Pacific Northwest National Laboratory, Richland Washington USA
  4. University of Wisconsin‐Milwaukee, Milwaukee Wisconsin USA
  5. National Center for Atmospheric Research Boulder Colorado USA
  6. State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences Beijing China
+ Show Author Affiliations

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 4 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 Gaussians 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. Furthermore, this study improves understanding of HOC behavior associated with parameter uncertainties and provides valuable insights for the interaction of macrophysics and microphysics.

Research Organization:
Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
Sponsoring Organization:
USDOE
Grant/Contract Number:
AC02-05CH11231; AC05-76RL01830
OSTI ID:
1402218
Alternate ID(s):
OSTI ID: 1244807; OSTI ID: 1785819
Report Number(s):
PNNL-SA-106629
Journal Information:
Journal of Advances in Modeling Earth Systems, Journal Name: Journal of Advances in Modeling Earth Systems Vol. 7 Journal Issue: 3; ISSN 1942-2466
Publisher:
American Geophysical Union (AGU)Copyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 27 works
Citation information provided by
Web of Science

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