Global climate impacts of stochastic deep convection parameterization in the NCAR CAM5
Abstract
In this paper, the stochastic deep convection parameterization of Plant and Craig (PC) is implemented in the Community Atmospheric Model version 5 (CAM5) to incorporate the stochastic processes of convection into the Zhang-McFarlane (ZM) deterministic deep convective scheme. Its impacts on deep convection, shallow convection, large-scale precipitation and associated dynamic and thermodynamic fields are investigated. Results show that with the introduction of the PC stochastic parameterization, deep convection is decreased while shallow convection is enhanced. The decrease in deep convection is mainly caused by the stochastic process and the spatial averaging of input quantities for the PC scheme. More detrained liquid water associated with more shallow convection leads to significant increase in liquid water and ice water paths, which increases large-scale precipitation in tropical regions. Specific humidity, relative humidity, zonal wind in the tropics, and precipitable water are all improved. The simulation of shortwave cloud forcing (SWCF) is also improved. The PC stochastic parameterization decreases the global mean SWCF from -52.25 W/m2 in the standard CAM5 to -48.86 W/m2, close to -47.16 W/m2 in observations. The improvement in SWCF over the tropics is due to decreased low cloud fraction simulated by the stochastic scheme. Sensitivity tests of tuning parameters aremore »
- Authors:
-
- Tsinghua Univ., Beijing (China)
- Scripps Institution of Oceanography, La Jolla, CA (United States)
- Publication Date:
- Research Org.:
- Scripps Institution of Oceanography, La Jolla, CA (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC), Biological and Environmental Research (BER)
- OSTI Identifier:
- 1357764
- Grant/Contract Number:
- SC0016504
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Journal of Advances in Modeling Earth Systems
- Additional Journal Information:
- Journal Volume: 8; Journal Issue: 4; Journal ID: ISSN 1942-2466
- Publisher:
- American Geophysical Union (AGU)
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 54 ENVIRONMENTAL SCIENCES; stochastic parameterization; convection; global climate impacts; CAM5
Citation Formats
Wang, Yong, and Zhang, Guang J. Global climate impacts of stochastic deep convection parameterization in the NCAR CAM5. United States: N. p., 2016.
Web. doi:10.1002/2016MS000756.
Wang, Yong, & Zhang, Guang J. Global climate impacts of stochastic deep convection parameterization in the NCAR CAM5. United States. https://doi.org/10.1002/2016MS000756
Wang, Yong, and Zhang, Guang J. Thu .
"Global climate impacts of stochastic deep convection parameterization in the NCAR CAM5". United States. https://doi.org/10.1002/2016MS000756. https://www.osti.gov/servlets/purl/1357764.
@article{osti_1357764,
title = {Global climate impacts of stochastic deep convection parameterization in the NCAR CAM5},
author = {Wang, Yong and Zhang, Guang J.},
abstractNote = {In this paper, the stochastic deep convection parameterization of Plant and Craig (PC) is implemented in the Community Atmospheric Model version 5 (CAM5) to incorporate the stochastic processes of convection into the Zhang-McFarlane (ZM) deterministic deep convective scheme. Its impacts on deep convection, shallow convection, large-scale precipitation and associated dynamic and thermodynamic fields are investigated. Results show that with the introduction of the PC stochastic parameterization, deep convection is decreased while shallow convection is enhanced. The decrease in deep convection is mainly caused by the stochastic process and the spatial averaging of input quantities for the PC scheme. More detrained liquid water associated with more shallow convection leads to significant increase in liquid water and ice water paths, which increases large-scale precipitation in tropical regions. Specific humidity, relative humidity, zonal wind in the tropics, and precipitable water are all improved. The simulation of shortwave cloud forcing (SWCF) is also improved. The PC stochastic parameterization decreases the global mean SWCF from -52.25 W/m2 in the standard CAM5 to -48.86 W/m2, close to -47.16 W/m2 in observations. The improvement in SWCF over the tropics is due to decreased low cloud fraction simulated by the stochastic scheme. Sensitivity tests of tuning parameters are also performed to investigate the sensitivity of simulated climatology to uncertain parameters in the stochastic deep convection scheme.},
doi = {10.1002/2016MS000756},
journal = {Journal of Advances in Modeling Earth Systems},
number = 4,
volume = 8,
place = {United States},
year = {Thu Sep 29 00:00:00 EDT 2016},
month = {Thu Sep 29 00:00:00 EDT 2016}
}
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