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Title: Global climate impacts of stochastic deep convection parameterization in the NCAR CAM5

Journal Article · · Journal of Advances in Modeling Earth Systems
DOI:https://doi.org/10.1002/2016MS000756· OSTI ID:1357764
 [1];  [2]
  1. Tsinghua Univ., Beijing (China)
  2. Scripps Institution of Oceanography, La Jolla, CA (United States)
+ Show Author Affiliations

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.

Research Organization:
Scripps Institution of Oceanography, La Jolla, CA (United States)
Sponsoring Organization:
USDOE Office of Science (SC), Biological and Environmental Research (BER)
Grant/Contract Number:
SC0016504
OSTI ID:
1357764
Journal Information:
Journal of Advances in Modeling Earth Systems, Vol. 8, Issue 4; ISSN 1942-2466
Publisher:
American Geophysical Union (AGU)Copyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 22 works
Citation information provided by
Web of Science

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Cited By (4)

Ongoing Breakthroughs in Convective Parameterization journal April 2019
Precipitation Partitioning in Multiscale Atmospheric Simulations: Impacts of Stability Restoration Methods journal September 2018
The Impact of a Stochastic Parameterization Scheme on Climate Sensitivity in EC‐Earth journal December 2019
Progress towards a probabilistic Earth system model: examining the impact of stochasticity in the atmosphere and land component of EC-Earth v3.2 journal January 2019

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54 ENVIRONMENTAL SCIENCES
stochastic parameterization
convection
global climate impacts
CAM5