Global climate impacts of stochastic deep convection parameterization in the NCARCAM5

Abstract

In this study, 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.

Simulation of Precipitation Extremes Using a Stochastic Convective Parameterization in the NCAR CAM5 Under Different Resolutions

“…At different resolutions, the overall geographical distribution of global total precipitation between the CTL and EXP is comparable, with more overestimated tropical ocean precipitation in EXP than that in CTL. The increased total precipitation in EXP is mainly from the increase of grid‐scale precipitation (Wang & Zhang, ).…”

“…With these sensitivity tests and the above three EXP simulations, the resolution dependence of simulated precipitation using the stochastic convection scheme can be investigated. No sensitivity tests are performed for temporal averaging as Wang and Zhang () showed that its impacts are negligible. All simulations except for CTL and EXP simulations at 2° resolution are run for 3 years from 1990 to 1992 with the same vertical resolution of 30 levels.…”

“…The clouds in each GCM grid box are randomly launched according to these two PDFs and contribute to the local fluctuations. Recently, the Plant‐Craig stochastic deep convection scheme was implemented into the National Center for Atmospheric Research Community Atmosphere Model (NCAR CAM5.3) and incorporated into the Zhang‐McFarlane (Zhang & McFarlane, , hereafter ZM) deterministic deep convection scheme (Wang & Zhang, ; Wang, Zhang, & Craig, ). It was found that the stochastic deep convection scheme not only increased the variability of model simulated precipitation but also improved the PDF of precipitation intensity.…”

“…The long‐standing deficiency of lacking intense precipitation in CAM5 was eliminated, and the frequency of occurrence of intense precipitation was increased to a level close to that in the Tropical Rainfall Measuring Mission (TRMM) observations. Wang and Zhang () provided a preliminary assessment of the impact of stochastic deep convection scheme on precipitation and radiation over the tropics at ~2° resolution.…”

“…As an extension of Wang and Zhang (), the present study examines the performance of the stochastic deep convection scheme in simulating precipitation extremes in CAM5 at different resolutions (~2°, 1°, and 0.5°). The sensitivity of the stochastic deep convection scheme to spatial averaging of input quantities for closure over different‐sized areas is also investigated.…”