Abstract
Model simulations are highly sensitive to the formulation of the atmospheric mixing process or entrainment in the deep convective parameterizations used in their atmospheric component. In this paper, we have implemented stochastic entrainment in the deep convection scheme of NCAR CAM5 and analyzed the improvements in model simulation, focusing on the South Asian Summer Monsoon (SASM), as compared to the deterministic entrainment formulation in the default version of the model. Simulations using stochastic entrainment (StochCAM5) outperformed default model simulations (DefCAM5), as inferred from multiple metrics associated with the SASM. StochCAM5 significantly alleviated some of the longstanding SASM biases seen in DefCAM5, such as precipitation pattern and magnitude over the Arabian Sea and western Equatorial Indian ocean, early monsoon withdrawal, and the overestimation in the frequency of light precipitation and the underestimation in the frequency of large-to-extreme precipitation. Related SASM dynamical and thermodynamical features, such as Somali Jet, low-level westerly winds, and meridional tropospheric temperature gradient (MTTG), are improved in StochCAM5. Further, the simulation of monsoon intra-seasonal oscillation (MISO), Madden Julian Oscillation (MJO), and equatorial Kelvin waves are improved in StochCAM5. Many essential climate variables, such as shortwave and longwave cloud forcing, cloud cover, relative and specific humidity, and precipitable water, show significant improvement in StochCAM5.
Highlights
The conventional global climate models (GCMs) have failed to adequately parameterize sub-grid scale cloud and convection processes that occur either in a small region or dissipate instantly (e.g., Jones and Randall 2011)
The simulated total precipitation pattern from DefCAM5 and StochCAM5 is found to be comparable to observations, with average values of 4.06, 4.96, and 5.01 mm/day over the tropical region for observations, DefCAM5, and StochCAM5, respectively
S2), we find a significant decrease in deep convection over South Asia, except the Western Ghats (WG), northeast India, and Indo-Burmese mountains, which show an increase in deep convection in StochCAM5 as compared to DefCAM5
Summary
The conventional global climate models (GCMs) have failed to adequately parameterize sub-grid scale cloud and convection processes that occur either in a small region or dissipate instantly (e.g., Jones and Randall 2011). Wang et al (2018) used the Plant and Craig (2008) scheme in CAM5 to link the stochastic generation of convective clouds to largescale vertical velocity and reported an improvement in Indian summer monsoon (ISM) simulation but a deterioration in precipitation simulation over the equatorial region. The entrainment rate value in the dry updraft region is not sensitive to model results (could be seen in Sušelj et al 2012) and is set to a constant value for simplicity This implementation has improved the representation of convective boundary layer clouds in SCM through an improved simulation of turbulent fluxes.
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