Abstract
Background In global climate models (GCMs), the convection is parameterized, since the typical scale of this process is smaller than the model resolution. Purpose This study examines the impact of two different cumulus parameterization schemes on the simulated climate using single-column model (SCM) as well as in an atmospheric global climate model (AGCM). Methods The two schemes used are: the Simplified Arakawa-Schubert (SAS) scheme; and the Emanuel scheme coupled with a probability distribution function-based cloud parameterization scheme (EMAN). Results The humidity, temperature, cloud fraction, and precipitation simulations are improved in EMAN as compared to that of SAS in SCM. Climatological simulations (1981-2014) conducted using an AGCM at a moderate resolution (T106L44: 1.125 degrees x 1.125 degrees) indicated that the use of the EMAN improved the results. The precipitation over the tropical belt also showed improvements in terms of the distributions, biases, and association with observation. These improvements are attributable to a better vertical structure of temperature, especially in the tropics, due to the more realistic estimation of the temperature and moisture fields by the EMAN. The error estimated in outgoing long-wave radiation for EMAN is lower than that of the SAS. The vertical structure of specific humidity and temperature shows less error in EMAN as compared to SAS. Conclusion Results using the SCM and AGCM reveal the benefits of using the EMAN in comparison to the SAS which includes better simulation of the relative humidity, temperature, and precipitation fields.