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This research incorporates the correlated k distribution BCC-RAD radiationmodel into the climate model BCC_AGCM2.0.1 and examines the change inclimate simulation by implementation of the new radiation algorithm. It isshown that both clear-sky radiation fluxes and cloud radiative forcings(CRFs) are improved. The modeled atmospheric temperature and specifichumidity are also improved due to changes in radiative heating rates, whichmost likely stem from the revised treatment of gaseous absorption. Subgrid cloud variability, including vertical overlap of fractional cloudsand horizontal inhomogeneity in cloud condensate, is addressed by using theMonte Carlo Independent Column Approximation (McICA) method. In McICA, acloud-type-dependent function for cloud fraction decorrelation length, whichgives zonal mean results very close to the observations of CloudSat/CALIPSO,is developed. Compared to utilizing a globally constant decorrelation length,the maximum changes in seasonal CRFs by the new scheme can be as large as 10and 20 W m−2 for longwave (LW) and shortwave (SW) CRFs, respectively,mostly located in the tropics. The inclusion of an observation-basedhorizontal inhomogeneity of cloud condensate has also a significant impact onCRFs, with global means of ~ 1.5 W m−2 and ~ 3.7 Wm−2for LW and SW CRFs at the top of atmosphere (TOA), respectively. Generally,incorporating McICA and horizontal inhomogeneity of cloud condensate in theBCC-RAD model reduces global mean TOA and surface SW and LW flux biases inBCC_AGCM2.0.1. These results demonstrate the feasibility of the new model configuration tobe used in BCC_AGCM2.0.1 for climate simulations, and also indicate thatmore detailed real-world information on cloud structures should be obtainedto constrain cloud settings in McICA in the future

Application and evaluation of a new radiation code under McICA scheme in BCC_AGCM2.0.1