New radiative parameterizations have been developed for the National Center for Atmospheric Research (NCAR) Community Atmospheric Model (CAM). The CAM is the next version of the NCAR Community Climate Model (CCM). This paper describes the generalized treatment of vertical cloud overlap in the radiative calculations. The new parameterizations compute the shortwave and longwave fluxes and heating rates for random overlap, maximum overlap, or an arbitrary combination of maximum and random overlap. The specification of the type of overlap is identical for the two bands, and it is completely separated from the radiative parameterizations. In the prototype of CAM (CAM 0.1), adjacent cloud layers are maximally overlapped and groups of clouds separated by cloud-free layers are randomly overlapped. The introduction of the generalized overlap assumptions permits more realistic treatments of cloud-radiative interactions. The parameterizations are based upon representations of the radiative transfer equations that are more accurate than previous approximations. These techniques increase the computational cost of the radiative calculations by approximately 30%. The methodology has been designed and validated against calculations based upon the independent pixel approximation (IPA). The solution techniques and validation procedure are described in detail. The hourly radiative fluxes and heating rates from the parameterizations and IPA have been compared for a 1-yr integration of CAM. The mean and rms errors in the hourly longwave top of the atmosphere (TOA) fluxes are -0.006 ± 0.066 W m⁻², and the corresponding errors in the shortwave TOA fluxes are -0.20 ± 1.58 W m⁻². Heating rate errors are O(10⁻³) K day⁻¹. In switching from random to maximum/random overlap, the largest changes in TOA shortwave fluxes occur over tropical continental areas, and the largest changes in TOA longwave fluxes occur in tropical convective regions. The effects on global climate are determined largely by the instantaneous changes in the fluxes rather than feedbacks related to cloud overlap.
