Abstract A 3D Monte Carlo photon transport algorithm is presented that computes broadband solar fluxes and heating rates. It treats attenuation by cloud droplets and gases separately and can produce 3D distributions of constituent absorptances. Underlying surfaces are accounted for and diurnal‐mean calculations can be achieved in the same time as typical single‐zenith‐angle experiments. Domain‐averaged fluxes and heating rate profiles are presented for two very different 3D cloud fields: (i) scattered, shallow cumuli inferred from Landsat imagery; and (ii) towering clouds simulated by a cloud‐resolving model. Plane‐parallel, homogeneous (PPH), independent column approximation (ICA), and clear‐sky versions of the 3D fields were generated and used as well. For both cloud fields, total atmospheric absorptance depends very weakly on cloud geometry. Cloud geometry does, however, invoke major differences in surface absorptance and, hence, reflectance to space. At high sun, albedos for 3D clouds are less than corresponding PPH values, but are in almost perfect agreement with ICA estimates. This indicates that simple horizontal variability of cloud optical depth outweighs the impact of cloud sides. At very low sun 3D fields reflect most because of interception of radiation by cloud sides, while PPH and ICA albedos come into better agreement. For the towering cloud field, radiative fluxes are determined largely by clouds below 6 km, despite some clouds reaching 12 km. Heating rate profiles are also affected by cloud geometry. For most sun angles, PPH clouds exhibit anomalously large heating near cloud tops and anomalously small heating beneath clouds. On the other hand, profiles for 3D and ICA fields are very similar and depend much less on altitude; partly because of side illumination but also because the dense cores of inhomogeneous clouds are often radiatively‐shielded (unlike their PPH counterparts). Finally, regular arrays of idealized cloud forms are used to demonstrate the potential ambiguity of using cloud radiative forcing ratios, R , as proxy measures for the impact of clouds on atmospheric absorptance. In essence, R depends not only on how clouds influence atmospheric absorption, but also on how they partition radiation between albedo and transmittance.