Forest canopies act as intermediaries in radiation energy exchange between the atmosphere and the snow surface. The size, location and distribution of forest discontinuities are important controls on forest shortwave radiation transmission and subsequent snow surface shading and radiation energy exchange between the atmosphere and the canopy, but challenges arise when accounting for these vegetation characteristics at large spatial scales. Airborne LiDAR datasets contain detailed information about canopy structure across large spatial scales which can be exploited within 2D transmission models. However, airborne LiDAR data typically does not resolve lower canopy elements, leading to unrealistic depictions of individual trees. We present a methodology to enhance airborne LiDAR data by calculating additional trunk and branch points based on segmentation of a canopy height model, allowing more accurate estimates of canopy shortwave transmissivity. To demonstrate this, we deployed a computationally efficient 2D radiation transfer modelling framework that calculates direct and diffuse radiation from a set of distributed synthetic hemispherical images. The model can predict incoming direct and diffuse solar radiation at the snow surface at high spatial (meter-scale) and temporal (minute-scale) resolutions. Comparison between synthetic and real hemispherical photographs showed that synthetic images, if based on enhanced LiDAR data, featured canopy and individual tree crowns that were much denser than the original LiDAR portrays, improving the representation of vegetation structure especially within dense environments and along canopy edges. Corresponding modelled total shortwave radiation matched well with spatially gridded measurements from a moving pyranometer at two sites, where model RMSE was reduced to 59 and 29 W m−2 from 181 and 138 W m−2, respectively, compared to the same transmission model with the original LiDAR data. Maps of snow surface shading patterns corresponded well to those seen in aerial photographs, showing the enhanced LiDAR data can be used to solve complex spatiotemporal patterns of sub-canopy incoming radiation. This work demonstrates that canopy structure information from the lower canopy is an important aspect for accurate radiation transfer modelling, and methods presented here can successfully mitigate problems inherent in many airborne LiDAR datasets to improve spatially distributed estimates of sub-canopy shortwave radiation.