Evaluating the radiative fidelity of WRF-driven PALM (v25.04) in high-resolution using RTM: impact of diverse urban morphology and vegetation on short-wave radiation

Validating urban short-wave radiation in numerical models is non-trivial, as city measurements are heavily influenced by multiple reflections, absorption, and shading processes driven by the three-dimensional urban morphology and vegetation. At the same time, urban micro-scale models are typically forced by only two types of solar radiation inputs: (i) field measurements, often represented by the global radiation, rarely by the combination of short-wave and long-wave radiation; and (ii) data given from coarser-resolution models. We conduct a novel high-resolution evaluation study of the PALM model (v25.04), driven by the regional WRF model-derived radiative forcing configured in two distinct parameterisation setups, across a multi-episode ensemble spanning from clear-sky to overcast conditions. We validate and quantify PALM's ability to explicitly resolve the spatiotemporal propagation of short-wave radiation and its interaction with heterogeneous urban landscapes against measurements collected from the stations located in morphologically variant urban settings with different solar access. Results demonstrate that PALM resolves urban- and vegetation-induced short-wave radiative exchange (i.e., canyon trapping, vegetation shading, building reflections, interaction with urban surfaces and dynamic timing) with high fidelity regardless of the urban setting. This performance highlights the model's ability to explicitly capture the 3D micro-scale heterogeneity of the urban canopy, providing a detailed representation of radiative interactions and their dynamic timing. The study reveals the dominant role of biases: despite PALM's explicit physical detail, the errors embedded in meso-scale cloud fields and radiation inputs cannot be fully compensated for by the micro-scale model. This work is a benchmark for the validation of high-resolution urban radiative transfer exchanges and shows that future progress in street-scale micrometeorological simulations hinges on rigorous verification of cloud representation and radiative fields in the meso-scale driving data.