Meter-scale radiative transfer process modelling in complex urban environments: a PALM model validation study

Ongoing climate change, insufficient urban resilience, and the ever-increasing exposure of city dwellers to environmental hazards such as urban heat stress require carefully tailored mitigation strategies supported by high-fidelity urban climate modelling tools. Urban boundary layer processes are strongly affected by urban morphology, vegetation, and the dynamic nature of human activities. Moreover, the complex structure of cities and their properties exacerbate an already complex process of modelling urban areas and climate; as spatial resolution increases, the complexity of radiative processes also increases.

Radiative transfer modelling in microscale urban environments remains challenging due to the highly complex interactions between buildings, vegetation, and dense urban morphology. These interactions include multiple reflections, scattering, shading, and thermal emission. Key factors, such as the sky view factor, the fractions of sunlit and shaded surfaces, and the spatial variability of surface properties, are also considered bottlenecks for numerical models. Despite considerable progress, uncertainties related to radiative transfer parameterisations and input data persist in street-scale simulations.

This study evaluates the Parallelized Large Eddy Simulation Model (PALM) and its Radiative Transfer Model (RTM) in representing shortwave radiation processes within a realistic urban environment. PALM simulations were conducted in spin-up mode at 1 m spatial resolution for a densely built and vegetated area in Prague, Czech Republic, and validated against measurements collected during observational campaigns in 2017 and 2018. Incoming and outgoing shortwave radiation were assessed across a series of selected episodes at four urban locations characterised by contrasting surface properties and urban morphology. 

The results demonstrate that PALM reproduces the incoming shortwave radiation with high fidelity, particularly when driven by carefully selected mesoscale forcing. Larger discrepancies are observed for outgoing shortwave radiation, highlighting its sensitivity to surface representation, vegetation structure, and urban geometry. The analysis identifies inaccuracies in static urban input data, such as building geometry and vegetation parameters, as a dominant source of error. Overall, the findings emphasise the high importance of accurate mesoscale forcing and high-quality urban static datasets for reliable street-scale radiative transfer modelling. Furthermore, this study provides a comprehensive validation of PALM’s shortwave radiation modelling, advancing the understanding of uncertainties in microscale urban radiative transfer simulations and supporting the improved modelling of urban heat exposure and mitigation strategies development.