Sensitivity of the LES PALM Model to Building Parameters Using TABULA Archetypes

There is a strong interaction between the thermal properties of buildings and urban microclimate, which could be seen as a nonlinear feedback loop affecting urban areas' energy consumption. Large eddy simulation (LES) is a reliable model to study the urban microclimate and thermal behavior of buildings. However, the thermal properties of buildings are highly complex and variable, and thus their inventory and representation in LES models is often lacking in detail. This underlines the need for sensitivity studies to improve the efficiency of LES and its application in studies on buildings' energy and their microclimate effects. This paper investigates the sensitivity of the PALM-4U model towards building parameters using the TABULA archetype building framework. In this case study, the effects of varying levels of building detail from homogeneous typologies to very detailed representations on 2 m air temperature, roof, and wall surface temperatures, sensible heat flux, and near-wall (10 cm) air temperature are investigated across three modeling scenarios: (1) a baseline scenario that uses uniform building types, (2) a simplified classification scheme based on PALM’s predefined categories, and (3) a detailed representation that uses 28 TABULA archetypes. Results show 2 m air temperature differences of −0.3 to 0.3°C between scenarios, with the detailed building properties representation exhibiting lower diurnal and higher nocturnal temperatures. Simplified scenarios demonstrate strong surface temperature fluctuations and lower nighttime surface temperatures which indicates fast heat transfer to the environment. In contrast, the TABULA parameterization depicts reduced surface temperature fluctuations and higher nighttime surface temperatures. These findings show a relevant sensitivity of the LES model towards building parameterization and hence detailed and accurate input data on thermal building properties are required to improve the modeling approaches for LES models in urban energy and microclimate studies.