Evaluation of vertically resolved longwave radiation in SPARTACUS-Urban 0.7.3 and the sensitivity to urban surface temperatures

Abstract

Cities' materials and urban form impact radiative exchanges and surface and air temperatures. Here, the SPARTACUS (Speedy Algorithm for Radiative Transfer through Cloud Sides) multi-layer approach to modelling longwave radiation in urban areas (SPARTACUS-Urban) is evaluated using the explicit DART (Discrete Anisotropic Radiative Transfer) model. SPARTACUS-Urban describes realistic 3D urban geometry statistically rather than assuming an infinite street canyon. Longwave flux profiles are compared across an August day for a 2 km × 2 km domain in central London. Simulations are conducted with multiple temperature configurations, including realistic temperature profiles derived from thermal camera observations. The SPARTACUS-Urban model performs well (cf. DART, 2022) when all facets are prescribed a single temperature, with normalised bias errors (nBEs) <2.5 % for downwelling fluxes, and <0.5 % for top-of-canopy upwelling fluxes. Errors are larger (nBE <8 %) for net longwave fluxes from walls and roofs. Using more realistic surface temperatures, varying depending on surface shading, the nBE in upwelling longwave increases to ∼2 %. Errors in roof and wall net longwave fluxes increase through the day, but nBEs are still 8 %–11 %. This increase in nBE occurs because SPARTACUS-Urban represents vertical but not horizontal surface temperature variation within a domain. Additionally, SPARTACUS-Urban outperforms the Harman single-layer canyon approach, particularly in the longwave interception by roofs. We conclude that SPARTACUS-Urban accurately predicts longwave fluxes, requiring less computational time (cf. DART, 2022) but with larger errors when surface temperatures vary due to shading. SPARTACUS-Urban could enhance multi-layer urban energy balance scheme prediction of within-canopy temperatures and fluxes.