Enhancing urban surface energy balance modeling: Evaluation of SEB models using scaled outdoor experiments in subtropical climates

Accurate modeling of the urban surface energy balance (SEB) is critical for understanding heat flux exchanges in rapidly growing subtropical cities. However, limited site-specific data and complex city morphologies often hamper model validation efforts. Real-world observations often carry uncertainties arising from anthropogenic emissions and variable building layouts. We employed controlled, scaled outdoor experiments in suburban Guangzhou, China, to evaluate two widely used models: the Surface Urban Energy and Water Balance Scheme (SUEWS) and the Single-Layer Urban Canopy Model (SLUCM). By removing anthropogenic emissions and standardizing building configurations, we isolated the impacts of geometry (high-density (H/W = 2) and low-density (H/W = 0.5)) and climate factors on model performance. Additionally, eddy covariance instruments atop an 85 m high-rise building measured fluxes of sensible heat (Q_H) and latent heat (Q_E), along with radiative components (K↓, K↑, L↓, L↑), at neighborhood scale. 
Results reveal that both models exhibit strong agreement with observed net radiation, revealing their effectiveness in capturing radiative exchanges. However, simulating storage heat flux (Q_S) remains challenging, particularly under varied seasonal and sky conditions. SUEWS generally simulates reflected shortwave and outgoing longwave radiation accurately, but incoming longwave radiation suffers under certain sky conditions. Default storage heat flux (Q_S) settings tend to overestimate values, leading to a recalibration of Objective Hysteresis Model (OHM) coefficients. Fitted OHM coefficients based on observation-based storage heat flux (Q_S) significantly improve model agreement, especially for sensible heat flux (Q_H). Modeling of latent heat flux (Q_E) remains challenging, indicating that partitioning between Q_H and Q_E must be addressed in future refinements. The study demonstrates the value of high-quality measurements for advancing urban surface energy balance modeling in diverse climates.