Incorporating localized weather station data for microclimate-integrated urban building energy modeling: A campus-scale decarbonization study
Authors:
Xueyu Chen, Tao Wang, Nyuk Hien Wong, Yu Qian Ang
Department of the Built Environment, National University of Singapore, Singapore
Abstract:
Urban building energy modeling (UBEM) has emerged as a robust tool for evaluating building energy performance at scale, yet most current UBEM tools rely on standardized weather files that fail to capture local microclimate variations. While distributed weather stations are increasingly available in campus and district settings, validated methodologies for integrating such localized data into UBEM remain underdeveloped. This study introduces an approach to assign high-resolution microclimate data for a campus-scale UBEM comprising 293 buildings. Using measurements from eight distributed weather stations deployed across campus, we develop and compare three models: a baseline using typical meteorological year (TMY) files, a distance-based microclimate model, and an advanced model incorporating building height and density alongside spatial proximity. The advanced weather station assignment approach achieves significant accuracy improvements over TMY-based simulations, specifically, a 6.58% to 11.51% reduction in the CV(RMSE) and an 9.09% to 15.24% reduction in NMBE. By identifying distinct microclimate patterns – including hot-stagnant zones and cool-ventilated zones – our study enables targeted retrofit strategies that leverage local microclimatic conditions. Scenario analyses demonstrate a potential 24% campus-wide energy reduction pathway through both general and microclimate-tailored interventions, including natural ventilation in favourable zones and enhanced shading in solar-exposed areas. This campus-scale application provides a methodological foundation for integrating distributed meteorological data into UBEM, with direct applicability to institutional, district, and other bounded urban contexts.
Keywords:
Urban building energy modeling; Urban microclimate; Decarbonization pathways; Carbon emissions reduction; Localized meteorological data