Abstract
<title>Abstract</title> <p>Street orientation is a fundamental spatial determinant of urban microclimate and outdoor thermal comfort (OTC). However, most empirical studies have focused only on typical summer days, failing to capture how street orientation affects OTC over the annual cycle. Conducting daily simulations across the annual cycle remains computationally prohibitive for routine planning practice. This study addresses this gap by investigating the seasonal thermal performance and annual thermal comfort balance of the Yuhou Street historic district in Chenzhou — a representative city in China's Hot-Summer Cold-Winter (HSCW) climate zone. To overcome the limitations of conventional instantaneous simulations, we applied a Fourier harmonic regression algorithm to compress the full 8,760-hour annual meteorological dataset into 12 representative days. A total of 48 ENVI-met simulations were conducted across four street orientations (N–S, E–W, NE–SW, and NW–SE), supported by a Python-based automated workflow for large-scale data processing. The annual daily thermal perception maps and outdoor thermal comfort autonomy (OTCA) distributions reveal that: (1) the NE–SW orientation is the optimal compromise orientation, consistently performing best in both map sets across the annual cycle by effectively balancing summer shading against winter solar access; and (2) the E–W orientation exhibits the highest thermal risk in the annual thermal perception cycle and shows extensive spatial non-autonomy in the OTCA maps. This study provides a standardized, data-driven methodological framework for long-term microclimate assessment and offers quantitative guidance for climate-adaptive urban design in the HSCW region.</p>