Quantifying the Influence of Meteorological Factors on Diurnal Urban Thermal Directional Anisotropy Using UAV Observations and Controlled Simulations
Lu Jiang, Na Kang, Wei He, Wenmei LiAccurate assessment of the urban thermal environment is challenged by urban thermal anisotropy (UTA). While UTA impacts microclimate evaluations, its meteorological controls remain unquantified because morphology, solar geometry, and weather co-vary in field observations, and existing UTA models assume static, clear-sky conditions. To address this, we combine 45 UAV-based multi-angle thermal scenarios across three seasons and multiple weather states with univariate controlled simulations. In these simulations, one meteorological factor is varied at a time while urban morphology and materials are held fixed. This design isolates the independent effects of air temperature, relative humidity, wind speed, wind direction, and cloud cover on UTA intensity (UTAI, the maximum difference among directional brightness temperatures). Near the winter solstice, the clear-sky UTAI reached 22.0 °C at 13:00, about 5.9 times the overcast value at the same hour (3.7 °C) and 3.7 times the cloudy value (5.9 °C); over the full observation period (10:00–14:00), the cloudy/overcast UTAI ranged from 3.7 to 9.6 °C. Near the spring equinox, the clear-sky UTAI ranged from 11.6 to 15.7 °C, about twice the cloudy values (3.9–8.0 °C). Controlled simulations identify wind speed and cloud cover as the dominant suppressors of daytime UTAI: increasing wind speed from 0 to 4 m/s nearly halves noon UTAI, and from 0 to 8 m/s lowers 12:00 UTAI by 3.2 °C; increasing cloud cover from 0 to 8 oktas lowers 09:00 UTAI by 7.5 °C. By contrast, air temperature and relative humidity mainly shift absolute temperatures while leaving the anisotropy pattern nearly unchanged in the vegetation-free built scene examined, and wind direction has a negligible effect under regular morphology. These results quantify how weather modulates UTA, providing a physical basis for all-weather urban microclimate modeling, heat island assessments, and adaptive thermal remote sensing.