Validation of seasonal mean radiant temperature simulations in hot arid urban climates
Autor: | Peter J. Crank, Anthony J. Brazel, Martin Smith, Melissa Wagner, Dani Hoots, Ariane Middel |
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Rok vydání: | 2020 |
Předmět: |
Environmental Engineering
010504 meteorology & atmospheric sciences Mean squared error 010501 environmental sciences Atmospheric sciences 01 natural sciences Pollution Arid Heat stress Extreme heat Range (statistics) Environmental Chemistry Environmental science Spatial variability Mean radiant temperature Transect Waste Management and Disposal 0105 earth and related environmental sciences |
Zdroj: | The Science of the total environment. 749 |
ISSN: | 1879-1026 |
Popis: | We validated seasonal RayMan and ENVI-met mean radiant temperature (TMRT) simulations to assess model performance in a sensitivity analysis from cold to extremely hot conditions. Human-biometeorological validation data were collected in Tempe, Arizona via transects during five field campaigns between 2014 and 2017. Transects were conducted across seven locations in two to three-hour intervals from 6:00 to 23:00 LST with a Kestrel meter and thermal camera (2014–2015) and the mobile instrument platform MaRTy (2017). Observations across diverse urban forms, sky view factors, and seasons covered a wide range of solar radiation regimes from a minimum TMRT of 8.7 °C to a maximum of 84.9 °C. Both models produced large simulation errors across regimes with RMSE ranging from 8 °C to 12 °C (RayMan) and 11.2 °C to 16.1 °C (ENVI-met), exceeding a suggested TMRT accuracy of ±5 °C for heat stress studies. RayMan model errors were largest for engineered enclosed spaces, complex urban forms, and extreme heat conditions. ENVI-met was unable to resolve intra-domain spatial variability of TMRT and exhibited large errors with RMSE up to 25.5 °C for engineered shade. Both models failed to accurately simulate TMRT for hot conditions. Errors varied seasonally with overestimated TMRT in the summer and underestimated TMRT in the winter and shoulder seasons. Results demonstrate that models should not be used under micrometeorological or morphological extremes without in-situ validation to quantify errors and assess directional bias due to model limitations. |
Databáze: | OpenAIRE |
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