As summer heat waves become the new normal worldwide, modeling human thermal exposure and comfort to assess and mitigate urban overheating is crucial to uphold livability in cities. We introduce PanoMRT, an open source human-biometeorological model to calculate Mean Radiant Temperature (TMRT), Physiologically Equivalent Temperature (PET), and the Universal Thermal Climate Index (UTCI) from thermal equirectangular 360° panoramas and standard weather information (air temperature, relative humidity, wind speed). We validated the model for hot, dry, clear summer days in Tempe, Arizona, USA with in-situ observations using a FLIR Duo Pro R thermal camera on a rotating arm and the mobile human-biometeorological instrument platform MaRTy. We observed and modeled TMRT and thermal comfort for 19 sites with varying ground cover (grass, concrete, asphalt), sky view factor, exposure (sun, shade), and shade type (engineered, natural) six times per day. PanoMRT performed well with a Root Mean Square Error (RMSE) of 4.1 °C for TMRT, 2.6 °C for PET, and 1.2 °C for UTCI, meeting the accuracy requirement of ±5 °C set in the ISO 7726 standard for heat and cold stress studies. RayMan reference model runs without measured surface temperature forcing reveal that accurate longwave radiative flux estimations are crucial to meet the ±5 °C threshold, particularly for shaded locations and during midday when surface temperatures peak and longwave modeling errors are largest. This study demonstrates the importance of spatially resolved 3D surface temperature data for thermal exposure and comfort modeling to capture complex longwave radiation exposure patterns resulting from heterogeneity in built configuration and material radiative and thermal properties in the built environment.
Keywords: Human-biometeorological observations and modeling; Infrared thermal panoramas; Mean radiant temperature; Thermal exposure.
Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.