Validation of predictive heat and mass transfer green roof model with extensive green roof field data

Abstract

Green roof technology has been adopted in the United States as a specialized roofing system and as a sustainable technology capable of saving energy. Most of the previous thermal performance models for green roofs have had the main goal of quantifying these energy savings. However, until recently, none of the models had been fully validated with laboratory and experimental data including both heat flux and surface temperature data. A recently developed green roof thermal performance model was validated with detailed experimental data from a new experimental apparatus called a Cold Plate, which is specifically designed and built for that purpose. In order to further examine the accuracy of the model, this paper describes the dynamic validation of the model using field data from a green roof installed on a commercial roof in Chicago. The dynamic validation consists of comparing substrate surface temperature, heat flux through the roof, and net radiation. The validated results show that the green roof thermal model predicts the heat and mass transfer appropriately as long as the long-wave radiation data from a weather station are used to reduce a possible bias resulting from the sky condition.