Modeling the urban heat island mitigation effect of cool coatings in realistic urban morphology

There are currently more than 400 cities that are subject to the urban heat island (UHI) effect, whose summer temperature can be over 15 degrees C above the human thermal comfort zone. As the scope of urbanization expands, more people will feel the influence of the UHI effect. Since cool coatings can serve as a mitigation measure against the UHI effect, this research proposes a method that can estimate its mitigation effect in any given region. The main idea of this method is to simulate the function of cool coatings via increasing the albedo values in the Weather Research and Forecasting (WRF) model. The main novelty of this method is that it incorporates detailed land categorization data to simulate realistic urban morphology for the purpose of improving model performance. To demonstrate the feasibility of the proposed method, the UHI mitigation effect of cool coatings was estimated in the city of Sydney during two consecutive sweltering days (7-8 January 2018) via the WRF model. The results showed that the proposed method fulfilled its purpose. To be specific, as the consequence of a 0.35 albedo increase in urban Sydney, the whole urban area will be subject to an average temperature decrease of 0.76 degrees C, while some regions will experience a temperature decrease as great as 5.71 degrees C during the hottest hour. However, this value for a given zone, such as the downtown coast area, was closely related to the local wind directions. The results also showed that the values of different urban canopy parameters could be treated as auxiliary information of WRF modeling results and used to identify the locations that suffered the most from the UHI effect. Therefore, the proposed method can help decision-makers and stakeholders to better analyze the UHI mitigation potential of cool coatings. Additionally, it indicates incorporating detailed land categorization data is an effective way of improving UHI numerical simulations. (C) 2020 Elsevier Ltd. All rights reserved.