Abstract Trees have been found to have significant cooling effect on outdoor thermal environment. This study explores the characteristics of a tree component (crown) that accounts for a large portion of the cooling effect. A field measurement was conducted in the Gold Coast, Australia, which has a subtropical climate (Cfa), according to the Koppen climate classification. The characteristics of the tree crown were indexed by its crown diameter, crown height, sky view factor (SVF), and leaf area index (LAI), based on which four new indicators that describe crown characteristics were proposed: gross canopy index (GCI), leaf layer index (LLI), crown volume index (CVI), and total canopy index (TCI). The former two are basic indicators and the latter two are sophisticated indicators. The results showed that the two sophisticated indicators were significantly associated with the mean radiant temperature beneath the tree crown and that increasing the value of each indicator by 10% could help reduce the mean radiant temperature by 0.67 °C (CVI) and 0.83 °C (TCI) respectively, if other predictors were fixed. Similarly, increasing the value of each basic indicator by 10% could help reduce the mean radiant temperature by 0.78 °C (GCI) and 0.066 °C (LLI) respectively, but their cooling effects were less significant than CVI and TCI. The thermal effect of the two sophisticated indicators was more significant than that of the two basic ones. Among all, TCI was found to be the best predictor of the outdoor thermal environment underneath the tree crown. This study proposes new effective indicators to quantify the cooling effects of trees and provides a rationale for plant selection in tropical/subtropical climates to achieve a more comfortable outdoor thermal environment.

中文翻译：

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澳大利亚亚热带城市树冠特征及其降温效果研究

摘要 树木对室外热环境具有显着的降温作用。本研究探讨了占冷却效果很大一部分的树组件（树冠）的特征。根据 Koppen 气候分类，在亚热带气候 (Cfa) 的澳大利亚黄金海岸进行了实地测量。以树冠直径、树冠高度、天空视野因子（SVF）和叶面积指数（LAI）为指标对树冠特征进行索引，并在此基础上提出了四个描述树冠特征的新指标：总冠层指数（GCI） 、叶层指数 (LLI)、冠体积指数 (CVI) 和总冠层指数 (TCI)。前两个是基本指标，后两个是复杂指标。结果表明，这两个复杂的指标与树冠下的平均辐射温度显着相关，将每个指标的值增加10%有助于将平均辐射温度降低0.67°C（CVI）和0.83°C（ TCI) 分别，如果其他预测变量是固定的。同样，将每个基本指标的值提高 10% 可以帮助平均辐射温度分别降低 0.78 °C (GCI) 和 0.066 °C (LLI)，但它们的冷却效果不如 CVI 和 TCI。两个复杂指标的热效应比两个基本指标的热效应更显着。其中，TCI 被发现是树冠下室外热环境的最佳预测器。