U.S. Geological Survey, Geosciences & Environmental Change Science Center, Denver, CO 80225, United States.
Department of Botany and Plant Sciences, University of California Riverside, Riverside, CA 92507, United States.
Sci Total Environ. 2022 Jul 10;829:154589. doi: 10.1016/j.scitotenv.2022.154589. Epub 2022 Mar 16.
Semi-arid urban environments are undergoing an increase in both average air temperatures and in the frequency and intensity of extreme heat events. Within cities, different composition and densities of urban landcovers (ULC) influence local air temperatures, either mitigating or increasing heat. Currently, understanding how combinations of ULC influence air temperature at the block to neighborhood scale is necessary for heat mitigation plans, and yet limited due to the complexities integrating high-resolution ULC with spatial and temporally high-resolution microclimate data. We quantify how ULC influences air temperature at 60 m resolution for day and nighttime climate normals and extreme heat conditions by integrating microclimate sensor data sensor and high-resolution (1 m) ULC for Denver, Colorado's urban core. We derive ULC drivers of air temperature using a structural equation model, then use a random forest algorithm to predict air temperatures for 30-year climate normals and an extreme heat condition. We find that, in conjunction with other ULC, urban tree canopy reduces daytime air temperatures (-0.026 °C per % cover), and the combination of impervious surfaces and buildings increases daytime air temperature (0.021 °C per % cover). Compared to daytime hours, nighttime irrigated turf temperature cooling effects are increased from being non-significant to -0.022 °C per % cover, while tree canopy effects are reduced from -0.026 °C during the day to -0.016 °C at night. Overall, ULC drives ~17% and 25% of local air temperature during the day and night, respectively. ULC influence on daytime air temperatures is altered in extreme heat events, both depending on the ULC type and time of day. Our findings inform urban planners seeking to identify potential hot and cool spots within a semi-arid city and mitigate high urban air temperatures through using ULC within larger urban climate mitigation strategies.
半干旱城市环境的平均气温以及极端高温事件的频率和强度都在增加。在城市内部,城市土地覆盖物(ULC)的不同组成和密度会影响当地气温,要么缓解,要么加剧热量。目前,了解 ULC 组合如何影响街区到邻里尺度的空气温度,对于高温缓解计划是必要的,但由于将高分辨率 ULC 与空间和时间高分辨率微气候数据集成的复杂性,目前还受到限制。我们通过整合微气候传感器数据和科罗拉多州丹佛市城市核心区的高分辨率(1 米)ULC,以 60 米的分辨率量化 ULC 对白天和夜间气候正常和极端高温条件下空气温度的影响。我们使用结构方程模型得出 ULC 对空气温度的驱动因素,然后使用随机森林算法预测 30 年气候正常和极端高温条件下的空气温度。我们发现,与其他 ULC 相结合,城市树木树冠会降低白天的空气温度(每覆盖百分比降低 0.026°C),而不透水面和建筑物的组合会增加白天的空气温度(每覆盖百分比增加 0.021°C)。与白天相比,夜间灌溉草坪的降温效果从无显著影响增加到每覆盖百分比降低 0.022°C,而树冠的影响从白天的 0.026°C 降低到夜间的 0.016°C。总的来说,ULC 对白天和夜间的当地空气温度分别有 17%和 25%的驱动作用。ULC 对白天空气温度的影响在极端高温事件中发生变化,这取决于 ULC 的类型和一天中的时间。我们的研究结果为那些试图在半干旱城市中识别潜在的热点和冷点,并通过在更大的城市气候缓解策略中使用 ULC 来缓解高城市空气温度的城市规划者提供了信息。