2019
DOI: 10.5194/gmd-12-785-2019
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The Air-temperature Response to Green/blue-infrastructure Evaluation Tool (TARGET v1.0): an efficient and user-friendly model of city cooling

Abstract: Abstract. The adverse impacts of urban heat and global climate change are leading policymakers to consider green and blue infrastructure (GBI) for heat mitigation benefits. Though many models exist to evaluate the cooling impacts of GBI, their complexity and computational demand leaves most of them largely inaccessible to those without specialist expertise and computing facilities. Here a new model called The Air-temperature Response to Green/blue-infrastructure Evaluation Tool (TARGET) is presented. TARGET is… Show more

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Cited by 33 publications
(6 citation statements)
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References 49 publications
(58 reference statements)
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“…Higher magnitudes of urban cooling due to urban vegetation are reported, for example, by Wang et al (2018) in the contiguous United States where tree shading reduces near-surface air temperature by 3.06 • C and by Middel et al (2015) in Phoenix where a moderate increase in tree cover can decrease average urban air temperature by 2.0 • C. This is consistent with the global analysis performed by Manoli et al (2019) showing that the cooling potential of urban vegetation is lower in the tropics. Higher air temperature decrease in drier climates is often linked to urban irrigation, as shown by Broadbent et al (2018b) in Mawson Lakes in Adelaide, where irrigation during a heat wave can reduce average air temperature by up to 2.3 • C. In dry climates, however, the trade-off between tem- perature reduction potential of urban vegetation and water use through irrigation needs to be considered to fully assess the feasibility of such a mitigation strategy (Yang and Wang, 2017;Wang et al, 2019).…”
Section: Discussionmentioning
confidence: 99%
“…Higher magnitudes of urban cooling due to urban vegetation are reported, for example, by Wang et al (2018) in the contiguous United States where tree shading reduces near-surface air temperature by 3.06 • C and by Middel et al (2015) in Phoenix where a moderate increase in tree cover can decrease average urban air temperature by 2.0 • C. This is consistent with the global analysis performed by Manoli et al (2019) showing that the cooling potential of urban vegetation is lower in the tropics. Higher air temperature decrease in drier climates is often linked to urban irrigation, as shown by Broadbent et al (2018b) in Mawson Lakes in Adelaide, where irrigation during a heat wave can reduce average air temperature by up to 2.3 • C. In dry climates, however, the trade-off between tem- perature reduction potential of urban vegetation and water use through irrigation needs to be considered to fully assess the feasibility of such a mitigation strategy (Yang and Wang, 2017;Wang et al, 2019).…”
Section: Discussionmentioning
confidence: 99%
“…Some urban models, such as TARGET (Broadbent et al, 2019) or UT&C (Meili et al, 2020), use inputs such as canyon aspect ratio (h/w) or sky view factor (ψ) for configuration. Although difficult to define for typical real-world urban areas (Masson et al, 2020), these parameters can easily derived from established parameters if the simplified geometric assumptions inherent in many urban models are used.…”
Section: Morphology Datamentioning
confidence: 99%
“…evapotranspiration from urban green spaces and anthropogenic moisture emission) is still limited and needs further improvement. For instance, the development of ecohydrological modules for urban green spaces is still in its early stages (Lee and Park 2008, Song and Wang 2015, Ryu et al 2016, Broadbent et al 2019, Krayenhoff et al 2020, Meili et al 2020, leaving some functions, such as biophysical behaviors of urban vegetation, either simple or vacant. In addition, some simplified anthropogenic moisture modules from individual sectors such as buildings have been developed recently (Vahmani and Hogue 2014, Huang et al 2021, Luo et al 2021a, while the entire inventory of anthropogenic moisture emissions from buildings, industry, traffic, metabolism, etc remain challenging to capture (Sailor 2011).…”
Section: Introductionmentioning
confidence: 99%