Evaluation of albedo enhancement to mitigate impacts of urban heat island in Rome (Italy) using WRF meteorological model

Morini, Elena; Touchaei, Ali Gholizade; Rossi, Federico; Cotana, Franco; Akbari, Hashem

doi:10.1016/j.uclim.2017.08.001

Cited by 106 publications

(38 citation statements)

References 38 publications

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“…When the albedo of road increased from 0.2 to 0.45, the daily-averaged urban heat island intensity of the urban area decreased by about 0.1 • C in Montreal [83]. Similarly, in Rome, a higher improvement of urban temperature is noticed during the daytime where temperature is decreased by 4 • C if the albedo of surfaces increases [84]. The model in Prague and Brno suggests that an albedo increased by 0.25 leads to a difference of −0.2 • C in daily average temperature, while an albedo increased by 0.5 leads to a daily average temperature difference of −0.5 • C in Prague and −0.4 • C in Brno [82], which also proves the negative linear relationship between the albedo and air temperature.…”

Section: Discussionmentioning

confidence: 95%

Numerical Simulation of Local Climate Zone Cooling Achieved through Modification of Trees, Albedo and Green Roofs—A Case Study of Changsha, China

Chen

Zheng

2020

Sustainability

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By exploring the cooling potential of tree quantity, ground albedo, green roofs and their combinations in local climate zone (LCZ)-4, LCZ-5, and LCZ-6, this study focuses on the optimum cooling level that can be achieved in open residential regions in Changsha. It designs and models 39 scenarios by integrating in situ measurement and ENVI-met numerical simulation and further compares cooling effects of various combinations of the cooling factors. The results show that (1) an increased number of trees and higher albedo are more effective compared to green roofs in reducing summer potential temperatures at street level (2 m high) in three LCZs. Negative correlations are observed in the pedestrian air temperature with trees and ground albedo; (2) the effects of cooling factors vary among different LCZ classes, with the increased 60% more trees leading to lower outdoor temperatures for LCZ-4 (0.28 °C), LCZ-5 (0.39 °C), and LCZ-6 (0.54 °C), while higher albedo of asphalt surface (increased by 0.4) is more effective in LCZ-4 (reaches to 0.68 °C) 14:00, compare to LCZ-5 (0.49 °C) and LCZ-6 (0.38 °C); (3) applying combined cooling methods can provoke air temperature reduction (up to 0.96 °C), especially when higher levels of tree quantities (increased by 60%) are coupled with cool ground materials (albedo increased by 0.4). The results can contribute useful information for improving thermal environment in existing residential regions and future residential planning.

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Section: Discussionmentioning

confidence: 95%

Numerical Simulation of Local Climate Zone Cooling Achieved through Modification of Trees, Albedo and Green Roofs—A Case Study of Changsha, China

Chen

Zheng

2020

Sustainability

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“…A typical and largely used tool of this type is represented by the Weather Research and Forecasting (WRF) model [9], which properly takes into account the reflections among different urban surfaces and between these and the atmosphere. Recently, this approach has been applied to the area of Rome [10], whose urban climate is modelled in order of evaluating the modification of the UHI intensity subsequent to an increase of the albedo of the horizontal surfaces of the built area.…”

Section: Urban Heat Island and Buildings Albedomentioning

confidence: 99%

A simple methodology for comparing cost-benefit of traditional, green and cool roofs

et al. 2019

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Energy policy makers, architects and researchers, when designing new buildings or rehabilitating the existing ones, are engaged in the attempt of limiting the energy needs for climatization (NZEB buildings) and the environmental pressure exerted by buildings (EU Climate Action). The pursuit of this demanding assignment calls for innovative solutions in conceiving the building envelope and its energy systems. Recently, among the most effective tools for improving the energy and environmental performances of buildings, the technical interventions regarding the roofs are gaining a rising attention. Indeed, covers of buildings are responsible of a relevant part of their energy losses and, on the other hand, could contribute to increasing the UHI effect. In the paper, a simple methodology that compares the energy and environmental benefits of cool and green coverages with traditional ones is presented. The capability of limiting the UHI effect of these solutions is also analysed. The methodology is applied to four cities of the Sicilian Island, characterized by different building density and different microclimates. This in-field application shows the feasibility of the method to be used in different urban contexts, as a useful contribution to the design of new buildings or to the re-design of the existing ones.

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“…As such, analysis of WRF variability has typically been limited to modifying small fragments of the model. For example, studies may change: urban models (Cui & de Foy, 2012; Holt & Pullen, 2007); land‐use products (Feng Chen et al, 2014; De Meij & Vinuesa, 2014; J. Wang et al, 2016); urban parameters, such as building heights or albedo (Lin et al, 2008; Miao et al, 2009; Morini et al, 2018; Touchaei & Wang, 2015); physics schemes (García‐Díez et al, 2013; Kleczek et al, 2014); synoptic conditions (X. X. Li et al, 2013; X. X. Li & Norford, 2016); or initial condition data sources (Gallus & Bresch, 2006; Wu et al, 2005). Several studies combine some of the above, that is, using multiphysics or parameter approaches (Crétat et al, 2012; Evans et al, 2012; Imran et al, 2018; Jankov et al, 2007; Jerez et al, 2013; Mooney et al, 2017; Sharma et al, 2017; Stegehuis et al, 2015; Wan & Zhong, 2014; Z. H. Wang et al, 2011; Zhong & Yang, 2015).…”

Section: Introductionmentioning

confidence: 99%

“…For example, studies may change: urban models (Cui & de Foy, 2012;Holt & Pullen, 2007); land-use products (Feng Chen et al, 2014;De Meij & Vinuesa, 2014;J. Wang et al, 2016); urban parameters, such as building heights or albedo (Lin et al, 2008;Miao et al, 2009;Morini et al, 2018;Touchaei & Wang, 2015); physics schemes (García-Díez et al, 2013;Kleczek et al, 2014); synoptic conditions (X. X. Li et al, 2013;X.…”

Section: Introductionmentioning

confidence: 99%

A Large Ensemble Approach to Quantifying Internal Model Variability Within the WRF Numerical Model

et al. 2020

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The Weather Research and Forecasting (WRF) community model is widely used to explore cross‐scale atmospheric features. Although WRF uncertainty studies exist, these usually involve ensembles where different physics options are selected (e.g., the boundary layer scheme) or adjusting individual parameters. Uncertainty from perturbing initial conditions, which generates internal model variability (IMV), has rarely been considered. Moreover, many off‐line WRF research studies generate conclusions based on a single model run without addressing any form of uncertainty. To demonstrate the importance of IMV, or noise, we present a 4‐month case study of summer 2018 over London, UK, using a 244‐member initial condition ensemble. Simply by changing the model start time, a median 2‐m temperature range or IMV of 1.2 °C was found (occasionally exceeding 8 °C). During our analysis, episodes of high and low IMV were found for all variables explored, explained by a relationship with the boundary condition data. Periods of slower wind speed input contained increased IMV, and vice versa, which we hypothesis is related to how strongly the boundary conditions influence the nested region. We also show the importance of IMV effects for the uncertainty of derived variables like the urban heat island, whose median variation in magnitude is 1 °C. Finally, a realistic ensemble size to capture the majority of WRF IMV is also estimated, essential considering the high computational overheads (244 members equaled 140,000 CPU hours). We envisage that highlighting considerable IMV in this repeatable manner will help advance best practices for the WRF and wider regional climate modeling community.

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Evaluation of albedo enhancement to mitigate impacts of urban heat island in Rome (Italy) using WRF meteorological model

Cited by 106 publications

References 38 publications

Numerical Simulation of Local Climate Zone Cooling Achieved through Modification of Trees, Albedo and Green Roofs—A Case Study of Changsha, China

Numerical Simulation of Local Climate Zone Cooling Achieved through Modification of Trees, Albedo and Green Roofs—A Case Study of Changsha, China

A simple methodology for comparing cost-benefit of traditional, green and cool roofs

A Large Ensemble Approach to Quantifying Internal Model Variability Within the WRF Numerical Model

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