Verification of a bioclimatic modeling system in a growing suburb in Melbourne
Graphical abstract
Validation process of a bioclimatic modeling system from selection of the measurement points, conducting field measurement and calculation of the RMSU between the measured and simulated outputs (from left to right).
Introduction
The importance of climatic modeling as a powerful planning tool has been regularly highlighted in the literature over the last few decades because of rapid urbanization rate, global climate change, and increased heat wave rate (Oke, 1984). As a result, climatic and bioclimatic modeling systems have been increasingly used to achieve the objectives of climate-sensitive urban planning.
The popularity of numerical modeling for on-site field measurements has led to increased research interest in modeling approaches (Arnfield, 2003). This popularity is justified by the high capacity of climatic modeling to handle the complexities and nonlinearity of urban climate systems. Climatic modeling systems also enable researchers to have greater control over modeling compared with nonlinear on-site field measurements. Most importantly, these modeling systems are economically viable and efficient in saving time and resources (Bruse and Fleer, 1998; Pearlmutter et al., 2006; Sailor and Dietsch, 2007). Modeling approaches can forecast and predict the climatic effects of diverse “what-if” scenarios, which leads to an environmentally friendly planning scheme and an improved outdoor thermal environment for citizens (Song et al., 2006).
On-site field measurement is a time-consuming approach that can only cover a limited number of parameters at a time. The complex interactions of 3D urban spaces and the spatial distribution of climatic parameters cannot be included simultaneously by conducting field measurements (Ali-Toudert and Mayer, 2006; Mirzaei and Haghighat, 2010). However, on-site measurements are an integral part of any modeling approach due to the importance of model validation.
Nowadays, Climatic and bioclimatic modeling systems are increasingly being used to highlight the benefits of heat mitigation strategies in urban areas (e.g., use of green infrastructure, alterations on urban form and street geometry, and application of high-albedo materials). However, testing the reliability of the computational models are necessary before evaluating the effectiveness of heat mitigation scenarios. Although several previous studies have conducted limited assessment of a range of climatic and bioclimatic modeling systems for different contexts with diverse geographical and climatic backgrounds, systematic evaluation of the models and their sensitivity to inputs and control parameters remains lacking. Whether the previous studies on model validation in one part of the world provide any assurance that the model can accurately simulate the effects of heat mitigation scenarios in the other parts of the world remains unclear.
Therefore, this study aims to provide an overview of different types of climatic and bioclimatic modeling systems and briefly present their main benefits and shortcomings in calculations initially. In the second part of this study, one of the most comprehensive and widely used modeling systems, namely, ENVI-met, was selected, and its reliability in different contexts was investigated by reviewing past researches. A sensitivity analysis on inputs and control parameters was then conducted, in line with field measurements in selected areas, to test the applicability of ENVI-met in accurately simulating the influence of future urban growth on one of the fastest growing suburbs in, Melbourne.
Section snippets
Climatic modeling systems
Urban climate models are defined on the basis of their scales, which range from a few centimeters to hundreds of kilometers. The five groups of climatic models based on scale are human-, room-, building-, city block-, and urban-scale models (Murakami, 2006). The scale of a model defines the resolution of each classification, and the resolution of each classification is highly dependent on the model scale.
Urban scale models often have the largest space resolution (Masson, 2000). Therefore,
Methodology
In this section, one of the fastest growing suburbs in Melbourne that will be the subject of rapid urban development in the future is studied. One of the visions of Melbourne City Council for future urban developments is to quantify the thermal and climatic consequences of implementing the proposed urban growth scenarios. Therefore, this section explains the validation process for the model that will be used as the base for future urban growth scenarios and assesses the reliability of ENVI-met
Results of on-site measurement
The climatic data show fluctuations in air temperature, relative humidity, and wind speed in the study area during the measurement dates. This variation is observed not only at different times of the measurement but also at different measurement points. The difference in the average recorded climatic data at different measurement points can be attributed to the accuracy of the equipment, the location of the equipment during the measurement, the proximity to construction sites, and the geometry
Conclusion
This study aims to provide a holistic overview of various modeling systems given the increasing concern of the international scientific community toward global climate change, microclimate, outdoor thermal comfort, and public health. The study also focuses on the software ENVI-met and its reliability as one of the holistic 3D nonhydrostatic models for simulating surface–plant–air interactions. This model is often used to evaluate urban environments and assess the microclimate derived from
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2020, Building and EnvironmentCitation Excerpt :The reliability of ENVI-met in different contexts was investigated by reviewing past researches. ENVI-met was considered a reliable tool for relative comparison of urban dynamics [35]. Matzarakis et al. [36] used the measured data to verify the simulation of short-wave and long-wave radiation flux in the 3D environment of RayMan; the total radiation and mean radiation temperature agreed well with the corresponding measured values.
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