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![Mean radiant temperature [°C] statistics for seasonal RayMan simulations: a) Mean Bias Error (MBE); b) Root Mean Square Error RMSE as bars and Index of Agreement (d) as points; c) Unsystematic Root Mean Square Error (RMSEu) and Systematic Root Mean Square Error (RMSEs).](profile/Peter-Crank-2/publication/343378976/figure/fig4/AS:928554330099716@1598396012935/Mean-radiant-temperature-C-statistics-for-seasonal-RayMan-simulations-a-Mean-Bias.jpg)
Mean radiant temperature [°C] statistics for seasonal RayMan simulations: a) Mean Bias Error (MBE); b) Root Mean Square Error RMSE as bars and Index of Agreement (d) as points; c) Unsystematic Root Mean Square Error (RMSEu) and Systematic Root Mean Square Error (RMSEs).
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![Fig. 3. Mean radiant temperature [°C] observations for each study site...](profile/Peter-Crank-2/publication/343378976/figure/fig3/AS:928554330095618@1598396012868/Mean-radiant-temperature-C-observations-for-each-study-site-and-hourly-transect-by_Q320.jpg)
![Fig. 4. Mean radiant temperature [°C] statistics for seasonal RayMan...](profile/Peter-Crank-2/publication/343378976/figure/fig4/AS:928554330099716@1598396012935/Mean-radiant-temperature-C-statistics-for-seasonal-RayMan-simulations-a-Mean-Bias_Q320.jpg)
We validated seasonal RayMan and ENVI-met mean radiant temperature (TMRT) simulations to assess model performance in a sensitivity analysis from cold to extremely hot conditions. Human-biometeorological validation data were collected in Tempe, Arizona via transects during five field campaigns between 2014 and 2017. Transects were conducted across s...
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... examine our RayMan simulations, we used multiple error metrics to assess the validity of the mode. For all seasons, times of day, and combined receptors (N = 238), RMSE is 10.7 °C with MBE = −0.5 °C and d = 0.88. Across all sites, times of day, and seasons (N = 49), RayMan simulated T MRT exhibits an RMSE of 8.0° to 12.4 °C (Fig. 4, Supp. Table 2). The error remains high irrespective of the instrumentation used for in-situ observations (Kestrel vs. MaRTy). MBE is positive in the summer but negative for winter and shoulder seasons, i.e. RayMan overestimates T MRT in the summer and underestimates T MRT otherwise. Adding T s as a forcing parameter yields similar ...
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... Thus, the formula given by Thorsson et al. (2007) is used for the same with adjusted globe diameter. Many urban climate studies (Lam and Lau, 2018;Crank et al., 2020) which have made use of Kestrel heat stress tracker to estimate T mrt , have used this formula for the calculation. Open arrangement of bushes, shrubs, and short, woody trees. ...
The urban fabric of Pune city has undergone massive changes due to diversifying urban functionalities. The study attempts to identify different urban morphological landscapes within the city based on Local Climate Zones (LCZs) configurations. After identification of urban morphology in accordance with the LCZ scheme, the microclimatic simulations for the performance and attenuation of the meteorological parameters that is air temperature (Ta), relative humidity (RH), mean radiant temperature (Tmrt), and wind speed (WS) was accomplished through ENVI-met during the warmest month for the city. The urban landscapes characteristics similar to the proposed LCZ configuration and to collect field data for the chosen meteorological parameters ground survey was done. In addition to field observations, climatological normals and long-term trends for the meteorological parameters were also analyzed. The simulation results revealed that barren lands are warmer (by ~18℃) than the compact city core due to the heat sink effect. For Ta and RH the simulation is more reliable in case of open LCZs (R2~0.9) compared to compact LCZs (R2~0.5). With changing LCZs, there is no significant change in the simulation except continuous underestimation of the Tmrt and the role of wind flow in modifying Tmrt was noticed.
... However, in actual environments, the atmospheric environment is constantly changing and has spatial variability (Maronga et al. 2019). Future research needs to consider incorporating more parameters, such as WS, T mrt (Crank et al. 2020) and thermal comfort indicators (such as PET, UTCI, etc.), to reduce errors and ensure the accuracy of the model. ...
Camping has become a popular outdoor activity in China. However, the long and scorching summers in China's hot and humid regions pose challenges for campsites in maintaining thermal comfort. Therefore, we explored the impact of tree species and planting methods on the thermal comfort of urban campsites in hot and humid areas using the ENVI-met model to simulate the conditions of the study area. The reliability of the model was validated by comparing the simulated values of air temperature (Ta) and relative humidity (RH) with field measurements. We conducted an in-depth analysis of common trees in hot and humid areas and analyzed the effects of five tree species and four tree planting forms on the microclimate of campsites in such areas, using the physiological equivalent temperature (PET) as the evaluation index of thermal comfort. The results indicated that: (1) trees with larger crown widths were most effective in improving outdoor thermal comfort. The ability of trees to regulate microclimate was more influenced by crown width than by leaf area index (LAI), and (2) trees planted in patches provided the highest level of thermal comfort, whereas single trees provided the lowest. However, relying solely on tree planting made it difficult to significantly reduce outdoor heat stress. Therefore, other methods such as increasing ventilation or mist spray should be adopted to modify camping area. This study provides a reference for the planting design of outdoor campsites in hot and humid regions of China.
... 110 Ladybug does not allow the modification of materials satisfactorily, unlike Honeybee. 111 Ladybug tools can evaluate evaporative cooling but only for indoor spaces. 112 In the input file, there is the possibility to insert specific values for many variables like vegetation, buildings, and topography. ...
... RayMan version 1.2 [108][109][110][111] RayMan (https://www.urbanclimate.net/rayman/) RayMan is a micro-scale model that calculates radiation fluxes in simple and complex environments. ...
The impact of human activities on climate change has become increasingly evident, with cities being particularly vulnerable to its effects. Anthropogenic emissions, such as heat and greenhouse gases, are projected to intensify climate-induced phenomena, which can lead to negative health outcomes. To understand how human health would be affected by such climate-exacerbated phenomena, computational models that consider the local microclimate are essential to better regulate cities to respond to these phenomena. Many simulation tools have been created and enhanced over the years. Therefore, this study systematically reviews the currently available urban microclimate simulation tools and compares their features and capabilities. The review suggests that these models can effectively assist in investigating urban health and testing adaptation strategies, but it is important to acknowledge their limitations due to assumptions made. Nonetheless, with proper interpretation and utilization, these models can provide valuable insights and contribute to informed decision-making processes.
... While research asserts that reductions in cold stress are unlikely to meaningfully impact mortality, dramatic increases in the number of mortalities son that would provide the same radiation load as measured in the environment (Kántor and Unger 2011). T mrt may range from above 80 • C to below −20 • C. Shading effects in strong sunshine can reduce T mrt values by 30 • C or more (Crank et al. 2020;Acero et al. 2021;Middel and Krayenhoff 2019; Thorsson et al. 2014). Advances in modelling have seen the emergence and adoption of thermal stress metrics encompassing all four meteorological variables, such as the Universal Thermal Climate Index (UTCI) and Physiologically Equivalent Temperature (PET), which have shown a potential to improve the identification of dangerous thermal conditions compared to simpler metrics (Błażejczyk et al. 2013;Höppe 1999;Di Napoli et al. 2019). ...
To adapt to Earth’s rapidly changing climate, detailed modelling of thermal stress is needed. Dangerous stress levels are becoming more frequent, longer, and more severe. While traditional measurements of thermal stress have focused on air temperature and humidity, modern measures including radiation and wind speed are becoming widespread. However, projecting such indices has presented a challenging problem, due to the need for appropriate bias correction of multiple variables that vary on hourly timescales. In this paper, we aim to provide a detailed understanding of changing thermal stress patterns incorporating modern measurements, bias correction techniques, and hourly projections to assess the impact of climate change on thermal stress at human scales. To achieve these aims, we conduct a case study of projected thermal stress in central Hobart, Australia for 2040–2059, compared to the historical period 1990–2005. We present the first hourly metre-scale projections of thermal stress driven by multivariate bias-corrected data. We bias correct four variables from six dynamically downscaled General Circulation Models. These outputs drive the Solar and LongWave Environmental Irradiance Geometry model at metre scale, calculating mean radiant temperature and the Universal Thermal Climate Index. We demonstrate that multivariate bias correction can correct means on multiple time scales while accurately preserving mean seasonal trends. Changes in mean air temperature and UTCI by hour of the day and month of the year reveal diurnal and annual patterns in both temporal trends and model agreement. We present plots of future median stress values in the context of historical percentiles, revealing trends and patterns not evident in mean data. Our modelling illustrates a future Hobart that experiences higher and more consistent numbers of hours of heat stress arriving earlier in the year and extending further throughout the day.
... An investigation of the thermal performance of all design combinations was carried out using the ENVI-met (Bruse & Fleer 1998) microclimate model. The ENVI-met model is a valuable tool for accurately assessing microclimate conditions at various scales, from simple to complex urban environments (Salvati et al. 2022;Alssad et al. 2022;Crank et al. 2020;Maggiotto et al. 2014). This three-dimensional software was developed based on fluid dynamics and thermodynamics principles, and offers an algorithm for calculating the radiative flux emitted from plants and materials and their effects on the radiative conditions (Bruse 2004). ...
... Based on the relevant research on RayMan model validation [49,61,62], this study mainly verifies the feasibility of the RayMan model in Wuhan. This experiment takes a university in Wuhan as an example, a total of three measurement locations were set up, including a total of five measurement sites for measuring the solar irradiance in the Wuhan area, as shown in Fig. 4. The total area of this university is 1.803 km 2 . ...
... GWh/year, and 3647. 62 GWh/year, respectively. The annual solar potential of the whole Hanyang District is 8864. ...
Accurate evaluation of rooftop solar potential is increasingly important in sustainable urban development. However, accurately evaluating the solar photovoltaic (PV) potential of rooftops in urban areas is a challenge due to the diversity of urban rooftop outlines and rooftop obstacles. This study proposes a generic framework for evaluating the potential of urban rooftop solar PV that integrates deep learning and geographic information systems (GIS). GIS is used to extract information about land use types and classify buildings based on land use types. A deep learning-based method for calculating the rooftop available area of multi-type buildings is proposed. To validate the proposed methodology, an area in Wuhan containing a variety of building features was used, combined with the utilization of the available rooftop area to estimate the solar photovoltaic potential, and solar irradiance measurement experiments were set up for validation. The results show that the classification of rooftops by building type can effectively improve the accuracy of rooftop availability identification, and the classification process improved the identification of rooftops by 12.68% and obstacles by 12.42% overall. The annual solar potential of urban rooftops in Hanyang District is 8864.37 GWh/year.
... The comparison of tools has two interests: determining which one has the best results and highlighting the impact of implementation differences on the results. The articles studied here were selected because they were involving the comparison of at least two tools, or focused on the simulation of the T mrt (or the different radiative components) or comparing simulations with observation [7]. Comparing the tools highlights the importance of certain simplifications: ...
This article reviews the main tools used to simulate the mean radiant temperature ( T mrt ) under outdoor conditions. Urban environment complexity and the multiplicity of the radiative fluxes force models’ developers to simplify the problem. To summarize the common assumptions of these models, a graphical tool is proposed. In addition to the physical description, effective coherence of models as a tool for urban decision-making is analyzed. Based on this double vision, this article achieves a multi-criteria analysis of T mrt calculation. Nine tools (ENVI-met, Solene-microclimat, SOLWEIG, RayMan, CitySim, Ladybug-Grasshopper, VTUF, DART and LASER/F) are evaluated against five criteria. Three criteria relate to physics implementation: completeness of the considered radiative phenomena, representation of the environment and surface temperature modeling. Two criteria deal with the operational capabilities: consistency with the needs of city-planners and practical accessibility. These criteria highlight various issues, and in particular the conflict between user-friendly practicality and an accurate description of physical phenomena.
... The proposed model performed well with an overall RMSE of just over 5 • C for MRT, which is the acceptable error margin for heat stress studies according to ISO 7226, as used in prior studies [56][57][58][59][60]. Most studies have reported larger MRT discrepancies for existing models, especially when simulating tree-shaded locations [61]. and Gál and Kántor [56] assessed the performance of RayMan and ENVI-met in Tempe, USA (hot and dry climate) and Szeged, Hungary (warm and temperate climate), respectively. ...
... Various researchers have pointed to some of the limitations in ENVI-met's modeling of heat transfer from roofs and other surfaces Maggiotto et al., 2014). Others have noted the challenges of modeling shade accurately in a complex urban environment (Crank et al., 2020;Gál and Kántor, 2020). To maximize the value of numerical models, it is recommended that in situ measurement data be used to validate the model for use in the location of interest (American Society of Mechanical Engineers., 2007;Blocken et al., 2007;Fig. ...
... The most complex of the metrics is Willmott's d, a unitless metric from 0 to 1 where 1 indicates perfect agreement and 0 has no agreement between the data (Willmott, 1981). Acceptable values for Willmott's d start at about 0.7 for T air and 0.5 for T MRT (Acero and Arrizabalaga, 2016;Crank et al., 2020;Roth and Lim, 2017). RMSE is typically expected to be <2 • C for T air and anywhere from 5 to 20 • C for T MRT (Acero and Arrizabalaga, 2016;Crank et al., 2020;Roth and Lim, 2017). ...
... Acceptable values for Willmott's d start at about 0.7 for T air and 0.5 for T MRT (Acero and Arrizabalaga, 2016;Crank et al., 2020;Roth and Lim, 2017). RMSE is typically expected to be <2 • C for T air and anywhere from 5 to 20 • C for T MRT (Acero and Arrizabalaga, 2016;Crank et al., 2020;Roth and Lim, 2017). MBE, as well as RMSE u and RMSE s, do not have specific thresholds in the literature but are Fig. 3. ...
... The models have different specifications, such as spatial and temporal resolution, intensity, input requirements, types of output metrics, and calculations of atmospheric conditions (Crank et al., 2020). Furthermore, they differ in approach to representing the main flow equations and the energy balance on the urban surface. ...
... Out of the 68 works analyzed, 3 mentioned this model, being associated with the ENVI-met, to demonstrate a complementarity between them. The former simulates a complete set of atmospheric variables in grids, whereas the latter was developed specifically to model radiation flux densities and temperature (Crank et al., 2020). ...
... In the evaluated works, 57.45% used the RMSE and 38.30% the MBE to demonstrate the similarity between the data obtained by the simulation and those acquired from the meteorological station. About this topic, the root mean square error (RMSE) represents the mean standard deviation of the model's prediction with respect to observation (Acero & Arrizabalaga, 2016;Chen et al., 2020;Crank et al., 2020;Ghaffarianhoseini et al., 2019;Jin et al., 2020;Salata et al., 2016). The mean bias error (MBE) is a measure of systematic error between predicted and observed values (Ghaffarianhoseini et al., 2019;Javanroodi & Nik, 2020;Jin et al., 2020). ...
Urban climate analysis usually uses data from weather stations, traverse, or satellite images. However, this methodology also has its limitations, since the series of data for climate monitoring can be scarce. Another option that has been earning attention in recent years is numeric models, which perform simulations in urban climate. Obtaining climate data is extremely important for climatology, as well as for related areas, such as urban planning, which uses this data to know how to best order the territory according to climate conditions and their projections. Our study aimed to carry out a literature review regarding urban heat island analysis methodologies, with emphasis on the use of models. We evaluated over 200 scientific documents and we used 68 in the results of this work, reporting different types of models. The results indicated that most of the works on urban climate use a more traditional methodological approach, with fieldwork, whereas studies with models have been carried out in a specific way, especially in cities in the northern hemisphere. Among the articles evaluated, the majority were published in Elsevier publisher journals, which have a more interdisciplinary approach. The most studied models were ENVI-met, SOLWEIG, PALM-4U, RayMan, and TEB. In this way, this work pointed out, unlike other works of review in urban climate methodologies, the difficulty in obtaining field data, emphasizing their importance, with regard to studies of urban heat islands and urban planning. We also conclude that the progress and development of the state of the art in numerical models are conditioned to scientific investment in the area.
