A New Modeling Approach to Forecast Building Energy Demands During Extreme Heat Events in Complex Cities

2011 ◽  
Author(s):  
Estatio Gutie´rrez ◽  
Jorge E. Gonza´lez ◽  
Robert Bornstein ◽  
Mark Arend ◽  
Alberto Martilli
Keyword(s):  
Urban Heat Island ◽  
Heat Wave ◽  
Extreme Event ◽  
Large City ◽  
Urban Canopy ◽  
Anthropogenic Heat ◽  
Heat Island ◽  
Urban Canopy Model ◽  
Urban Heat ◽  
Canopy Model

The thermal response of a large city including the energy production aspects of it are explored for a large and complex city using urbanized atmospheric mesoscale modeling. The Weather Research and Forecasting (WRF) mesocale model is coupled to a multi-layer urban canopy model that considers thermal and mechanical effects of the urban environment including a building scale energy model to account for anthropogenic heat contributions due to indoor-outdoor temperature differences. This new urban parameterization is used to evaluate the evolution and the resulting urban heat island formation associated to a 3-day heat wave in New York City (NYC) during the summer of 2010. High resolution (250 m.) urban canopy parameters (UCPs) from the National Urban Database were employed to initialize the multi-layer urban parameterization. The precision of the numerical simulations is evaluated using a range of observations. Data from a dense network of surface weather stations, wind profilers and Lidar measurements are compared to model outputs over Manhattan and its surroundings during the 3-days event. The thermal and drag effects of buildings represented in the multilayer urban canopy model improves simulations over urban regions giving better estimates of the surface temperature and wind speed. An accurate representation of the nocturnal urban heat island registered over NYC in the event was obtained from the improved model. The accuracy of the simulation is further assessed against more simplified urban parameterizations models with positive results with new approach. Results are further used to quantify the energy consumption of the buildings during the heat wave, and to explore alternatives to mitigate the intensity of the UHI during the extreme event.

A New Modeling Approach to Forecast Building Energy Demands During Extreme Heat Events in Complex Cities

2013 ◽  
Vol 135 (4) ◽  
Author(s):  
Estatio Gutiérrez ◽  
Jorge E. González ◽  
Robert Bornstein ◽  
Mark Arend ◽  
Alberto Martilli
Keyword(s):  
Urban Heat Island ◽  
Heat Wave ◽  
Extreme Event ◽  
Surface Air Temperature ◽  
Urban Canopy ◽  
Anthropogenic Heat ◽  
Heat Island ◽  
Urban Canopy Model ◽  
Urban Heat ◽  
Canopy Model

The thermal response of a large and complex city including the energy production aspects of it are explored using urbanized atmospheric mesoscale modeling. The Weather Research and Forecasting (WRF) Mesocale model is coupled to a multilayer urban canopy model that considers thermal and mechanical effects of the urban environment including a building scale energy model to account for anthropogenic heat contributions due to indoor–outdoor temperature differences. This new urban parameterization is used to evaluate the evolution and the resulting urban heat island (UHI) formation associated to a 3-day heat wave in New York City (NYC) during the summer of 2010. High-resolution (250 m) urban canopy parameters (UCPs) from the National Urban Database were employed to initialize the multilayer urban parameterization. The precision of the numerical simulations is evaluated using a range of observations. Data from a dense network of surface weather stations, wind profilers, and Lidar measurements are compared to model outputs over Manhattan and its surroundings during the 3-days event. The thermal and drag effects of buildings represented in the multilayer urban canopy model improves simulations over urban regions giving better estimates of the 2 m surface air temperature and 10 m wind speed. An accurate representation of the nocturnal urban heat island registered over NYC in the event was obtained from the improved model. The accuracy of the simulation is further assessed against more simplified urban parameterizations models with positive results with new approach. Results are further used to quantify the energy consumption of the buildings during the heat wave, and to explore alternatives to mitigate the intensity of the UHI during the extreme event.

scholarly journals Modified RAMS-Urban Canopy Model for Heat Island Simulation in Chongqing, China

2008 ◽  
Vol 47 (2) ◽  
pp. 509-524 ◽  
Author(s):  
Hongbin Zhang ◽  
Naoki Sato ◽  
Takeki Izumi ◽  
Keisuke Hanaki ◽  
Toshiya Aramaki
Keyword(s):  
Urban Canopy ◽  
Heat Emission ◽  
Atmospheric Modeling ◽  
Anthropogenic Heat ◽  
Urban Region ◽  
Infinite Length ◽  
Heat Island ◽  
Urban Canopy Model ◽  
Canopy Model ◽  
Anthropogenic Heat Emission

Abstract A single-layer urban canopy model was integrated into a nonhydrostatic meteorological model, the Regional Atmospheric Modeling System (RAMS). In the new model, called RAMS-Urban Canopy (RAMS-UC), anthropogenic heat emission was also considered. The model can be used to calculate radiation, heat, and water fluxes in an urban area, considering the geometric structure and thermodynamic characteristics of the urban canopy. The urban canopy was represented by normalized street canyons of infinite length, which were bordered by buildings on both sides. The urban region was covered by three types of surfaces: roof, wall, and road. Anthropogenic heat was emitted from these surfaces. Sensitivity tests between the original RAMS and the modified one were carried out by simulating the urban heat island (UHI) of Chongqing, located in an inland mountainous region in China. The results of the model were also compared with the observational data. It was found that the original model could not accurately simulate the UHI, in particular at night, whereas the accuracy was significantly improved in the RAMS-UC. The improvement is substantial even when anthropogenic heat emission is set to zero.

scholarly journals Comparison of Urban Heat Island Intensity Estimation Methods Using Urbanized WRF in Berlin, Germany

Atmosphere ◽  
2020 ◽  
Vol 11 (12) ◽  
pp. 1338
Author(s):  
Julian Vogel ◽  
Afshin Afshari
Keyword(s):  
Urban Heat Island ◽  
Weather Prediction ◽  
Urban Canopy ◽  
Anthropogenic Heat ◽  
Estimation Methods ◽  
Mean Bias Error ◽  
Surface Model ◽  
Heat Island ◽  
Near Surface ◽  
Urban Heat

In this study, we present a meso-scale simulation of the urban microclimate in Berlin, Germany, using the Weather Research and Forecasting (WRF) numerical weather prediction platform. The objective of the study is to derive an accurate estimate of the near-surface urban heat island (UHI) intensity. The simulation is conducted over a two-week summer period. We compare different physical schemes, different urban canopy schemes and different methods for estimating the UHI intensity. The urban fraction of each urban category is derived using the Copernicus Impervious Density data and the Corine Land Cover data. High-resolution City Geography Markup Language (CityGML) data is used to estimate the building height densities required by the multi-layer urban canopy model (UCM). Within the single-layer UCM, we implement an anthropogenic heat profile based on the large scale urban consumption of energy (LUCY) model. The optimal model configuration combines the WRF Single Moment Five-Class (WSM5) microphysics scheme, the Bougeault–Lacarrère planetary boundary layer scheme, the eta similarity (Mellor–Yamada–Janjic) surface layer scheme, the Noah Multi-Parameterization land surface model, the Dudhia and Rapid Radiative Transfer Model (RRTM) radiation schemes, and the multi-layer UCM (including the building energy model). Our simulated UHI intensity results agree well with measurements with a root mean squared error of 0.86K and a mean bias error of 0.20K. After model validation, we proceed to compare several UHI intensity calculation methods, including the ‘ring rural reference’ (RRR) method and the ‘virtual rural reference’ (VRR) method. The VRR mthod is also known as the ‘urban increment’ method. We suggest and argument that the VRR approach is superior.

scholarly journals Explore the Accuracy of the Pedestrian Level Temperature Estimated by the Combination of LCZ with WRF Urban Canopy Model through the Microclimate Measurement Network

2021 ◽  
Vol 8 (1) ◽  
pp. 14
Author(s):  
Yu-Cheng Chen ◽  
Fang-Yi Cheng ◽  
Cheng-Pei Yang ◽  
Tzu-Ping Lin
Keyword(s):  
Heat Capacity ◽  
Urban Development ◽  
Urban Climate ◽  
Urban Canopy ◽  
Subtropical Climate ◽  
Heat Island ◽  
Urban Canopy Model ◽  
Urban Heat ◽  
The City ◽  
Canopy Model

Due to the urban heat island effect becoming more evident in the cities in Taiwan, the urban climate has become an essential factor in urban development. Taiwan is located on the border of tropical and subtropical climate zones, the climate condition is hot and humid, and the city shows high-density development. The dense urban development has increased the heat storage capacity of the ground and buildings. However, if only the climate stations set by the Central Meteorological Bureau to observe the climate data are applied, the predicted results differ from the actual urban climate conditions due to the small number of these stations and the too far distance between them. Therefore, this study employs the local climate zone (LCZ), which can classify the land features by considering both land use and land cover, and can be freely generated from satellite images. The LCZ classification method can view the type of the city through the height and density of obstacles. This study also combines the urban canopy model (UCM) of the mesoscale climate prediction model and weather research and forecasts (WRF). This approach can calculate vertical and horizontal planes of the city, such as building volume, road width, the influence of streets and roofs, roof heat capacity, building wall heat capacity, etc., to predict the climatic conditions in different lands in the study area. Simultaneously, to understand the actual distribution of urban climate more accurately, this study used the microclimate measurement network built in the research area to produce pedestrian-level temperature distribution and compared the estimated results with the actual measured values for urban climate assessment. This study can understand the cause of urban heat islands and assist urban planners more appropriately formulate heat island mitigation strategies in different regions.

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