Impact of remotely sensed albedo and vegetation fraction on simulation of urban climate in WRF-urban canopy model: A case study of the urban heat island in Los Angeles

2016 ◽  
Vol 121 (4) ◽  
pp. 1511-1531 ◽  
Author(s):  
P. Vahmani ◽  
G. A. Ban-Weiss
Author(s):  
Estatio Gutie´rrez ◽  
Jorge E. Gonza´lez ◽  
Robert Bornstein ◽  
Mark Arend ◽  
Alberto Martilli

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.


2021 ◽  
Vol 8 (1) ◽  
pp. 14
Author(s):  
Yu-Cheng Chen ◽  
Fang-Yi Cheng ◽  
Cheng-Pei Yang ◽  
Tzu-Ping Lin

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.


2013 ◽  
Vol 135 (4) ◽  
Author(s):  
Estatio Gutiérrez ◽  
Jorge E. González ◽  
Robert Bornstein ◽  
Mark Arend ◽  
Alberto Martilli

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.


Atmosphere ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 546
Author(s):  
Andreas Matzarakis

In the era of climate change, before developing and establishing mitigation and adaptation measures that counteract urban heat island (UHI) effects [...]


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