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Response of urban heat island to future urban expansion over the Beijing–Tianjin–Hebei metropolitan area

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TLDR
In this paper, the responses of urban heat islands to urban expansion in the past decades were simulated using the coupled weather research forecast/urban canopy model (WRF/UCM) system from the 1980s to 2005 and in the future in 2050 embedded with the fine spatial resolution land use/land cover (LULC) datasets over the Beijing-Tianjin-Hebei (BTH) metropolitan area.
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This article is published in Applied Geography.The article was published on 2016-05-01 and is currently open access. It has received 86 citations till now. The article focuses on the topics: Urban climate & Urban climatology.

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Urban heat island effect: A systematic review of spatio-temporal factors, data, methods, and mitigation measures

TL;DR: A systematic and overarching review of different spatial and temporal factors affecting the UHI effect is provided and discusses the findings in policy terms and provides directions for future research.
Journal ArticleDOI

The impact of urbanization and climate change on urban temperatures: a systematic review

Abstract: Cities have elevated temperatures compared to rural areas, a phenomenon known as the “urban heat island”. Higher temperatures increase the risk of heat-related mortality, which will be exacerbated by climate change. To examine the impact of climate change and urban growth on future urban temperatures and the potential for increased heat stress on urban residents. We conducted a systematic review of scientific articles from Jan 2000 to May 2016. The majority (n = 49, = 86%) of studies examined climate change and the urban heat island in isolation, with few (8) considering their combined effect. Urban growth was found to have a large impact on local temperatures, in some cases by up to 5 °C in North-east USA. In some locations climate change increased the heat island, such as Chicago and Beijing, and in others decreased it, such as Paris and Brussels. When the relative impact of both factors was considered, the temperature increase associated with the urban heat island was always higher. Few studies (9) considered heat stress and its consequences for urban populations. Important contributors to urban temperatures, such as variation in urban density and anthropogenic heat release, were often excluded from studies. We identify a need for an increased research focus on (1) urban growth impact on the urban heat island in climate change studies; (2) heat stress; and, (3) variation in urban density and its impacts on anthropogenic heat. Focussing on only one factor, climate change or urban growth, risks underestimating future urban temperatures and hampering adaptation.
Journal ArticleDOI

Urban heat island impacts on building energy consumption: A review of approaches and findings

TL;DR: In this paper, the authors reviewed existing literature for improving the understanding of UHI impacts on building energy consumption and found that UHI could result in a median increase of 19.0% in cooling energy consumption, and a median decrease of 18.7% in heating energy consumption.
Journal ArticleDOI

The surface urban heat island response to urban expansion: A panel analysis for the conterminous United States

TL;DR: This study investigated the relationship between surface UHI (SUHI) and urban area size in the climate and ecological context, and its spatial and temporal variations, based on a panel analysis of about 5000 urban areas of 10km2 or larger, in the conterminous U.S.
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Spatial-temporal change of land surface temperature across 285 cities in China: An urban-rural contrast perspective

TL;DR: The results showed that, 98.9% of the cities exhibited SUHI effect in summer nighttime and the effect was stronger in northern cities than that in southern cities, indicating that the summer nighttime was the key temporal period for SUHI management.
References
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A Description of the Advanced Research WRF Version 2

TL;DR: The Weather Research and Forecasting (WRF) model as mentioned in this paper was developed as a collaborative effort among the NCAR Mesoscale and Microscale Meteorology (MMM) Division, the National Oceanic and Atmospheric Administration's (NOAA) National Centers for Environmental Prediction (NCEP) and Forecast System Laboratory (FSL), the Department of Defense's Air Force Weather Agency (AFWA) and Naval Research Laboratory (NRL), the Center for Analysis and Prediction of Storms (CAPS) at the University of Oklahoma, and the Federal Aviation Administration (F
Journal ArticleDOI

Thermal remote sensing of urban climates

TL;DR: In this article, the authors review the use of thermal remote sensing in the study of urban climates, focusing primarily on the urban heat island effect and progress made towards answering the methodological questions posed by Roth et al.
Journal ArticleDOI

Estimation of land surface temperature-vegetation abundance relationship for urban heat island studies

TL;DR: In this article, the applicability of vegetation fraction derived from a spectral mixture model as an alternative indicator of vegetation abundance was investigated based on examination of a Landsat Enhanced Thematic Mapper Plus (ETM+) image of Indianapolis City, IN, USA, acquired on June 22, 2002.
Journal ArticleDOI

Remote sensing image-based analysis of the relationship between urban heat island and land use/cover changes

TL;DR: Wang et al. as discussed by the authors used Landsat TM and ETM+ images from 1990 to 2000 in the Pearl River Delta (PRD) to retrieve the brightness temperatures and land use/cover types.
Journal ArticleDOI

A simple single-layer urban canopy model for atmospheric models: Comparison with multi-layer and slab models

TL;DR: In this article, a single-layer urban canopy model was developed, and compared to both multi-layer and slab models, which is a column model of energy and momentum exchange between an urban surface and the atmosphere.
Related Papers (5)
Frequently Asked Questions (10)
Q1. What are the contributions in "Response of urban heat island to future urban expansion over the beijing-tianjin-hebei metropolitan area" ?

In this study, the responses of UHI to the urban expansion in the past decades were simulated using the coupled weather research forecast/urban canopy model ( WRF/UCM ) system from the 1980s to 2005 and in the future in 2050 embedded with the fine spatial resolution land use/land cover ( LULC ) datasets over the BeijingeTianjineHebei ( BTH ) metropolitan area. With the urban expansion, the validations suggested that the designed models in this research can well simulate the generation and development of UHI. 

The urban surface had much higher sensible heat flux and much lower latent heat flux than rural areas due, in part, to lower evaporation over the urban surface. 

The low sky view factor also delayed the loss of heat through multiple reflections and the trapping of nearsurface air in urban areas (Argüeso, Evans, Fita, & Bormann, 2013). 

The datasets, which were used to derive the explanatory factors, were obtained from the DSIESS, CAS, including road, population density, and digital elevation data. 

Statistical models, in particular correlation and regression, have been employed widely to determine the effect of urbanization on surface UHI (SUHI). 

The experiments in the 1980s and 2050 were used as the compared experiments presenting the early and future urbanization simulations, respectively. 

Reanalysis data used in this research were obtained from the “National Centers for Environmental Prediction/Global Forecast System (NCEP/GFS)” (http://www.nco.ncep.noaa.gov/pmb/products/ gfs/). 

In January, the correlation coefficient (CC) between the observed and simulated values was significant at the 0.001 level (CC: 0.84 for the temperature and 0.86 for the wind speed). 

A simulated average of 2-m temperature and 10-m wind speed was achieved within the 3 3 pixels surrounding each meteorological station. 

To produce the dependent urbanerural map in the 1980s and 2005, the urban built-up areas were reclassified as the “urban” category, the seas and deserts were reclassified as “others”, and all the other types were reclassified as the “rural” category.