Urban Climate

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Climatology".

Deadline for manuscript submissions: closed (31 December 2018) | Viewed by 19089

Special Issue Editors


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Guest Editor
Royal Meteorological Institute of Belgium, B1180 Brussels, Belgium
Interests: NWP; urban parametrization; urban meteorology; interaction climate change and urban climate; land atmosphere interactions; surface data assimilation
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Co-Guest Editor
Royal Meteorological Institute of Belgium, Ringlaan 3, Uccle, Brussels B1180, Belgium
Interests: extreme value analysis; weather and climate extremes; IDF-models; spatial precipitation extremes; drought; past and future climate change
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

According to the latest UN-Habitat scenario (UN-Habitat, 2010), it is projected that by 2050, 70% of the world population will be urban residents. The future climate, as projected by General Circulation Models (GCMs) in the latest IPCC report (IPCC, AR5), will be marked by (i) more frequent, longer, and more intense heat waves associated with air pollution episodes, (ii) exacerbated inland flooding from heavy precipitation, and (iii) extended coastal flooding due to sea level rise. However such global climate information is provided at spatial scales much larger than the (sub)urban scales. Therefore, climate change signals projected by GCMs may not capture some mesoscale features of the urban environment. One very known phenomenon is the so-called Urban Heat Island effect. Regional Climate Models are widely used to understand meso-scale processes, as well as to downscale climate change projections from GCMs to the regional scale required for impact studies. These simulations are typically done at horizontal resolutions of 50 km to 12.5 km. The aim of this Special Issue is:

  • to go beyond what is classically done in regional climate modeling, and to improve downscaling techniques to be valid down to the urban scale. The diversity of results that arises from natural climate variability, the use of different models (global, regional, impact models) and scenarios (land use, greenhouse gases) is identified as uncertainty.
  • to fill the scientific knowledge gap about the effect of 1.5 °C versus 2 °C global warming on the urban climate of cities.
  • to discuss meteorological monitoring network for cities (with a focus on Africa and Asia).

Dr. Rafiq Hamdi
Guest Editor

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Keywords

  • dynamical downscaling
  • statistical downscaling
  • urban heat island
  • 1.5 °C versus 2 °C global warming
  • near-future climate change
  • microclimate measurement
  • propagation of uncertainties
  • heat waves
  • land-use scenario

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Published Papers (3 papers)

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Research

17 pages, 5188 KiB  
Article
The Sensitivity of Urban Heat Island to Urban Green Space—A Model-Based Study of City of Colombo, Sri Lanka
by Dikman Maheng, Ishara Ducton, Dirk Lauwaet, Chris Zevenbergen and Assela Pathirana
Atmosphere 2019, 10(3), 151; https://doi.org/10.3390/atmos10030151 - 21 Mar 2019
Cited by 33 | Viewed by 7595
Abstract
Urbanization continues to trigger massive land-use land-cover change that transforms natural green environments to impermeable paved surfaces. Fast-growing cities in Asia experience increased urban temperature indicating the development of urban heat islands (UHIs) because of decreased urban green space, particularly in recent decades. [...] Read more.
Urbanization continues to trigger massive land-use land-cover change that transforms natural green environments to impermeable paved surfaces. Fast-growing cities in Asia experience increased urban temperature indicating the development of urban heat islands (UHIs) because of decreased urban green space, particularly in recent decades. This paper investigates the existence of UHIs and the impact of green areas to mitigate the impacts of UHIs in Colombo, Sri Lanka, using UrbClim, a boundary climate model that runs two classes of simulations, namely urbanization impact simulations, and greening simulations. The urbanization impact simulation results show that UHIs spread spatially with the reduction of vegetation cover, and increases the average UHI intensity. The greening simulations show that increasing green space up to 30% in urban areas can decrease the average air temperature by 0.1 °C. On the other hand, converting entire green areas into urban areas in suburban areas increases the average temperature from 27.75 °C to 27.78 °C in Colombo. This demonstrates the sensitivity of UHI to vegetation cover in both urban and suburban areas. These seemingly small changes are average grid values and may indicate much higher impacts at sub-grid levels. Full article
(This article belongs to the Special Issue Urban Climate)
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15 pages, 3360 KiB  
Article
Modelling Daily Mean Surface Air Temperature Calculated from Different Methods and Its Impact on Urban-Related Warming Evaluations over Guangzhou and Shenzhen Using the WRF Model
by Deming Zhao and Jian Wu
Atmosphere 2019, 10(2), 48; https://doi.org/10.3390/atmos10020048 - 27 Jan 2019
Viewed by 2711
Abstract
The impacts of urban surface expansion, based on satellite-derived data displaying urban surface expansion in China at different spatial scales from 1980 to 2016, were investigated using nested dynamical downscaling methods with the Weather Research and Forecasting (WRF) regional climate model at a [...] Read more.
The impacts of urban surface expansion, based on satellite-derived data displaying urban surface expansion in China at different spatial scales from 1980 to 2016, were investigated using nested dynamical downscaling methods with the Weather Research and Forecasting (WRF) regional climate model at a 3.3-km resolution over a city and city cluster scale. Urban-related warming, based on daily mean surface air temperature at 2 m (SAT), calculated from the averages of four time records each day (00, 06, 12, and 18 h UTC, T4) and averages of SAT maximum (Tmax) and minimum (Tmin) (Txn), was evaluated. Differences in urban-related warming contributions calculated using T4 and Txn were small, whereas annual mean SAT and trends calculated using Txn were respectively and significantly larger and smaller than those calculated using T4 over Guangzhou and Shenzhen, excluding the trends over middle-northern Shenzhen. The differences in annual mean SAT calculated using T4 and Txn are attributed to nonlinear or asymmetric variations with time for the diurnal cycle of SAT. Meanwhile, differences in trends between T4 and Txn are interpreted as a strong trend for Tmin and a weak one for Tmax, which mitigated the trend for Txn. The impacts on the evaluations of urban-related warming contributions calculated from different methods were the largest over the areas classified as urban surfaces in both time periods (U2U), especially during intense urban-surface-expansion periods between 2000 and 2016. The subregional performances in the changes in annual mean SAT, trends, and urban-related warming are attributed to urban-surface-expansion, which induced varied changes in the diurnal cycle due to asymmetric warming during the daytime and nighttime over different subregions. Full article
(This article belongs to the Special Issue Urban Climate)
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16 pages, 3266 KiB  
Article
The Fingerprint of Climate Change and Urbanization in South Korea
by Won-Ho Nam, Guillermo A. Baigorria, Eun-Mi Hong, Taegon Kim, Yong-Sang Choi and Song Feng
Atmosphere 2018, 9(7), 273; https://doi.org/10.3390/atmos9070273 - 17 Jul 2018
Cited by 7 | Viewed by 6565
Abstract
Understanding long-term changes in precipitation and temperature patterns is important in the detection and characterization of climate change, as is understanding the implications of climate change when performing impact assessments. This study uses a statistically robust methodology to quantify long-, medium- and short-term [...] Read more.
Understanding long-term changes in precipitation and temperature patterns is important in the detection and characterization of climate change, as is understanding the implications of climate change when performing impact assessments. This study uses a statistically robust methodology to quantify long-, medium- and short-term changes for evaluating the degree to which climate change and urbanization have caused temporal changes in precipitation and temperature in South Korea. We sought to identify a fingerprint of changes in precipitation and temperature based on statistically significant differences at multiple-timescales. This study evaluates historical weather data during a 40-year period (1973–2012) and from 54 weather stations. Our results demonstrate that between 1993–2012, minimum and maximum temperature trends in the vicinity of urban and agricultural areas are significantly different from the two previous decades (1973–1992). The results for precipitation amounts show significant differences in urban areas. These results indicate that the climate in urbanized areas has been affected by both the heat island effect and global warming-caused climate change. The increase in the number of rainfall events in agricultural areas is highly significant, although the temporal trends for precipitation amounts showed no significant differences. Overall, the impacts of climate change and urbanization in South Korea have not been continuous over time and have been expressed locally and regionally in terms of precipitation and temperature changes. Full article
(This article belongs to the Special Issue Urban Climate)
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