scholarly journals Simultaneous assessment of the summer urban heat island in Moscow megacity based on in situ observations, thermal satellite images and mesoscale modeling

2019 ◽  
Vol 12 (4) ◽  
pp. 74-95 ◽  
Author(s):  
Mikhail I. Varentsov ◽  
Mikhail Y. Grishchenko ◽  
Hendrik Wouters
Keyword(s):  
Remote Sensing ◽  
Spatial Structure ◽  
Urban Heat Island ◽  
Air Temperature ◽  
Surface Air Temperature ◽  
Atmospheric Model ◽  
Heat Island ◽  
Near Surface ◽  
Urban Heat

This study compares three popular approaches to quantify the urban heat island (UHI) effect in Moscow megacity in a summer season (June-August 2015). The first approach uses the measurements of the near-surface air temperature obtained from weather stations, the second is based on remote sensing from thermal imagery of MODIS satellites, and the third is based on the numerical simulations with the mesoscale atmospheric model COSMO-CLM coupled with the urban canopy scheme TERRA_URB. The first approach allows studying the canopy-layer UHI (CLUHI, or anomaly of a near- surface air temperature), while the second allows studying the surface UHI (SUHI, or anomaly of a land surface temperature), and both types of the UHI could be simulated by the atmospheric model. These approaches were compared in the daytime, evening and nighttime conditions. The results of the study highlight a substantial difference between the SUHI and CLUHI in terms of the diurnal variation and spatial structure. The strongest differences are found at the daytime, at which the SUHI reaches the maximal intensity (up to 10°С) whereas the CLUHI reaches the minimum intensity (1.5°С). However, there is a stronger consistency between CLUHU and SUHI at night, when their intensities converge to 5–6°С. In addition, the nighttime CLUHI and SUHI have similar monocentric spatial structure with a temperature maximum in the city center. The presented findings should be taken into account when interpreting and comparing the results of UHI studies, based on the different approaches. The mesoscale model reproduces the CLUHI-SUHI relationships and provides good agreement with in situ observations on the CLUHI spatiotemporal variations (with near-zero biases for daytime and nighttime CLUHI intensity and correlation coefficients more than 0.8 for CLUHI spatial patterns). However, the agreement of the simulated SUHI with the remote sensing data is lower than agreement of the simulated CLUHI with in situ measurements. Specifically, the model tends to overestimate the daytime SUHI intensity. These results indicate a need for further in-depth investigation of the model behavior and SUHI–CLUHI relationships in general.

scholarly journals Estimating urban heat island effects on near-surface air temperature records of Uccle (Brussels, Belgium): an observational and modeling study

2011 ◽  
Vol 6 (1) ◽  
pp. 27-34 ◽  
Author(s):  
R. Hamdi ◽  
H. Van de Vyver
Keyword(s):  
Remote Sensing ◽  
Urban Heat Island ◽  
Air Temperature ◽  
Surface Air Temperature ◽  
Heat Island ◽  
Urban Bias ◽  
Near Surface ◽  
Urban Warming ◽  
Urban Heat ◽  
Weather Stations

Abstract. In this letter, the Brussels's urban heat island (UHI) effect on the near-surface air temperature time series of Uccle (the national suburban recording station of the Royal Meteorological Institute of Belgium) was estimated between 1955 and 2006 during the summer months. The UHI of Brussels was estimated using both ground-based weather stations and remote sensing imagery combined with a land surface scheme that includes a state-of-the-art urban parameterization, the Town Energy Balance scheme. Analysis of urban warming based on the remote sensing method reveals that the urban bias on minimum air temperature is rising at a higher rate, 2.5 times (2.85 ground-based observed) more, than on maximum temperature, with a linear trend of 0.15 °C (0.19 °C ground-based observed) and 0.06 °C (0.06 °C ground-based observed) per decade respectively. The summer-mean urban bias on the mean air temperature is 0.8 °C (0.9 °C ground-based observed). The results based on remote sensing imagery are compatible with estimates of urban warming based on weather stations. Therefore, the technique presented in this work is a useful tool in estimating the urban heat island contamination in long time series, countering the drawbacks of an ground-observational approach.

scholarly journals The Trend Inconsistency between Land Surface Temperature and Near Surface Air Temperature in Assessing Urban Heat Island Effects

2020 ◽  
Vol 12 (8) ◽  
pp. 1271 ◽  
Author(s):  
Tao Sun ◽  
Ranhao Sun ◽  
Liding Chen
Keyword(s):  
Surface Temperature ◽  
Urban Heat Island ◽  
Air Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Temporal Trends ◽  
Surface Air Temperature ◽  
Heat Island ◽  
Near Surface ◽  
Urban Heat

The credible urban heat island (UHI) trend is crucial for assessing the effects of urbanization on climate. Land surface temperature (LST) and near surface air temperature (SAT) have been extensively used to obtain UHI intensities. However, the consistency of UHI trend between LST and SAT has rarely been discussed. This paper quantified the temporal stability and trend consistency between Moderate Resolution Imaging Spectroradiometer (MODIS) LST and in situ SAT. Linear regressions, temporal trends and coefficients of variations (CV) were analyzed based on the yearly mean, maximum and minimum temperatures. The findings in this study were: (1) Good statistical consistency (R2 = 0.794) and the same trends were found only in mean temperature between LST-UHI and SAT-UHI. There are 54% of cities that showed opposite temporal trends between LST-UHI and SAT-UHI for minimum temperature while the percentage was 38% for maximum temperature. (2) The high discrepancies in temporal trends were observed for all cities, which indicated the inadequacy of LST for obtaining reliable UHI trends especially when using the maximum and minimum temperatures. (3) The larger uncertainties of LST-UHI were probably due to high inter-annual fluctuations of LST. The topography was the predominant factor that affected the UHI variations for both LST and SAT. Therefore, we suggested that SAT should be combined with LST to ensure the dependable temporal series of UHI. This paper provided references for understanding the UHI effects on various surfaces.

scholarly journals Effectiveness of Different Urban Heat Island Mitigation Methods and Their Regional Impacts

2017 ◽  
Vol 18 (11) ◽  
pp. 2991-3012 ◽  
Author(s):  
Ning Zhang ◽  
Yan Chen ◽  
Ling Luo ◽  
Yongwei Wang
Keyword(s):  
Boundary Layer ◽  
Urban Heat Island ◽  
Air Temperature ◽  
Surface Air Temperature ◽  
Green Roofs ◽  
Heat Island ◽  
Near Surface ◽  
Regional Impacts ◽  
Urban Heat ◽  
Cool Roofs

Abstract Cool roofs and green roofs are two popular methods to mitigate the urban heat island and improve urban climates. The effectiveness of different urban heat island mitigation strategies in the summer of 2013 in the Yangtze River delta, China, is investigated using the Weather Research and Forecasting (WRF) Model coupled with a physically based single-layer urban canopy model. The modifications to the roof surface changed the urban surface radiation balance and then modified the local surface energy budget. Both cool roofs and green roofs led to a lower surface skin temperature and near-surface air temperature. Increasing the roof albedo to 0.5 caused a similar effectiveness as covering 25% of urban roofs with vegetation; increasing the roof albedo to 0.7 caused a similar near-surface air temperature decrease as 50% green roof coverage. The near-surface relative humidity increased in both cool roof and green roof experiments because of the combination of the impacts of increases in specific humidity and decreases in air temperature. The regional impacts of cool roofs and green roofs were evaluated using a regional effect index. A regional impact was found for near-surface air temperature and specific/relative humidity when the percentage of roofs covered with high-albedo materials or green roofs reached a higher fraction (greater than 50%). The changes in the vertical profiles of temperature cause a more stable atmospheric boundary layer over the urban area; at the same time, the crossover phenomena occurred above the boundary layer due to the decrease in vertical wind speed.

scholarly journals Investigation of Urban Air Temperature and Humidity Patterns during Extreme Heat Conditions Using Satellite-Derived Data

2015 ◽  
Vol 54 (11) ◽  
pp. 2245-2259 ◽  
Author(s):  
Leiqiu Hu ◽  
Andrew J. Monaghan ◽  
Nathaniel A. Brunsell
Keyword(s):  
Urban Heat Island ◽  
Air Temperature ◽  
Urban Land Use ◽  
Extreme Heat ◽  
Heat Island ◽  
Near Surface ◽  
Vegetation Fraction ◽  
Dewpoint Temperature ◽  
Temperature And Humidity ◽  
Urban Heat

AbstractExtreme heat is a leading cause of weather-related human mortality. The urban heat island (UHI) can magnify heat exposure in metropolitan areas. This study investigates the ability of a new MODIS-retrieved near-surface air temperature and humidity dataset to depict urban heat patterns over metropolitan Chicago, Illinois, during June–August 2003–13 under clear-sky conditions. A self-organizing mapping (SOM) technique is used to cluster air temperature data into six predominant patterns. The hottest heat patterns from the SOM analysis are compared with the 11-summer median conditions using the urban heat island curve (UHIC). The UHIC shows the relationship between air temperature (and dewpoint temperature) and urban land-use fraction. It is found that during these hottest events 1) the air temperature and dewpoint temperature over the study area increase most during nighttime, by at least 4 K relative to the median conditions; 2) the urban–rural temperature/humidity gradient is decreased as a result of larger temperature and humidity increases over the areas with greater vegetation fraction than over those with greater urban fraction; and 3) heat patterns grow more rapidly leading up to the events, followed by a slower return to normal conditions afterward. This research provides an alternate way to investigate the spatiotemporal characteristics of the UHI, using a satellite remote sensing perspective on air temperature and humidity. The technique has potential to be applied to cities globally and provides a climatological perspective on extreme heat that complements the many case studies of individual events.

Urban heat island diagnosis using ASTER satellite images and ‘in situ’ air temperature

2009 ◽  
Vol 94 (2) ◽  
pp. 276-284 ◽  
Author(s):  
Janet E. Nichol ◽  
Wing Yee Fung ◽  
Ka-se Lam ◽  
Man Sing Wong
Keyword(s):  
Urban Heat Island ◽  
Air Temperature ◽  
Satellite Images ◽  
Heat Island ◽  
Urban Heat

scholarly journals Moderation of Summertime Heat Island Phenomena via Modification of the Urban Form in the Tokyo Metropolitan Area

2014 ◽  
Vol 53 (8) ◽  
pp. 1886-1900 ◽  
Author(s):  
Sachiho A. Adachi ◽  
Fujio Kimura ◽  
Hiroyuki Kusaka ◽  
Michael G. Duda ◽  
Yoshiki Yamagata ◽  
...  
Keyword(s):  
Urban Heat Island ◽  
Air Temperature ◽  
Metropolitan Area ◽  
Urban Form ◽  
Surface Air Temperature ◽  
Heat Island ◽  
Compact City ◽  
Tokyo Metropolitan Area ◽  
Island Effect ◽  
Urban Heat

AbstractThis study investigated the moderation of the urban heat island via changes in the urban form in the Tokyo metropolitan area (TMA). Two urban scenarios with the same population as that of the current urban form were used for sensitivity experiments: the dispersed-city and compact-city scenarios. Numerical experiments using the two urban scenarios as well as an experiment using the current urban form were conducted using a regional climate model coupled with a single-layer urban canopy model. The averaged nighttime surface air temperature in TMA increased by ~0.34°C in the dispersed-city scenario and decreased by ~0.1°C in the compact-city scenario. Therefore, the compact-city scenario had significant potential for moderating the mean areal heat-island effect in the entire TMA. Alternatively, in the central part of the TMA, these two urban-form scenarios produced opposite effects on the surface air temperature; that is, severe thermal conditions worsened further in the compact-city scenario because of the denser population. This result suggests that the compact-city form is not always appropriate for moderation of the urban-heat-island effect. This scenario would need to combine with other mitigation strategies, such as the additional greening of urban areas, especially in the central area. This study suggests that it is important to design a plan to adapt to higher urban temperatures, which are likely to ensue from future global warming and the urban heat island, from several perspectives; that is, designs should take into account not only climatological aspects but also impacts on urban inhabitants.

scholarly journals Dense Network Observations of the Twin Cities Canopy-Layer Urban Heat Island

2015 ◽  
Vol 54 (9) ◽  
pp. 1899-1917 ◽  
Author(s):  
Brian V. Smoliak ◽  
Peter K. Snyder ◽  
Tracy E. Twine ◽  
Phillip M. Mykleby ◽  
William F. Hertel
Keyword(s):  
Spatial Structure ◽  
Urban Heat Island ◽  
Surface Air Temperature ◽  
Twin Cities ◽  
Daily Maximum ◽  
Heat Island ◽  
Canopy Layer ◽  
Local Climate ◽  
Local Climate Zones ◽  
Urban Heat

AbstractData from a dense urban meteorological network (UMN) are analyzed, revealing the spatial heterogeneity and temporal variability of the Twin Cities (Minneapolis–St. Paul, Minnesota) canopy-layer urban heat island (UHI). Data from individual sensors represent surface air temperature (SAT) across a variety of local climate zones within a 5000-km2 area and span the 3-yr period from 1 August 2011 to 1 August 2014. Irregularly spaced data are interpolated to a uniform 1 km × 1 km grid using two statistical methods: 1) kriging and 2) cokriging with impervious surface area data. The cokriged SAT field exhibits lower bias and lower RMSE than does the kriged SAT field when evaluated against an independent set of observations. Maps, time series, and statistics that are based on the cokriged field are presented to describe the spatial structure and magnitude of the Twin Cities metropolitan area (TCMA) UHI on hourly, daily, and seasonal time scales. The average diurnal variation of the TCMA UHI exhibits distinct seasonal modulation wherein the daily maximum occurs by night during summer and by day during winter. Daily variations in the UHI magnitude are linked to changes in weather patterns. Seasonal variations in the UHI magnitude are discussed in terms of land–atmosphere interactions. To the extent that they more fully resolve the spatial structure of the UHI, dense UMNs are advantageous relative to limited collections of existing urban meteorological observations. Dense UMNs are thus capable of providing valuable information for UHI monitoring and for implementing and evaluating UHI mitigation efforts.

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