scholarly journals Efficient urban canopy parametrization for atmospheric modelling: description and application with the COSMO-CLM model (version 5.0_clm6) for a Belgian Summer

2016 ◽  
Author(s):  
Hendrik Wouters ◽  
Matthias Demuzere ◽  
Ulrich Blahak ◽  
Krzysztof Fortuniak ◽  
Bino Maiheu ◽  
...  
Keyword(s):  
Land Surface ◽  
Urban Canopy ◽  
Urban Land ◽  
Urban Heat Islands ◽  
Heat Islands ◽  
Atmospheric Modelling ◽  
Urban Heat ◽  
Urban Canopy Parametrization ◽  
Surface Scheme ◽  
Bulk Parameters

Abstract. This paper presents the Semi-empirical URban-canopY parametrization SURY, which bridges the gap between bulk urban land-surface schemes and explicit-canyon schemes. Based on detailed observational studies, modelling experiments and available parameter inventories, it offers a robust translation of urban canopy parameters containing the three-dimensional information into bulk parameters. It is extremely suitable for an intrinsic representation of canopy-dependent urban physics in existing bulk urban land-surface schemes of atmospheric models. At the same time, it delivers high efficiency in terms of computational cost for long-term climate modelling and numerical weather prediction. SURY enables versatility and consistency in choosing between the urban canopy parameters from bottom-up inventories and bulk parameters from top-down estimates. SURY is tested for Belgium at 2.8 km resolution with the COSMO-CLM model (version 5.0_clm6) that is extended with the bulk urban land-surface scheme TERRA_URB (version 2). The model reproduces very well the urban heat islands observed from in-situ urban-climate observations, satellite imagery and tower observations, which is in contrast to the original COSMO-CLM model without an urban land-surface scheme. As an application of SURY, the sensitivity of the COSMO-CLM model in terms of land-surface temperatures, air temperatures and associated urban heat islands is quantified for the urban canopy parameter ranges from the Local Climate Zones classification system. On the one hand, their city-scale effect shows that additional urban canopy information has potential for improving regional atmospheric modelling. On the other hand, the model performance and its sensitivity to the different urban canopy parameters largely depend on the temperature quantity considered. Such an ambiguity demonstrates that a multi-variable model evaluation is a requirement for improving and comparing online urban atmospheric modelling strategies.

scholarly journals The efficient urban canopy dependency parametrization (SURY) v1.0 for atmospheric modelling: description and application with the COSMO-CLM model for a Belgian summer

2016 ◽  
Vol 9 (9) ◽  
pp. 3027-3054 ◽  
Author(s):  
Hendrik Wouters ◽  
Matthias Demuzere ◽  
Ulrich Blahak ◽  
Krzysztof Fortuniak ◽  
Bino Maiheu ◽  
...  
Keyword(s):  
Land Surface ◽  
Urban Canopy ◽  
Urban Land ◽  
Urban Heat Islands ◽  
Land Surface Scheme ◽  
Heat Islands ◽  
Atmospheric Modelling ◽  
Urban Heat ◽  
Surface Scheme ◽  
Bulk Parameters

Abstract. This paper presents the Semi-empirical URban canopY parametrization (SURY) v1.0, which bridges the gap between bulk urban land-surface schemes and explicit-canyon schemes. Based on detailed observational studies, modelling experiments and available parameter inventories, it offers a robust translation of urban canopy parameters – containing the three-dimensional information – into bulk parameters. As a result, it brings canopy-dependent urban physics to existing bulk urban land-surface schemes of atmospheric models. At the same time, SURY preserves a low computational cost of bulk schemes for efficient numerical weather prediction and climate modelling at the convection-permitting scales. It offers versatility and consistency for employing both urban canopy parameters from bottom-up inventories and bulk parameters from top-down estimates. SURY is tested for Belgium at 2.8 km resolution with the COSMO-CLM model (v5.0_clm6) that is extended with the bulk urban land-surface scheme TERRA_URB (v2.0). The model reproduces very well the urban heat islands observed from in situ urban-climate observations, satellite imagery and tower observations, which is in contrast to the original COSMO-CLM model without an urban land-surface scheme. As an application of SURY, the sensitivity of atmospheric modelling with the COSMO-CLM model is addressed for the urban canopy parameter ranges from the local climate zones of http://WUDAPT.org. City-scale effects are found in modelling the land-surface temperatures, air temperatures and associated urban heat islands. Recommendations are formulated for more precise urban atmospheric modelling at the convection-permitting scales. It is concluded that urban canopy parametrizations including SURY, combined with the deployment of the WUDAPT urban database platform and advancements in atmospheric modelling systems, are essential.

scholarly journals Birmingham’s air and surface urban heat islands associated with Lamb weather types and cloudless anticyclonic conditions

2014 ◽  
Vol 38 (4) ◽  
pp. 431-447 ◽  
Author(s):  
Fang Zhang ◽  
Xiaoming Cai ◽  
John E. Thornes
Keyword(s):  
Spatial Patterns ◽  
Land Surface ◽  
Urban Canopy ◽  
Urban Heat Islands ◽  
City Centre ◽  
Canopy Layer ◽  
Weather Types ◽  
Heat Islands ◽  
Urban Heat ◽  
The Difference

This study investigates the characteristics of the air and surface urban heat islands (aUHI and sUHI) of Birmingham in relation to Lamb weather types (LWTs) over the period 2002–2007, with a particular focus on cloudless anticyclonic conditions. Ground-based MIDAS air temperatures within the urban canopy layer at the urban Edgbaston and rural Shawbury weather stations were used to derive the aUHI intensity (aUHII). Satellite-derived MODIS/Aqua land surface temperatures (LST) under cloudless conditions were used to derive the spatial patterns of the sUHI as well as the sUHI intensity (sUHII). Using Jenkinson’s objective daily synoptic indices, a combined subset of 11 LWTs were examined for their association with the nocturnal aUHI. Over the study period, the most frequently occurring LWT, ‘anticyclonic’ (21.1%), gives a strongest mean/maximum nocturnal aUHII of 2.5°C/7°C (391 nights) and the largest proportion of nocturnal heat island events of 65.2%. The spatial patterns of nocturnal sUHI for each LWT were also assessed, and the results demonstrate Birmingham’s urban warming of up to 4.16°C (48 clear nights) in the city centre under cloudless anticyclonic conditions. The scatter plot of nocturnal aUHII and sUHII for the 48 nights demonstrates a linear relationship. We also developed a simple analytical model that links the slope of the aUHII–sUHII relationship to the difference of ‘built-up’ area fraction between the urban pixel and the rural pixel in satellite imagery of land cover. This partially explains the physical basis behind the relationship. These findings of the aUHII–sUHII relationship may lead to the future development of a generic methodology of deriving the spatial patterns of aUHI from satellite measurements.

MONITORING THERMAL POLLUTION SOURCES IN VORONEZH (RUSSIA) USING REMOTE SENSING DATA

2021 ◽  
pp. 54-65
Author(s):  
Дмитрий Владимирович Сарычев ◽  
Ирина Владимировна Попова ◽  
Семен Александрович Куролап
Keyword(s):  
Remote Sensing ◽  
Land Surface ◽  
Remote Sensing Data ◽  
Urban Heat Islands ◽  
Landsat 8 ◽  
Heat Islands ◽  
Land Surface Temperatures ◽  
Treatment Facilities ◽  
Urban Heat ◽  
Industrial Zones

Рассмотрены вопросы мониторинга теплового загрязнения окружающей среды в городах. Представлена методика отбора спектрозональных спутниковых снимков, их обработки и интерпретации полученных результатов. Для оценки городского острова тепла были использованы снимки с космического аппарата Landsat 8 TIRS. На их основе построены карты пространственной структуры острова тепла города Воронежа за летний и зимний периоды. Определены тепловые аномалии и выявлено 11 основных техногенных источников теплового загрязнения в г. Воронеже, установлена их принадлежность к промышленным зонам предприятий, а также к очистным гидротехническим сооружениям. Поверхностные температуры данных источников в среднем были выше фоновых температур приблизительно на 6° зимой и на 15,5° С летом. Синхронно со спутниковой съемкой были проведены наземные контрольные тепловизионные измерения температур основных подстилающих поверхностей в г. Воронеже. Полученные данные показали высокую сходимость космических и наземных измерений, на основании чего сделан вывод о надежности используемых данных дистанционного зондирования Земли в мониторинговых наблюдениях теплового загрязнения городской среды. Результаты работ могут найти применение в городском планировании и медицинской экологии. The study deals with the remote sensing and monitoring of urban heat islands. We present a methodology of multispectral satellite imagery selection and processing. The study bases on the freely available Landsat 8 TIRS data. We used multitemporal thermal band combinations to make maps of the urban heat island of Voronezh (Russia) during summer and winter periods. That let us identify 11 artificial sources of heat in Voronezh. All of them turned out to be allocated within industrial zones of plants and water treatment facilities. Land surface temperatures (LST) of these sources were approximately 6° and 15.5° C above the background temperatures in winter and summer, respectively. To prove the remotely sensed temperatures we conducted ground control measurements of LST of different surface types at the satellite revisit moments. Our results showed a significant correlation between the satellite and ground-based measurements, so the maps we produced in this study should be robust. They are of use in urban planning and medical ecology studies.

scholarly journals Urban heat island: Aerodynamics or imperviousness?

2019 ◽  
Vol 5 (4) ◽  
pp. eaau4299 ◽  
Author(s):  
Dan Li ◽  
Weilin Liao ◽  
Angela J. Rigden ◽  
Xiaoping Liu ◽  
Dagang Wang ◽  
...  
Keyword(s):  
Green Infrastructure ◽  
Rural Areas ◽  
Land Surface ◽  
Urban Heat Islands ◽  
Lower Atmosphere ◽  
Geographic Variations ◽  
Heat Islands ◽  
Urban Heat ◽  
The Difference ◽  
Urban And Rural Areas

More than half of the world’s population now live in cities, which are known to be heat islands. While daytime urban heat islands (UHIs) are traditionally thought to be the consequence of less evaporative cooling in cities, recent work sparks new debate, showing that geographic variations of daytime UHI intensity were largely explained by variations in the efficiency with which urban and rural areas convect heat from the land surface to the lower atmosphere. Here, we reconcile this debate by demonstrating that the difference between the recent finding and the traditional paradigm can be explained by the difference in the attribution methods. Using a new attribution method, we find that spatial variations of daytime UHI intensity are more controlled by variations in the capacity of urban and rural areas to evaporate water, suggesting that strategies enhancing the evaporation capability such as green infrastructure are effective ways to mitigate urban heat.

scholarly journals Effect of Land Cover Fractions on Changes in Surface Urban Heat Islands Using Landsat Time-Series Images

2019 ◽  
Vol 16 (6) ◽  
pp. 971 ◽  
Author(s):  
Tao Chen ◽  
Anchang Sun ◽  
Ruiqing Niu
Keyword(s):  
Land Cover ◽  
Urban Heat Island ◽  
Land Surface ◽  
Urban Heat Islands ◽  
Urban Heat Island Intensity ◽  
Heat Island ◽  
Impervious Surfaces ◽  
Heat Islands ◽  
Urban Heat ◽  
Surface Urban Heat Island

Man-made materials now cover a dominant proportion of urban areas, and such conditions not only change the absorption of solar radiation, but also the allocation of the solar radiation and cause the surface urban heat island effect, which is considered a serious problem associated with the deterioration of urban environments. Although numerous studies have been performed on surface urban heat islands, only a few have focused on the effect of land cover changes on surface urban heat islands over a long time period. Using six Landsat image scenes of the Metropolitan Development Area of Wuhan, our experiment (1) applied a mapping method for normalized land surface temperatures with three land cover fractions, which were impervious surfaces, non-chlorophyllous vegetation and soil and vegetation fractions, and (2) performed a fitting analysis of fierce change areas in the surface urban heat island intensity based on a time trajectory. Thematic thermal maps were drawn to analyze the distribution of and variations in the surface urban heat island in the study area. A Multiple Endmember Spectral Mixture Analysis was used to extract the land cover fraction information. Then, six ternary triangle contour graphics were drawn based on the land surface temperature and land cover fraction information. A time trajectory was created to summarize the changing characteristics of the surface urban heat island intensity. A fitting analysis was conducted for areas showing fierce changes in the urban heat intensity. Our results revealed that impervious surfaces had the largest impacts on surface urban heat island intensity, followed by the non-chlorophyllous vegetation and soil fraction. Moreover, the results indicated that the vegetation fraction can alleviate the occurrence of surface urban heat islands. These results reveal the impact of the land cover fractions on surface urban heat islands. Urban expansion generates impervious artificial objects that replace pervious natural objects, which causes an increase in land surface temperature and results in a surface urban heat island.

scholarly journals Night Thermal Unmixing for the Study of Microscale Surface Urban Heat Islands with TRISHNA-Like Data

2019 ◽  
Vol 11 (12) ◽  
pp. 1449 ◽  
Author(s):  
Carlos Granero-Belinchon ◽  
Aurelie Michel ◽  
Jean-Pierre Lagouarde ◽  
Jose A. Sobrino ◽  
Xavier Briottet
Keyword(s):  
Surface Temperature ◽  
Land Surface ◽  
Image Resolution ◽  
Urban Heat Islands ◽  
Land Uses ◽  
Regression Kriging ◽  
Heat Islands ◽  
Urban Heat ◽  
Land Covers ◽  
The City

Urban Heat Islands (UHIs) at the surface and canopy levels are major issues in urban planification and development. For this reason, the comprehension and quantification of the influence that the different land-uses/land-covers have on UHIs is of particular importance. In order to perform a detailed thermal characterisation of the city, measures covering the whole scenario (city and surroundings) and with a recurrent revisit are needed. In addition, a resolution of tens of meters is needed to characterise the urban heterogeneities. Spaceborne remote sensing meets the first and the second requirements but the Land Surface Temperature (LST) resolutions remain too rough compared to the urban object scale. Thermal unmixing techniques have been developed in recent years, allowing LST images during day at the desired scales. However, while LST gives information of surface urban heat islands (SUHIs), canopy UHIs and SUHIs are more correlated during the night, hence the development of thermal unmixing methods for night LSTs is necessary. This article proposes to adapt four empirical unmixing methods of the literature, Disaggregation of radiometric surface Temperature (DisTrad), High-resolution Urban Thermal Sharpener (HUTS), Area-To-Point Regression Kriging (ATPRK), and Adaptive Area-To-Point Regression Kriging (AATPRK), to unmix night LSTs. These methods are based on given relationships between LST and reflective indices, and on invariance hypotheses of these relationships across resolutions. Then, a comparative study of the performances of the different techniques is carried out on TRISHNA synthesized images of Madrid. Since TRISHNA is a mission in preparation, the synthesis of the images has been done according to the planned specification of the satellite and from initial Aircraft Hyperspectral Scanner (AHS) data of the city obtained during the DESIREX 2008 capaign. Thus, the coarse initial resolution is 60 m and the finer post-unmixing one is 20 m. In this article, we show that: (1) AATPRK is the most performant unmixing technique when applied on night LST, with the other three techniques being undesirable for night applications at TRISHNA resolutions. This can be explained by the local application of AATPRK. (2) ATPRK and DisTrad do not improve significantly the LST image resolution. (3) HUTS, which depends on albedo measures, misestimates the LST, leading to the worst temperature unmixing. (4) The two main factors explaining the obtained performances are the local/global application of the method and the reflective indices used in the LST-index relationship.

scholarly journals Inclusion of vegetation in the Town Energy Balance model for modeling urban green areas

2012 ◽  
Vol 5 (2) ◽  
pp. 1295-1340 ◽  
Author(s):  
A. Lemonsu ◽  
V. Masson ◽  
L. Shashua-Bar ◽  
E. Erell ◽  
D. Pearlmutter
Keyword(s):  
Global Climate ◽  
A Priori ◽  
Urban Canopy ◽  
Bare Soil ◽  
Urban Heat Islands ◽  
Balance Model ◽  
Local Climate ◽  
Heat Islands ◽  
Planning Strategy ◽  
Urban Heat

Abstract. Cities impact both local climate, through urban heat islands, and global climate, because they are an area of heavy greenhouse gas release into the atmosphere due to heating, air conditioning and traffic. Including more vegetation into cities is a planning strategy having possible positive impacts for both concerns. Improving vegetation representation into urban models will allow to address more accurately these questions. This paper presents an improvement of the TEB urban canopy model. Vegetation is directly included inside the canyon, allowing shadowing of grass by buildings, better representation of urban canopy form, and, a priori, a more accurate simulation of canyon air microclimate. The development is performed so that any vegetation model can be used to represent the vegetation part. Here the ISBA model is used. The model results are compared to microclimatic and evaporation measurements performed in small courtyards in a very arid region of Israel. Two experimental landscaping strategies – bare soil or irrigated grass in the courtyard – are observed and simulated. The new version of the model with integrated vegetation performs better than if vegetation is treated outside the canyon. Surface temperatures are closer to the observations, especially at night when radiative trapping is important. The integrated vegetation version simulates a more humid air inside the canyon. The microclimatic quantities are better simulated with this new version. This opens opportunities to study with better accuracy the urban microclimate, down to the micro (or canyon) scale.

scholarly journals Reducing urban heat islands and improving the thermal comfort of residents: A nature-based solution

2021 ◽  
pp. 65-75
Author(s):  
Tomislav Đorđević
Keyword(s):  
Spectral Analysis ◽  
Green Infrastructure ◽  
Land Surface ◽  
Complex Geometry ◽  
Urban Heat Islands ◽  
Heat Islands ◽  
Pollution Levels ◽  
Radiation Distribution ◽  
Urban Heat

The benefits of urban blue-green infrastructures are well known: they intercept airborne three-atom particles, thus reducing pollution levels; and they provide shade and cooling by means of evapotranspiration. The focus of this paper is to demonstrate methods such as remote sensing and multi-spectral analysis, which can be a very useful addition to the quantification of blue-green infrastructures for cooling and shading, especially in the highly complex geometry of city blocks. The basic aim of this research is to attempt to reduce urban heat islands and in this way to indirectly increase the comfort of living. A cause/ effect relationship between the envelope of built up structures and the solar radiation distribution on the environment was established by means of multi-spectral analysis, and an estimation was made concerning the lack of vegetation on a specific parcel/block (an important tool for urban planners). This state-of-the-art methodology was applied to the optimized prediction concept of vegetation resources. Now it is possible to create a model that will incorporate this newly-added urban vegetation into urban plans, depending on the evaporation potential that will affect the microclimate of the urban area. Such natural cooling can be measured and adapted and hence aimed at a potential decrease in temperature in areas with UHI emissions. As a case study, part of a seacoast urban block (Abu Dhabi UE,) was analysed with and without a street treeline and green façades and roofs. It was concluded that green infrastructure reduced the land surface temperature by up to 4.5˚C.

scholarly journals GEOSPATIAL ASSESSMENT AND MODELING OF URBAN HEAT ISLANDS IN QUEZON CITY, PHILIPPINES USING OLS AND GEOGRAPHICALLY WEIGHTED REGRESSION

2019 ◽  
Vol XLII-4/W16 ◽  
pp. 85-92
Author(s):  
C. A. Alcantara ◽  
J. D. Escoto ◽  
A. C. Blanco ◽  
A. B. Baloloy ◽  
J. A. Santos ◽  
...  
Keyword(s):  
Geographically Weighted Regression ◽  
Land Surface ◽  
Google Earth ◽  
Urban Heat Islands ◽  
Weighted Regression ◽  
View Factor ◽  
Landsat 8 ◽  
Quezon City ◽  
Heat Islands ◽  
Urban Heat

Abstract. Urbanization has played an important part in the development of the society, yet it is accompanied by environmental concerns including the increase of local temperature compared to its immediate surroundings. The latter is known as Urban Heat Islands (UHI). This research aims to model UHI in Quezon City based on Land Surface Temperature (LST) estimated from Landsat 8 data. Geospatial processing and analyses were performed using Google Earth Engine, ArcGIS, GeoDa, and SAGA GIS. Based on Urban Thermal Field Variance Index (UTFVI) and the normalized mean per barangay (village), areas with strong UHI intensities were mapped and characterized. high intensity UHIs are observed mostly in areas with high Normalized Difference Built-up Index (NDBI) like the residential regions while the weak intensity UHIs are noticed in areas with high Normalized Difference Vegetation Index (NDVI) near the La Mesa Reservoir. In the OLS regression model, around 69% of LST variability is explained by Surface Albedo (SA), Sky View Factor (SVF), Surface Area to Volume Ratio (SVR), Solar Radiation (SR), NDBI and NDVI. OLS yield relatively high residuals (RMSE = 1.67) and the residuals are not normally distributed. Since LST is non-stationary, Geographically Weighted Regression (GWR) regression was conducted, proving normally and randomly distributed residuals (average RMSE = 0.26).

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