scholarly journals Urban Canyon in the CBD of Rio de Janeiro (Brazil): Avenida Rio Branco during Summer

2021 ◽  
Author(s):  
Lidiane de Oliveira Lemos ◽  
Antonio Carlos Oscar Júnior ◽  
Francisco Mendonça
Keyword(s):  
Land Surface ◽  
Rio De Janeiro ◽  
Field Experiments ◽  
Atmospheric Stability ◽  
Urban Morphology ◽  
Urban Canyon ◽  
Synoptic Situation ◽  
Canopy Layer ◽  
Heat Islands ◽  
Atmospheric Instability

This study aims to evaluate the land surface temperature (LST) and the thermal characteristics of the Urban Canopy Layer (UCL) of the urban canyon in Avenida Rio Branco in the Central Business District (CBD) of Rio de Janeiro during summer. In order to conduct this evaluation, two methods were employed: 1) summer LST estimation from the last decade (2011-2020); 2) field survey using nine sampling points — seven along two mobile transects, one fixed point, and one vertical measurement point, which required the use of a RPA (Remotely Piloted Aircraft). Three categories of analysis were established based on the prevailing synoptic situations: stability, instability, and post-instability. The CBD showed extensive areas with surface heat islands, in which temperatures were higher than 38.9°C; the areas with milder LSTs were Campo do Santana, Avenida Rio Branco, and one of the Mixed-Use Zones (Praça Mauá). The shadows of the buildings gave rise to niches of lower LSTs on Avenida Rio Branco; however, the satellite data and the data collected during the ten days of field experiments diverged. In situ data revealed that the urban morphology of Avenida Rio Branco is susceptible to the formation of heat islands, presenting heat islands of very strong magnitude (over 6.1°C) in atmospheric stability, strong magnitude (4.1-6.0°C) in atmospheric instability, and moderate magnitude (2.1°C-4.0°C) in post-atmospheric instability. Despite the synoptic situation, thermal cores were concentrated at 1 pm. The intersection between Avenida Rio Branco, Rua do Ouvidor, and Praça Mauá stored most of the solar energy received during the day. Finally, vertical analysis demonstrated the formation of a thermal inversion on the night of the highest mean air temperature (29.5°C), probably, due to the roughness and number of buildings in the urban canyon.

scholarly journals Urban Canyon in the CBD of Rio de Janeiro (Brazil): Thermal Profile of Avenida Rio Branco during Summer

2021 ◽  
Author(s):  
Lidiane de Oliveira Lemos ◽  
Antonio Carlos Oscar-Júnior ◽  
Francisco Mendonça
Keyword(s):  
Rio De Janeiro ◽  
Field Survey ◽  
Atmospheric Stability ◽  
Urban Morphology ◽  
Urban Canyon ◽  
Synoptic Situation ◽  
Landsat 8 ◽  
Observation Data ◽  
Heat Islands ◽  
Atmospheric Instability

This study aims to evaluate the land surface temperature (LST) and the thermal characteristics of the Urban Canopy Layer (UCL) of the urban canyon in Avenida Rio Branco in the Central Business District (CBD) of Rio de Janeiro during summer. In order to conduct this evaluation, two methods were employed: 1) TIRS Landsat-8 sensor for data selection and processing (latest generation, 2011-2020); ; 2) field survey using nine sampling points — seven along two mobile transects, one fixed point, and one vertical measurement point, which required the use of a RPA (Remotely Piloted Aircraft). Three categories of analysis were established for the field survey based on the prevailing synoptic situations: stability, instability, and post-instability. The CBD is characterized by extensive areas with surface heat islands, in which temperatures were higher than 38.9°C; the areas with milder LSTs were Campo do Santana, Avenida Rio Branco, and one of the Mixed-Use Zones (Praça Mauá). With respect to Rio Branco Avenue, the LST niches of lowest elevation were derived through building shadowing; however, the orbital data diverged from the observation data of the ten field-study days. In situ data revealed that the characteristics urban morphology of Avenida Rio Branco is susceptible to the formation of heat islands, presenting heat islands of very strong magnitude (over 6.1°C) in atmospheric stability, strong magnitude (4.1-6.0°C) in atmospheric instability, and moderate magnitude (2.1°C-4.0°C) in post-atmospheric instability. Despite the synoptic situation, thermal cores were concentrated at 1 pm. The intersection between Avenida Rio Branco, Rua do Ouvidor, and Praça Mauá stored most of the solar energy received during the day due to the greater sky obstruction caused by the verticalization. Finally, vertical analysis demonstrated the formation of a thermal inversion on the night of the highest mean air temperature (29.5°C), probably, due to the roughness and number of buildings in the urban canyon.

scholarly journals Urban Canyon in the CBD of Rio de Janeiro (Brazil): Thermal Profile of Avenida Rio Branco during Summer

Atmosphere ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 27
Author(s):  
Lidiane de Oliveira Lemos ◽  
Antonio Carlos Oscar Júnior ◽  
Francisco Mendonça
Keyword(s):  
Rio De Janeiro ◽  
Field Survey ◽  
Atmospheric Stability ◽  
Urban Morphology ◽  
Urban Canyon ◽  
Synoptic Situation ◽  
Landsat 8 ◽  
Observation Data ◽  
Heat Islands ◽  
Atmospheric Instability

This study aims to evaluate the thermal field of the central business district (CBD) of Rio de Janeiro during summer from land surface temperature (LST) and the thermal characteristics of the urban canopy layer (UCL) of the urban canyon in Avenida Rio Branco. In order to conduct this evaluation, two methods were employed: (1) TIRS Landsat-8 sensor for data selection and processing (latest generation, 2011–2020); (2) a field survey using nine sampling points—seven along two mobile transects, one fixed point, and one vertical measurement point, which required the use of an RPA (remotely piloted aircraft). Three categories of analysis were established for the field survey based on the prevailing synoptic situations: stability, instability, and post-instability. The CBD is characterized by extensive areas with surface heat islands, in which temperatures were higher than 38.9 °C; the areas with milder LSTs were Campo do Santana, Avenida Rio Branco, and one of the mixed-use zones (Praça Mauá). With respect to Rio Branco Avenue, the LST niches of lowest elevation were derived through building shadowing; however, due to the nature of the data, the orbital data diverged from the observation data of the 10 field-study days. In situ data revealed that the characteristics urban morphology of Avenida Rio Branco, by contrast with the LST result, is susceptible to the formation of atmospheric heat islands, presenting heat islands of very strong magnitude (over 6.1 °C) in atmospheric stability, strong magnitude (4.1–6.0 °C) in atmospheric instability, and moderate magnitude (2.1–4.0 °C) in post-atmospheric instability. Despite the synoptic situation, thermal cores were concentrated at 1 p.m. The intersection between Avenida Rio Branco, Rua do Ouvidor, and Praça Mauá stored most of the solar energy received during the day due to the greater sky obstruction caused by the verticalization. Finally, vertical analysis demonstrated the formation of a thermal inversion on the night of the highest mean air temperature (29.5 °C), probably due to the roughness and number of buildings in the urban canyon.

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.

scholarly journals Influence of Land Cover and Soil Moisture on the Horizontal Distribution of Sensible and Latent Heat Fluxes in Southeast Kansas during IHOP_2002 and CASES-97

2007 ◽  
Vol 8 (1) ◽  
pp. 68-87 ◽  
Author(s):  
Margaret A. LeMone ◽  
Fei Chen ◽  
Joseph G. Alfieri ◽  
Mukul Tewari ◽  
Bart Geerts ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Latent Heat ◽  
Land Surface ◽  
Field Experiments ◽  
Time Of Day ◽  
Horizontal Distribution ◽  
Heat Fluxes ◽  
Surface Model ◽  
Green Vegetation ◽  
The Impact

Abstract Analyses of daytime fair-weather aircraft and surface-flux tower data from the May–June 2002 International H2O Project (IHOP_2002) and the April–May 1997 Cooperative Atmosphere Surface Exchange Study (CASES-97) are used to document the role of vegetation, soil moisture, and terrain in determining the horizontal variability of latent heat LE and sensible heat H along a 46-km flight track in southeast Kansas. Combining the two field experiments clearly reveals the strong influence of vegetation cover, with H maxima over sparse/dormant vegetation, and H minima over green vegetation; and, to a lesser extent, LE maxima over green vegetation, and LE minima over sparse/dormant vegetation. If the small number of cases is producing the correct trend, other effects of vegetation and the impact of soil moisture emerge through examining the slope ΔxyLE/ΔxyH for the best-fit straight line for plots of time-averaged LE as a function of time-averaged H over the area. Based on the surface energy balance, H + LE = Rnet − Gsfc, where Rnet is the net radiation and Gsfc is the flux into the soil; Rnet − Gsfc ∼ constant over the area implies an approximately −1 slope. Right after rainfall, H and LE vary too little horizontally to define a slope. After sufficient drying to produce enough horizontal variation to define a slope, a steep (∼−2) slope emerges. The slope becomes shallower and better defined with time as H and LE horizontal variability increases. Similarly, the slope becomes more negative with moister soils. In addition, the slope can change with time of day due to phase differences in H and LE. These trends are based on land surface model (LSM) runs and observations collected under nearly clear skies; the vegetation is unstressed for the days examined. LSM runs suggest terrain may also play a role, but observational support is weak.

scholarly journals Assessment of the Effect of Neyshabur Green Spatial Configuration on the Temperature of Land Surface and Heat Islands

2017 ◽  
Vol 07 (09) ◽  
pp. 554-567 ◽  
Author(s):  
Elham Jafari ◽  
Hadi Soltanifard ◽  
Kazem Aliabadi ◽  
Hadi Karachi
Keyword(s):  
Land Surface ◽  
Spatial Configuration ◽  
Heat Islands

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 An overview of the LOess Plateau mesa region land surface process field EXperiment series (LOPEXs)

2009 ◽  
Vol 13 (6) ◽  
pp. 945-951 ◽  
Author(s):  
J. Wen ◽  
L. Wang ◽  
Z. G. Wei
Keyword(s):  
Loess Plateau ◽  
Land Surface ◽  
Field Experiments ◽  
Chinese Loess Plateau ◽  
Data Sets ◽  
Surface Process ◽  
Land Surface Process ◽  
Chinese Loess ◽  
Series Of Experiments ◽  
The Chinese Loess Plateau

Abstract. A series of land surface process field experiments were carried out in a mesa region of the Chinese Loess Plateau in each of the years from 2004 to 2008 (acronymized as LOPEX04, LOPEX08, etc.). The general objectives of this series of experiments, observational data sets, and preliminary science results are presented in this paper. The prospective research topics by using the LOPEXs data sets are discussed.

scholarly journals Calculating the turbulent fluxes in the atmospheric surface layer with neural networks

2018 ◽  
Author(s):  
Lukas Hubert Leufen ◽  
Gerd Schädler
Keyword(s):  
Land Surface ◽  
Field Experiments ◽  
Climate Models ◽  
Similarity Theory ◽  
Turbulent Fluxes ◽  
Global Climate Models ◽  
Surface Model ◽  
Time Step ◽  
One Dimensional ◽  
Stability Functions

Abstract. The turbulent fluxes of momentum, heat and water vapour link the Earth's surface with the atmosphere. The correct modelling of the flux interactions between these two systems with very different time scales is therefore vital for climate (resp. Earth system) models. Conventionally, these fluxes are modelled using Monin–Obukhov similarity theory (MOST) with stability functions derived from a small number of field experiments; this results in a range of formulations of these functions and thus also in the flux calculations; furthermore, the underlying equations are non-linear and have to be solved iteratively at each time step of the model. For these reasons, we tried here a different approach, namely using an artificial neural network (ANN) to calculate the fluxes resp. the scaling quantities u* and θ*, thus avoiding explicit formulas for the stability functions. The network was trained and validated with multi-year datasets from seven grassland, forest and wetland sites worldwide using the Broyden–Fletcher–Goldfarb–Shanno (BFGS) quasi-Newton backpropagation algorithm and six-fold cross validation. Extensive sensitivity tests showed that an ANN with six input variables and one hidden layer gave results comparable to (and in some cases even slightly better than) the standard method. Similar satisfying results were obtained when the ANN routine was implemented in a one-dimensional stand alone land surface model (LSM), opening the way to implementation in three-dimensional climate models. In case of the one-dimensional LSM, no CPU time was saved when using the ANN version, since the small time step of the standard version required only one iteration in most cases. This could be different in models with longer time steps, e.g. global climate models.

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