Estimation of the urban heat island in the Metropolitan Area of Rio de Janeiro - Brazil

Lucena, Andrews José de; Peres, Leonardo F.; Filho, Otto Corrêa Rotunno; França, José Ricardo de Almeida

doi:10.1109/jurse.2015.7120540

Cited by 4 publications

(5 citation statements)

References 13 publications

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“…T (RH) mean differences as high as 5 • C (30%) between, e.g., the sites RD/RI and FC/XE could be related with the occurrences of heat islands that have important effects in human weather comfortability and the formation of extreme weather events contributing to significant variability in the T m , commonly used to estimate IWV. The spatiotemporal variabilities of T between the sites analyzed in this work corroborate with the observations of Lucena et al [26][27][28] that mapped urban, suburban, and rural heat islands in the MARJ. These studies indicated that the temperatures of the surface and the air near the surface in the heat islands were much higher than those in the surrounding (vegetated or near the coast) areas and were related with extreme rainfall events.…”

Section: Discussionsupporting

confidence: 91%

“…Spatial differences were more evident in the daytime intervals of 09:30-10:45 and 12:45-14:30 LT, where the highest mean values of IWV were located along the oceanic coast toward the upslopes of the mountain ranges. This approximate south-north configuration of the mean IWV variation can be explained by the occurrence of daytime convection influenced by land heating, such as the heat islands identified by Lucena et al [26][27][28], and the convergence of the southerly and easterly sea breezes that cause maxima rainfall from the coastline to the upslopes of the mountain ranges during the late afternoon to nocturnal hours, as observed by Dereczynski et al [24] and Mota and Song [25].…”

Section: Discussionmentioning

confidence: 75%

“…The composites of GNSS IWV with rainfall in Rio de Janeiro state observed by Mota and Song [25] showed a high rate of change of IWV related with the occurrences of extreme rainfall events. Lucena et al [26][27][28] mapped heat islands in the urban, suburban, and rural sectors of the MARJ. Those phenomena have been associated with high records of surface temperature and near surface air temperature (T) that favor the occurrences of extreme rainfall and flooding events that affect MARJ [24,29,30].…”

Section: Introductionmentioning

confidence: 99%

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Assessment of Integrated Water Vapor Estimates from the iGMAS and the Brazilian Network GNSS Ground-Based Receivers in Rio de Janeiro

2019

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There is pressing demand for knowledge improvement of the integrated water vapor (IWV) distribution in regions affected by heat islands that are associated with extreme rainfall events such as in the metropolitan area of Rio de Janeiro (MARJ). This work assessed the suitability and evaluation of the spatiotemporal distribution of Global Navigation Satellite Systems (GNSS) IWV from the cooperation of the International GNSS Monitoring and Assessment System (iGMAS) and the National Observatory (Observatório Nacional, ON) of Brazil, from the Brazilian Network for Continuous Monitoring (RBMC), and IWV products from Moderate Resolution Imaging Spectroradiometer (MODIS) and radiosonde, jointly with surface meteorological data, in two sectors of the state of Rio de Janeiro from February 2015–August 2018. High variability of the near surface air temperature (T) and relative humidity (RH) were observed among eight meteorological sites. The mean T differences between sites, up to 4.4 °C, led to mean differences as high as 3.1 K for weighted mean temperature (Tm) and hence 0.83 mm for IWV differences. Local grid points of MODIS IWV estimates had relatively good agreement with the GNSS-derived IWV, with mean differences from –2.4–1.1 mm for the daytime passages of the satellites TERRA and AQUA and underestimation from –9 mm to –3 mm during nighttime overpasses. A contrasting behavior was found in the radiosonde IWV estimates compared with the estimates from GNSS. There were dry biases of 1.4 mm (3.7% lower than expected) by radiosonde IWV during the daytime, considering that all other estimates were unbiased and the differences between IWVGNSS and IWVRADS were consistent. Based on the IWV comparisons between radiosonde and GNSS at nighttime, the atmosphere over the radiosonde site is about 1.2 mm and 2.3 mm wetter than that over the RBMC RIOD and iGMAS RDJN stations, respectively. The atmosphere over the site RIOD was 1.2 mm wetter than over that of RDJN for all three-hour means. These results showed that there were important variabilities in the meteorological conditions and in the distribution of water vapor in the MERJ. The data from the iGMAS RDJN station were feasible, together with those from the RBMC, MODIS, and radiosonde data, to investigate IWV in the region with occurrence of heat islands and peculiar physiographic and meteorological characteristics. This work recommends the magnification of the GNSS network in the State of Rio de Janeiro with the use of complete meteorological station data collocated near every GNSS receiver, aiming to improve local IWV estimates and serving as additional support for operational numerical assimilation, weather forecast, and nowcast of extreme rainfall and flooding events.

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Section: Discussionsupporting

confidence: 91%

Section: Discussionmentioning

confidence: 75%

Section: Introductionmentioning

confidence: 99%

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Assessment of Integrated Water Vapor Estimates from the iGMAS and the Brazilian Network GNSS Ground-Based Receivers in Rio de Janeiro

2019

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“…(See Figure 1 that shows higher records of rainfall in XE than those in the other two sites with recorded rainfall.) The spatial and temporal variabilities of T between the sites analyzed in this work corroborate with the observations of [23][24][25] that mapped urban, suburban, and rural heat islands in the MARJ.…”

Section: Meteorological Conditionssupporting

confidence: 89%

“…These comparisons showed low T and e, less spread, and high accuracy between the matches RD and RI, and hence low Tm and IWV in the year 2015. The daytime convection seems to be influenced by land heating (such as the heat islands identified by [23][24][25]). Additionally, the convergence of the southerly and easterly sea breezes causes maxima rainfall from the coastline to the upslopes of the mountain ranges during the nocturnal hours (compare with [26][27][28]).…”

Section: Meteorological Conditionsmentioning

confidence: 99%

Assessment of Integrated Water Vapor Estimates from the iGMAS and the Brazilian Network GNSS Ground-Based Receivers in Rio de Janeiro

Mota¹,

Song²,

Stępniak³

2019

Preprint

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There is crescent demand for knowledge improvement of the integrated water vapor (IWV) distribution in regions affected by heat islands that are associated with extreme rainfall events such as in the metropolitan area of Rio de Janeiro (MARJ). This work assessed the suitability and distribution of IWV in the MARJ using products from the Global Navigation Satellite Systems (GNSS), MODerate Resolution Imaging Spectroradiometer (MODIS), and radiosonde. GNSS data were collected by the tracking station named RDJN, from the cooperation of the International GNSS Monitoring and Assessment System (iGMAS) and the National Observatory of Brazil (Observatório Nacional - ON), and the tracking stations ONRJ, RIOD, and RJCG belonging to the Brazilian Network for Continuous Monitoring (RBMC) in the period of January 2015–August 2018. High variability of the near surface air temperature (T) and relative humidity (RH) were observed among eight meteorological sites considered. The mean T differences between sites, up to 4.4 °C, led to mean differences as high as 3.1 K for weighted mean temperature (Tm) and hence 0.83 mm for IWV differences. The performance of the MODIS MOD07 and MYD07 products provided a reasonably good representation of the mean spatial distribution of IWV, especially during the daylight passages of the satellites TERRA and AQUA. Local grid points of MODIS IWV estimates had relatively good agreement with the GNSS-derived IWV, with mean differences from -2.4–1.1 mm considering only daytime passages of the satellites TERRA and AQUA. During nighttime, MODIS underestimated IWV (from -9–-3 mm) with respect to GNSS, due to attenuation of IR radiation by clouds. A contrasting behavior was found in the radiosonde IWV estimates compared with the estimates from GNSS. There were dry biases of 1.4 mm (3.7% lower than expected) by radiosonde IWV during the daytime considering that all other estimates were unbiased and the differences between IWV GNSS and IWV RADS were consistent. Based on the IWV comparisons between radiosonde and GNSS at nighttime, the atmosphere over the radiosonde site is about 1.2 (2.3) mm wetter than over RIOD (RDJN) station. The long time series of the comparisons between IWVRDJN and IWVRIOD showed that the highest values of IWV occurred from the afternoon to nocturnal hours. Further, the atmosphere over the site RIOD was consistently about 1 mm wetter than over RDJN. These results showed the feasibility of the iGMAS RDJN station data compared with the RBMC, MODIS, and radiosonde data to investigate IWV in a region with occurrence of heat islands, and the peculiar physiographic and meteorological characteristics as in the MARJ. This work recommended the usage of complete meteorological station data collocated near every GNSS receiver aiming improvements of local GNSS IWV estimates and serving as additional support for operational numerical assimilation, weather forecast, and nowcast of extreme rainfall events.

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Prediction of temperature using linear regression

Menon¹,

Bharadwaj²,

Shetty³

et al. 2017

2017 International Conference on Electrical, Electronics, Communication, Computer, and Optimization Techniques (ICEECCOT)

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Estimation of the urban heat island in the Metropolitan Area of Rio de Janeiro - Brazil

Cited by 4 publications

References 13 publications

Assessment of Integrated Water Vapor Estimates from the iGMAS and the Brazilian Network GNSS Ground-Based Receivers in Rio de Janeiro

Assessment of Integrated Water Vapor Estimates from the iGMAS and the Brazilian Network GNSS Ground-Based Receivers in Rio de Janeiro

Assessment of Integrated Water Vapor Estimates from the iGMAS and the Brazilian Network GNSS Ground-Based Receivers in Rio de Janeiro

Prediction of temperature using linear regression

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