Regime de Vento na Serra do Mar - Rio de Janeiro, Brasil

Sobral, Bruno Serafini; Júnior, José Francisco de Oliveira; Góis, Givanildo de; Terassi, Paulo Miguel de Bodas; Pereira, Carlos Rodrigues

doi:10.1590/0102-7786333004

Cited by 12 publications

(9 citation statements)

References 14 publications

(25 reference statements)

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“…The wind variability is associated with land and sea breezes (Pimentel et al ., 2014; Oliveira‐Júnior et al ., 2017). Many stations in G1 are most likely associated with mountain/valley circulations and the interaction of synoptic winds with the mountain ranges of SEB (Sant'Anna Neto, 2005; Sobral et al ., 2018b). Some stations in G1 are next to river lowlands, such as Pirapora/MG (ID 35) and São Romão/MG (ID 37), which are located over São Francisco River valley.…”

Section: Resultsmentioning

confidence: 99%

“…Frontal systems (FS) also contribute to the occurrence of rainfall extremes and changes in the wind regime over SEB (de Morais et al ., 2010; Reboita et al ., 2010; Grimm, 2011; Andrade and Cavalcanti, 2018; Oliveira and Silva Quaresma, 2018; Sobral et al ., 2018b; Correia Filho et al ., 2021). In addition to the influence of SACZ and FS, the region's wind regime is strongly affected by the South Atlantic Subtropical Anticyclone (SASA) and by Atmospheric Blocking (AB) (Reboita et al ., 2010; Grimm, 2011; Gilliland and Keim, 2018b; Machado et al ., 2019).…”

Section: Introductionmentioning

confidence: 99%

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The wind regime over the Brazilian Southeast: Spatial and temporal characterization using multivariate analysis

Filho

Souza

Júnior

et al. 2021

Intl Journal of Climatology

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The characterization of spatial and temporal patterns of wind is essential to several sectors, including energy, urban climate, and applied meteorology. However, few studies describe the regional characteristics of the wind regime over the Brazilian Southeast (SEB), the most developed and populated part of the country. The objectives of the current work were (a) to assess the spatial patterns of the wind regime using cluster analysis (CA) and (b) to apply principal components analysis (PCA) to investigate which meteorological systems influence the spatial and temporal patterns of the wind regime. The dataset consisted of wind speed and direction from 70 automatic weather stations with records from 2008 to 2019. According to the CA method, four groups of homogeneous wind speed (G1–G4) were identified; G4 presented the highest magnitudes of wind speed (wind speed >5 m·s−1, with maxima of 7.2 m·s−1). Seasonal well‐defined minima (March–June) and maxima (July–October) were observed only for G2 and G3. The systems South Atlantic Subtropical Anticyclone (SASA), Frontal Systems (FS), and the South Atlantic Convergence Zone (SACZ) influenced these groups. In addition, the mesoscale meteorological systems likely influence other groups such as breezes from land/sea (G1, G3, and G4), lakes (G2 and G3), and valley/mountain (G2 and G3). The topography had a strong influence on G3, mainly due to the mountain ranges of Mantiqueira and Serra do Mar and Paraíba River valley. Dominant wind directions were E, N/NE, and NW, associated with SASA, in addition to S and SE/SW, influenced by FS and SACZ. The wind speed range of 1.4–3.9 m·s−1 was dominant in all groups, except for G4 (range of 2.4–5.5 m·s−1). According to PCA analysis, two PCs are enough to explain the wind pattern in the SEB with 69.9% of the total variance explained. The surface roughness accounted for 29% of the total variance explained in PC1. The latitude (37.6%) and distance to the coast (30.8%) are the most important variables for PC2. Region's physiography and meteorological systems strongly influenced the wind regime over the Brazilian Southeast. The assessment of wind regime variability presented in this work is expected to support public policies on renewable energy applications, air pollution, and climate change mitigation.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The wind regime over the Brazilian Southeast: Spatial and temporal characterization using multivariate analysis

Filho

Souza

Júnior

et al. 2021

Intl Journal of Climatology

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“…In the analysis of the relief of the municipality of Cascavel we defined the orographic wall as a decisive factor in the interference of wind direction and speed, since this was a variable that had a clear obstacle effect (Tubelis & Nascimento, 1980), as was observed in the study by (Sobral et al, 2018) conducted on the coast of Rio de Janeiro.…”

Section: Knowledge Of Local Variablesmentioning

confidence: 99%

Method for estimating the wind power micro and minigeneration applied to a city with a subtropical climate in south America

Guicho

Ferreira

Medeiros

et al. 2021

RSD

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The search for renewable resources has become necessary for sustainable development. Wind energy is a clean energy source and of global importance, but most studies refer to high altitude and are carried out by researchers in developed countries. In this work, the objective was to evaluate the potential of micro and mini-generation (low heights) wind power in Cascavel-PR, a city located in southern Brazil, as an example of the application of the proposed methodology. For this purpose, wind speed and direction data were used, with a historical series of 21 years (1997-2017). The land use and occupation were performed in a semi-automatic way using Sentinel-2 satellite images. To generate the maps, an algorithm was created in Spring software, which correlated the land use and land cover information, the wind speed kriging and the formula coefficient values according to the identified obstacles. With this it was possible to conclude that regarding the period, spring is considered the season of the year with the greatest energy potential, where the highest averages for speed and power were estimated. It was also noted that the 40-meter-high range has the greatest potential and that the prevailing winds come from the northeast.

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“…Os estudos sobre as características dos ventos podem indicar aspectos da dinâmica atmosférica e a interação entre os demais atributos climáticos (CARDOSO et al, 2012;. Em um estudo na Serra do Mar no estado do Rio de Janeiro, Sobral et al (2018) destacaram a influência orográfica na distribuição espacial da velocidade e direção dos ventos e, ainda destacaram os padrões da direção dos ventos com os registros de chuvas. Reboita et al (2014)…”

Section: Introductionunclassified

“…para Maringá (PR) e são inferiores aos 38,7% obtidos porBarbano et al (2003) em Campinas (SP). Entretanto, estes valores de calmaria obtidos nas localidades do presente trabalho são superiores ao demonstrado para a Região Metropolitana do Rio de Janeiro porPimentel et al (2014), que estiveram entre 3,4 e 24,9%.Considera-se que a velocidade dos ventos nestas localidades é baixa em comparação às localidades do estado de Alagoas investigadas por Costa e Lyra (2012), que obtiveram velocidades médias anuais entre 5,3 e 7,1 m. s -1 , sendo que os histogramas indicaram a predominância das classes de ventos entre 6 a Em Petrópolis, situada na região serrana do estado do Rio de Janeiro,Sobral et al (2018) mostraram 61,6% dos registros de ventos estiveram entre 2 e 4 m. s -1 , enquanto que em Curitiba e Paranaguá estas classes representam apenas 14,6% e 16,1% dos registros totais anuais, nesta ordem Veneziani et al (2013). observaram para o Núcleo Cunha, no Parque Estadual Serra do Mar (SP) uma velocidade média anual dos ventos de 2 m. s -1 , embora tenha ocorrido calmaria em cerca de 58% do período analisado.Quanto à direção anual dos ventos, observa-se a predominância dos ventos nas direções NE (18,5%) e E (15,2%) em Curitiba, ao passo que Paranaguá caracteriza-se pelas direções S e E, ambas as direções com 15,2% na frequência anual(Figura 3b e 3d).…”

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Regime De Ventos Em Curitiba E Paranaguá, Paraná

Terassi

Oliveira‐Júnior

Galvani

et al. 2019

ABClima

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RESUMO: Os estudos sobre as características da velocidade e direção dos ventos são relevantes para diversos setores da sociedade, sob aspecto ambiental e econômico. Este trabalho objetiva avaliar o regime dos ventos em multiescala (anual, mensal e horária) nos municípios de Curitiba e Paranaguá (PR). Utilizaram-se os dados horários (12,18 e 0 TMG) das estações meteorológicas convencionais pertencentes ao Instituto Nacional de Meteorologia para o período de 1976 a 2010. As rosas de vento e os histogramas foram realizados por meio do programa WRPLOT versão 8.0.0. Para a elaboração dos gráficos boxplot da velocidade e direção dos ventos foram utilizados os softwares R versão 3.3.2 e Statistica 7.0. Em Curitiba verificou-se o predomínio de ventos de nordeste (18,5%) e leste (15,2%) associados à atuação da Alta Subtropical do Atlântico Sul (ASAS), enquanto que em Paranaguá a interação entre o relevo adjacente (Serra do Mar) e a circulação da brisa marítima (Oceano Atlântico) condiciona uma maior frequência de ventos de sul (15,3%). A velocidade média anual dos ventos foi 2,19 m.s -1 em Curitiba e 2,15 m.s -1 em Paranaguá. Os meses com as mais elevadas velocidades dos ventos ocorrem entre setembro e março. O ciclo diário apontou o aumento da velocidade dos ventos às 15 horas, atribuída ao aquecimento superficial e à instabilidade atmosférica, sobretudo em Paranaguá (ambiente costeiro), pois esta localidade apresenta uma temperatura média anual 4°C mais elevada em relação à Curitiba, que mostrou maiores valores de velocidade dos ventos às 9 e 21 horas em comparação à Paranaguá. PALAVRAS-CHAVES: escoamento atmosférico; fatores fisiográficos; velocidade e direção dos ventos, sistemas meteorológicos. WIND REGIME IN CURITIBA AND PARANAGUÁ, PARANÁABSTRACT: Studies about the wind speed and direction characteristics are relevant to several society sectors, both environment and economy. This paper aims to evaluate the winds regime in multiple scales (annual, monthly and hourly) in the Curitiba and Paranaguá municipalities (PR). Were used the time data (12,18 and 0 GMT) of the conventional meteorological stations belonging to the National Meteorological Institute for the period between 1976 to 2010. Wind roses and histograms were performed using WRPLOT version 8.0.0. Were used the software R version 3.3.2 and Statistica 7.0 to _________________Revista Brasileira de Climatologia_________________ ISSN: 2237-8642 (Eletrônica) Ano 15 -Vol. 25 -JUL/DEZ 2019 295 elaborate the boxplot graphics of the speed and direction winds were used. In Curitiba was observed the predominance of northeast (18.5%) and east (15.2%) direction winds associated with the performance of the South Atlantic Subtropical High (SASH), while in Paranaguá the interaction between adjacent relief (Serra do Mar) and the circulation of the maritime breeze (Atlantic Ocean) conditions a greater frequency of south winds (15,3%). The annual average wind velocity was 2.19 m.s -1 in Curitiba and 2.15 m.s -1 in Paranaguá. The months with the highest wind speeds occur betw...

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Regime de Vento na Serra do Mar - Rio de Janeiro, Brasil

Cited by 12 publications

References 14 publications

The wind regime over the Brazilian Southeast: Spatial and temporal characterization using multivariate analysis

The wind regime over the Brazilian Southeast: Spatial and temporal characterization using multivariate analysis

Method for estimating the wind power micro and minigeneration applied to a city with a subtropical climate in south America

Regime De Ventos Em Curitiba E Paranaguá, Paraná

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