Connection Between Frontal Extremity And Intertropical Convergence Zone On The Northeast
                        Brazil

Lyra, Matheus José Arruda; Cavalcante, Lucas Carvalho Vieira; Levit, Vladimir; Федорова, Н. И.

doi:10.11137/2019_1_413_424

Cited by 6 publications

(3 citation statements)

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“…In addition to this annual oscillation, it presents oscillations with higher frequencies, varying from weeks to days. The influence of this positioning on rainfall is addressed in several studies (Lyra et al, 2019). The ITCZ is more significant over the oceans, and therefore, Sea Surface Temperature (SST) is one of the determining factors in its position and intensity (Ferreira and Mello, 2005;Carvalho, 2020).…”

Section: Climate Change Processmentioning

confidence: 99%

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Influence of rainfall on wind power generation in Northeast Brazil

Barros¹,

Sobral

Assis

et al. 2021

Rev. Bras. Ciênc. Ambient. (Online)

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Wind power has been emerging as one of the main renewable energy sources in Northeast Brazil, which concentrates 87% of the country’s installed wind capacity, especially in recent years, due to water scarcity and its seasonal energy complementarity to hydraulic generation. The objective of this article is to present a method to evaluate the influence of rainfall on the behavior of wind power generation, considering rainfall anomaly index and extreme climatic indices of precipitation. We utilized daily rainfall data from cities located near wind farms CE1 and CE2 in the state of Ceará — Aracati, in the 1974-2016 period, and Trairi, in the 1976-2016 period —, as well as daily wind power generation data for the same period, provided by the Electric System National Operator (ONS). The RClimdex software was used to calculate 11 indices of climatic extremes dependent on rainfall. The capacity factor for wind power generation was calculated for the period from 2011 to 2016 for the CE1 and CE2 wind farms. The application of this method found an inversely proportional relation between rainfall anomaly index (RAI) and the wind power capacity factor, with a decrease in total rainfall and a greater number of consecutive dry days and concentrated rain in the short term. From 2012 to 2016, the rainfall anomaly index was negative. However, wind power factors were higher than in 2011. The developed methodology can be applied to other wind farms, contributing to the medium and long term energy planning of the National Interconnected System.

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Section: Climate Change Processmentioning

confidence: 99%

“…As a consequence, wind generation was lower on these days. In this region, the main responsible factor in the occurrence of rainfall is the Intertropical Convergence Zone (Lyra et al, 2019).…”

Section: Analysis Of Rainfall Anomaly Index and Its Relation With The Capacity Factor Of Wind Power Generationmentioning

confidence: 99%

Influence of rainfall on wind power generation in Northeast Brazil

Barros¹,

Sobral

Assis

et al. 2021

Rev. Bras. Ciênc. Ambient. (Online)

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“…The observed patterns are directly related to atmospheric phenomena that modulate climate variability in the NRB. The ITCZ is the main modulator of the rainy season in northern NRB [15,69,70]. During the austral summer, the ITCZ moves toward the southern hemisphere, due to the temperature gradient between the hemispheres, and reaches the northern portion of the NRB.…”

Section: Drought Frequencymentioning

confidence: 99%

Bivariate Assessment of Drought Return Periods and Frequency in Brazilian Northeast Using Joint Distribution by Copula Method

et al. 2020

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The Northeast region of Brazil (NRB) is the most populous semiarid area in the world and is extremely susceptible to droughts. The severity and duration of these droughts depend on several factors, and they do not necessarily follow the same behavior. The aim of this work is to evaluate the frequency of droughts in the NRB and calculate the return period of each drought event using the copula technique, which integrates the duration and severity of the drought in the NRB in a joint bivariate distribution. Monthly precipitation data from 96 meteorological stations spatially distributed in the NRB, ranging from 1961 to 2017, are used. The copula technique is applied to the Standardized Precipitation Index (SPI) on the three-month time scale, testing three families of Archimedean copula functions (Gumbel–Hougaard, Clayton and Frank) to reveal which model is best suited for the data. Averagely, the most frequent droughts observed in the NRB are concentrated in the northern sector of the region, with an observed duration varying from three and a half to five and a half months. However, the eastern NRB experiences the most severe droughts, lasting for 14 to 24 months. The probability distributions that perform better in modeling the series of severity and duration of droughts are exponential, normal and lognormal. The observed severity and duration values show that, for average values, the return period across the region is approximately 24 months. Still in this regard, the southernmost tip of the NRB stands out for having a return period of over 35 months. Regarding maximum observed values of severity and duration, the NRB eastern strip has the longest return period (>60 months), mainly in the southeastern portion where a return period above 90 months was observed. The northern NRB shows the shortest return period (~45 months), indicating that it is the NRB sector with the highest frequency of intense droughts. These results provide useful information for drought risk management in the NRB.

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