Space-Time Distribution of Rainfall Anomaly Index (Rai) for the Salgado Basin, Ceará State - Brazil

Abstract

Given the great variability of the precipitation in the Brazilian

Dinâmica espaço-temporal das anomalias de precipitação em uma região semiárida, Nordeste do Brasil

“…Lançando mão desse método, torna-se possível compreender as características pluviométricas de determinada região, o que, por sua vez, contribui para o entendimento do clima local e favorece a identificação de áreas suscetíveis à ocorrência de extremos climáticos (Santos et al, 2014;Nóbrega et al, 2015;Hänsel et al, 2016;Nascimento et al, 2019;Yadav et al, 2021). Por ser um método simples e com boa eficiência em comparação a índices mais complexos (Oladipo, 1985), o IAC tem sido adotado em muitos estudos desenvolvidos no sentido de verificar as anomalias de chuva em diferentes regiões (Noronha et al, 2016;Costa & Rodrigues, 2017;Nafchi, 2018;. Entretanto, apesar de ser muito aplicado nos estudos de eventos climáticos extremos, poucos trabalhos o relacionam à variabilidade espacial da precipitação, sobretudo, para regiões Áridas e Semiáridas.…”

Variabilidade espacial e temporal da precipitação pluviométrica na região hidrográfica do Paraguaçu - BA

“…The highest indexes (between 0 and 0.18) occurred at the eastern end and in some points distributed from the central area to the west of the hydrographic region. Likewise, Costa and Rodrigues (2017) found higher RAI values in regions with high rainfall. On the other hand, the most critical negative indices were situated to the east of the middle Paraguaçu, which is influenced by the drier climate.…”

“…The main negative peaks were in the years 2012 (-4.3) and 1993 (-3.1), also marked by the lowest average precipitation records. In those same years, the maximum negative values of the RAI were found by Costa and Rodrigues (2017) in a basin in Ceará (state of the same region of Bahia), a fact explained by the occurrence of the El Niño phenomenon of strong intensity, responsible for the scarcity of rains in the Northeast of Brazil (NEB).…”

“…Kumari et al (2016) evaluated this interpolator in the distribution of the same variable and found the similar percentage ratio of 88.2 %, for the 484 mm RMSE. As for the RAI and the annual PCI, the literature has not presented the performance of the models, and ordinary kriging is already used as a starting point for spatial distribution in Brazilian studies (COSTA;RODRIGUES, 2017;SIQUEIRA;NERY, 2018). Similar to the average annual precipitation, the values of the RMSE for the rainfall indexes were below the standard deviations of the initial data, equivalent to 0.14 for the RAI and 3.84 % for the annual PCI.…”

Effects of Droughts on Vegetation Condition and Ecosystem Service Delivery in Data-Poor Areas: A Case of Bobirwa Sub-District, Limpopo Basin and Botswana

“…For the weather station precipitation data, the annual raiall anomaly index (RAI) was computed based on the Rooy Van Equation (1965) to analyze the frequency and intensity of the dry (wet) years. RAI was initially developed by Rooy in 1965 and adapted by Freitas in 2005 [31], and is computed by the following equations:…”