Extreme events of precipitation in the paraibano sertão: Space-temporary variation

• Autor(a) principal: Sena, Jaricélia Patrícia de Oliveira
• Data de Publicação: 2017
• Outros Autores: Lucena, Daisy Beserra, Ribeiro, George do Nascimento
• Tipo de documento: Artigo
• Idioma: por
• Título da fonte: Revista Verde de Agroecologia e Desenvolvimento Sustentavel
• Texto Completo: https://www.gvaa.com.br/revista/index.php/RVADS/article/view/4938
• topic: Temporo-spacial panel; IAC; Semiarid; Painel têmporo-espacial; IAC; Semiárido

Rainfall variability is a striking feature in the semi - arid region, not only in annual totals, but also in quantity and spatial distribution. In order to contribute to the understanding of extreme precipitation events in the semi - arid region of Paraíba, it was identified years of extreme events in the Sertão Paraíba micro - region, using the rainfall anomaly index (IAC). The data used came from the CPC (Climate Prediction Center), a center belonging to the NCEP (National Centers for Environmental Prediction), covering the period 1979-2013. The results show a very homogeneous temporo-space distribution in relation to the extreme events, that is, the rainy or dry years, when they occur reaches the entire microregion. It was observed that in the annual panel a very small precipitation period, it is considered the rainy season and after this period a drastic decrease in precipitation occurs. Of the 35 analyzed years of precipitation, it was verified that 19 years presented rainfall below the climatological average (54.3%) and 16 years with precipitations above the average (45.7%).The contribution of the months that do not compose the rainy season to the Sertão Paraibano microregion (May to January - 9 months), presented in a significant way in the rainy events, however, for the dry events had no contribution. The spatial variation of the precipitation in the region for both the climatology and the compositions of the years selected as dry and rainy, shows a distribution in the east-west direction, with high amplitudes, proving the spatial variation.