Analysis of Daily Rainfall in São Carlos/SP, Brazil over 1979-2017 Using Laplace Trend Test

Abstract

Rainfall expresses one of the most complex climate factors in Southeastern Brazil. Understanding the dynamics and temporal trends of rainfall represents a significant challenge due to regional and even global mechanisms, such as FS (Frontal Systems) and the SACZ (South Atlantic Convergence Zone), and the interaction with the Atlantic and Pacific Oceans. The present study aimed at analyzing the pluviometric tendencies in São Carlos/SP, in the countryside of São Paulo State. Laplace trend test was used to comprehend the temporal evolution of daily rainfall in the region in the historical series 1979-2017, in seven pluviometric stations (climatological or surface stations). Significant fluctuations in interannual trends and between seasons were observed. However, it was noted that the beginning of the 1980s showed positive trends, whereas, as of the year 2000, most of the stations demonstrated negative trends, indicating a reduction in daily rainfall volume due to the great tropical climatic variability of Brazil. Emphasis should also be given to the regional and local effects, such as elevation and urbanization, respectively, which corroborate such differences among the analyzed stations. This methodology is of considerable value for the observation of pluviometric trends, and future studies can validate such a tool in climatological studies.

Satellite-Based Precipitation Estimates Validation Using Surface Stations in the Central Region of the State of São Paulo, From 1981 to 2019

“…It is noted that both data show, for most seasons, a negative trend in monthly rainfall at the studied area. This pattern of negative trends was also observed in the region by Sanches et al (2020), who pointed to a reduction in rainfall for the municipality of São Carlos-SP. In other study over a larger area (Paraná basin), Rafee et al (2021) have found general negative trends for annual rainfall in the north portion of the watershed (which includes the region of this study), and positive trends when moving toward the south of the area.…”

Análise espaço-temporal da precipitação na região central do estado de São Paulo utilizando dados CHIRPS

“…A variabilidade pluviométrica tem sido um tema constante nas pesquisas científicas, tendo em vista sua importância em escala regional e local, na medida em que as oscilações das chuvas impactam nas mais diversas regiões do planeta. Ainda, com o avanço de modelos insustentáveis de uso e ocupação do solo, principalmente pela conversão de florestas às atividades antrópicas com potencial para afetar o ciclo hidrológico, torna-se imprescindível a análise e monitoramento dos regimes pluviométricos (Ambrizzi et al, 2014;Abreu et al, 2017;Cunha et al, 2014;Filho et al, 2019;Sanches et al, 2020;Zandonadi et al, 2016;e Zilli et al, 2017;Mu et al, 2021;Sales et al, 2021).…”

Precipitation Variability for Protected Areas of Primary Forest and Pastureland in Southwestern Amazônia

“…Advances in remotely sensed products' contribution are key for climate sciences, since several studies confirm that precipitation has shown alterations in its spatial and temporal patterns [3,4,9,10], precipitation in the Amazon Basin is determined by the regularity caused by the action of the Continental Equatorial Air Mass, which originates in the west of the region; the Intertropical Convergence Zone, developed by the convergence of trade winds and cold fronts from extratropical latitudes that frequently impact the southern region of the Amazon; and systems such as the Bolivian High, that act at higher levels of the troposphere [11]. Such oscillations are identified both by the number of episodes and by the rainfall volume; as attested by several climatological studies carried out in South America [12][13][14][15][16][17][18][19][20][21].…”

“…The standardized normal random variable is roughly represented by this measurement. According to Sanches [18], the Laplace test allows for the design of this kind of evaluation as a function of precipitation, reiterating the tool's potential for these studies in historical data series. The following equation determines the trend based on a given value u(t) and taking into account a given period [0, t] [47] (Equation ( 16)).…”