Abstract
Abstract This work aimed to select semivariogram models to estimate trends in monthly precipitation in Paraiba State-Brazil using ordinary kriging. The methodology involves the application of geostatistical interpolation of precipitation records of 51 years from 69 rainfall stations across the state. Analysis of semivariograms showed that specific months had a strong spatial dependence (Index of Spatial Dependence - IDE < 25%). The trends were subjected to the following models: circular, spherical, pentaspherical, exponential, Gaussian, rational quadratic, K-Bessel and tetraspherical. The best fit models were selected by cross-validation and Error Comparison Index (ECI). Each data set (month) had a particular spatial dependence structure, which made it necessary to define specific models of semivariogram in order to enhance the adjustment of the experimental semivariogram. Besides, the monthly trend map was plotted to justify the chosen models.
Highlights
Northern South America distinguishes by being a large and complex region where distinct weather systems act
To choose the best-fitted model that would predict the trend of precipitation in Paraiba, we used cross-validation
We analyze rainfall trends over the entire Paraíba state, where significant changes in rainfall trends have occurred during all months
Summary
Northern South America distinguishes by being a large and complex region where distinct weather systems act. According to Andreoli et al (2012), the Amazon region, which represents one of the most intense convective areas in the world, and northeast of Brazil, which is related to intense and prolonged droughts due to its semi-arid climate, are inserted in northern South America. Rainfall is a periodical spatiotemporal phenomenon displaying significant spatial and temporal variability, and rain gauge networks only collect point estimates. Providing an estimate of spatial rainfall distribution within an area from rain gauge data usually remains a barrier of interpolation (Mirás-Avalos et al, 2007). Rainfall measurement principles have remained unchanged; non-recording and recording rain gauges are still the standard equipment for measuring ground-based precipitation, notwithstanding that they only provide point measurements. According to Ochoa et al (2014), rainfall amounts evaluated at different locations are usually extrapolated to obtain areal-average rainfall estimates
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