Climatic variability and occurrence of extreme events in Matopiba
climate variability, climate modeling, climatology
The analysis of annual precipitation in the MATOPIBA region revealed variability
over the years, with a slight decreasing trend between 2015 and 2020, although
inconclusive. Using statistical methods such as hierarchical clustering, multiple linear
regression, and the Mann-Kendall trend test, the research investigated seasonal and
spatial variations in precipitation, aiming to provide a solid foundation for future
projections. Pearson correlations indicated a significant role of sea surface temperature
(SST) in the North and South Atlantic, with implications for regional climate variability.
The Generalized Pareto Distribution (GPD) was used to model extreme events, revealing
seasonal patterns that inform adaptive strategies for future scenarios. In evaluating
climate models, the French and American models showed greater consistency,
particularly the French model, while the Chinese and Norwegian models displayed higher
variability. These findings provide a critical perspective for understanding climate trends
in the region, supporting both precipitation forecasting and the development of adaptive
public policies to address the challenges of climate change.