Analysis of Precipitation, Extreme Events, and Climate Model Evaluation in MATOPIBA
MATOPIBA; Precipitation; Extreme Events; Climate Models; Climate
Trends
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.