Central American climate extreme trends: A statistical analysis of CLIMDEX indices

This paper presents a comprehensive analysis of climate extreme trends across Central America using the CLIMDEX methodology applied to daily precipitation and temperature data from 1981-2020. The research updates previous assessments from 2005 and introduces innovative statistical techniques that account for spatial and temporal dependencies when determining trend significance.

The study analyzes 21 extreme climate indices (10 precipitation, 11 temperature) across 216 grid points in the Central American region using CHIRPs and CHIRTs gridded datasets. A key methodological advancement is the implementation of Monte Carlo permutation tests that consider spatial correlation, providing more robust assessments of trend significance than traditional approaches that assume independence.

Key findings reveal more consistent and widespread significant warming trends in temperature extremes, with evidence of increasing minimum and maximum temperatures across the region. Precipitation extreme trends are more localized and variable, though the research identifies a robust signal toward more intense extreme precipitation events, particularly in Costa Rica. The analysis suggests a pattern of drier conditions in northern Central America and wetter conditions in the south, consistent with climate model projections.

This work is the product of a collaboration with researchers from the Univesity of Costa Rica, at the CIGEFI. The research addresses critical needs for updated climate change assessments in a region highly vulnerable to climate extremes, providing essential information for adaptation planning and risk management. The study’s methodological contributions in handling spatially correlated climate data have broader applications for climate trend analysis globally.

Recommended citation: Alfaro-Córdoba, M., Mora-Sandí, N. P., Hidalgo, H. G., & Alfaro, E. J. (2024). "Central American climate extreme trends: A statistical analysis of CLIMDEX indices." International Journal of Climatology, 44(11), 4115-4126. DOI: 10.1002/joc.8571
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