A Hierarchical Archimedean Copula (HAC) Model for Climatic Variables: An Application to Kenyan Data

Abstract

This study applies a Hierarchical Archimedean Copula model to analyze dependence structures among key climatic variables in Kenya. Using empirical climate data, the paper demonstrates how hierarchical copulas capture complex, multi-level interdependencies beyond traditional correlation approaches. The findings highlight the usefulness of advanced statistical modeling for understanding climate variability and informing climate-sensitive planning and policy in low- and middle-income settings.