The occurrence of extreme weather phenomena is projected to intensify globally in the coming decades, particularly under future climate scenarios. As a result, the long-term resilience of urban green infrastructure (UGI) remains uncertain. Although several studies have attempted to quantify UGI vulnerability to climate change, exposure indicators beyond precipitation-related variables have often been overlooked, limiting the understanding of the full range of climatic stressors. To address this gap, an extreme weather exposure index development framework was established to support climate-resilient planning and environmental impact assessments. The framework was applied to two UGI types, permeable pavements and green roofs, across eight major cities in South Korea using three weighting methods. The Analytic Hierarchy Process (AHP) was used to reflect expert judgment, Principal Component Analysis (PCA) to identify co-varying environmental stressors, and entropy weighting to capture indicators with discriminatory power. Climate projections were obtained from CMIP6 models under the SSP1–2.6 and SSP5–8.5 scenarios and bias-corrected using quantile mapping. AHP emphasized temperature extremes, PCA highlighted multivariate contrasts such as heat wave and rainfall extremes, and entropy weighting prioritized unevenly distributed indicators such as cold wave days and heavy rainfall. Exposure levels varied by UGI type, city, and climate zone, with cities classified into humid continental (Dfa) and humid subtropical (Cfa) climate zones. A strong alignment was observed between AHP- and PCA-based indices (ρ = 0.74–0.93), indicating consistency between expert-informed and variance-driven approaches. Among the methods, AHP was found most reliable, making it the recommended basis for index construction. Meanwhile, the framework remains broadly applicable across planning contexts, offering a structured tool for assessing climate exposure and supporting resilient urban infrastructure under climatic uncertainties.
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