Advancing the methodology for identifying key risks and prioritizing impact chain indicators based on the Korea Climate Crisis Adaptation Information Taxonomy (KADT)

Systematic climate risk assessment and adaptation information management are increasingly emphasized in response to the climate crisis, yet Korea lacks a standardized framework for evaluating nationally designated climate risks. This study advances the methodology for identifying key risks within the Korea Adaptation Information Taxonomy (KADT) by incorporating quantitative evidence into the traditionally qualitative, expert-driven process. A scoring system was established by quantifying the occurrence trends of climate impact factors through slope analysis of time-series data and by evaluating the magnitude of risk impacts using disaster-related damage costs. Based on this approach, the top 30% of risks within each sector were selected as candidate key risks. For these risks, impact chains were constructed, and indicators categorized into hazard, exposure, and vulnerability were systematically listed and prioritized according to interpretability and data availability. The proposed methodology provides a structured basis for linking indicators with key risks, enhances the objectivity and reliability of climate risk assessment, and offers practical criteria for evaluating indicator applicability while identifying gaps in climate-related data. By supporting the development of a national climate adaptation information platform, this study contributes to strengthening the evidence base and enabling the effective and evidence-based implementation of Korea’s climate crisis adaptation policies.

Authors

Publication Details

Journal
Journal of Climate Change Research
Published
2025-10-31
DOI
https://doi.org/10.15531/ksccr.2025.16.5.1001
Primary Topic
Flood Risk Assessment and Management
Type
article
Field-Weighted Citation Impact
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article

Advancing the methodology for identifying key risks and prioritizing impact chain indicators based on the Korea Climate Crisis Adaptation Information Taxonomy (KADT)

Hyungah Jin, Do Hyun Seo, Young Jae Yoo, Yun‐Yeong Oh et al.
Journal of Climate Change Research
Flood Risk Assessment and Management
article

Advancing the methodology for identifying key risks and prioritizing impact chain indicators based on the Korea Climate Crisis Adaptation Information Taxonomy (KADT)

Hyungah Jin, Do Hyun Seo, Young Jae Yoo, Yun‐Yeong Oh, Seong Woo Jeon, Si Won Jeong
article en

Abstract

Systematic climate risk assessment and adaptation information management are increasingly emphasized in response to the climate crisis, yet Korea lacks a standardized framework for evaluating nationally designated climate risks. This study advances the methodology for identifying key risks within the Korea Adaptation Information Taxonomy (KADT) by incorporating quantitative evidence into the traditionally qualitative, expert-driven process. A scoring system was established by quantifying the occurrence trends of climate impact factors through slope analysis of time-series data and by evaluating the magnitude of risk impacts using disaster-related damage costs. Based on this approach, the top 30% of risks within each sector were selected as candidate key risks. For these risks, impact chains were constructed, and indicators categorized into hazard, exposure, and vulnerability were systematically listed and prioritized according to interpretability and data availability. The proposed methodology provides a structured basis for linking indicators with key risks, enhances the objectivity and reliability of climate risk assessment, and offers practical criteria for evaluating indicator applicability while identifying gaps in climate-related data. By supporting the development of a national climate adaptation information platform, this study contributes to strengthening the evidence base and enabling the effective and evidence-based implementation of Korea’s climate crisis adaptation policies.

Journal of Climate Change ResearchVol. 16(5-2)
Openalex Percentile: Top 67%
Flood Risk Assessment and Management
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