Summary
This study evaluated how the choice of dry indicator significantly affects projections of compound hot-dry events under climate change using 22 CMIP6 models. The authors found substantial differences in projected event frequency depending on whether precipitation, runoff, soil moisture, or multivariate indices were used to characterise drought conditions. While model uncertainty remains the dominant source of uncertainty, dry indicator choice emerges as a substantial and sometimes regionally dominant source of uncertainty, highlighting the importance of indicator selection in climate risk assessments.
Regional applicability
The global analysis includes projections for United Kingdom regions. Findings are directly applicable to UK climate adaptation planning, particularly for water resource and agricultural drought risk assessments, where the choice between precipitation-based versus soil moisture-based drought metrics could substantially alter project climate impacts.
Key measures
Projected changes in likelihood of compound hot-dry events; uncertainty attribution to dry indicator choice, model uncertainty, and scenario uncertainty
Outcomes reported
The study quantified sensitivity of projected changes in compound hot-dry events to different dry indicators (precipitation, runoff, soil moisture, and multivariate indices) using CMIP6 models. It compared the relative importance of dry indicator choice against model and scenario uncertainty sources.
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