Summary
This 2019 study in Nature Climate Change examines the relative contributions of different uncertainty sources in regional runoff projections derived from global climate models, as suggested by the title and journal scope. The authors appear to evaluate whether constraining certain model inputs or structural choices could reduce spread in future runoff predictions at regional scales—a question relevant to water resource and agricultural planning. The findings address the question of whether improved climate model design or ensemble methods could narrow the range of hydrological outcomes.
UK applicability
UK water resource planning and agricultural drought adaptation strategies depend on reliable regional runoff projections; this work is likely directly applicable to reducing uncertainty in Environment Agency and Met Office hydrological forecasting. The methodology may inform UK climate impact assessments for farming and water availability.
Key measures
Regional runoff projections, model-to-model uncertainty, internal variability, forcing uncertainty, and skill metrics for hydrological climate model outputs
Outcomes reported
The study examined sources of uncertainty in regional runoff projections from climate models and assessed potential methods to reduce that uncertainty. The research quantified how model structure, initial conditions, and forcing data contribute to projection variability across different regions.
Topic tags
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