Pulse Brain · Growing Health Evidence Index
Tier 3 — Observational / field trialPeer-reviewed

The potential to reduce uncertainty in regional runoff projections from climate models

Flavio Lehner, Andrew W. Wood, J. A. Vano, David M. Lawrence, Martyn Clark, Justin Mankin

Nature Climate Change · 2019

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Summary

This Nature Climate Change article, published in 2019, examines the sources of uncertainty inherent in regional runoff projections generated by climate models and explores avenues for reducing that uncertainty. The authors, affiliated with institutions including the National Center for Atmospheric Research, assess how model structure, parameterisation, and initialisation choices contribute to divergence in projected runoff across regions. The work suggests that targeted improvements to climate and hydrological model coupling, as well as enhanced initialisation strategies, could narrow the range of future runoff projections and thereby improve regional water resource planning under climate change.

UK applicability

The findings are relevant to UK water resource management and climate adaptation planning, particularly for river basin authorities and water companies assessing future supply reliability. UK-specific runoff projections depend critically on the uncertainty quantification methods described; improved regional uncertainty characterisation could inform more robust water security strategies for a changing climate.

Key measures

Regional runoff projection uncertainty; climate model skill; hydrological sensitivity to climate drivers

Outcomes reported

The study examined sources of uncertainty in regional runoff projections from climate models and assessed the potential to reduce such uncertainty through improved model representation and initialisation techniques.

Theme
Climate & resilience
Subject
Climate & greenhouse gas mitigation
Study type
Research
Study design
Narrative review
Source type
Peer-reviewed study
Status
Published
Geography
Global
System type
Other
DOI
10.1038/s41558-019-0639-x
Catalogue ID
BFmommpl0r-wpttmw

Topic tags

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