Skip to main content
U.S. flag

An official website of the United States government

Publication Date
1 December 2019

The Potential to Reduce Uncertainty in Regional Runoff Projections from Climate Models

Print / PDF
Powerpoint Slide

We benchmark climate model representation of regional runoff sensitivity (how much runoff changes with a changing climate) with observational estimates of runoff sensitivity and derive an observational constraint on future runoff projections for major basins in the western United States.


The observational constraint has the potential to greatly reduce uncertainty in future runoff projections, which will guide both model development as well as climate change adaptation in water-scarce regions. 


Climate model projections show greater uncertainty for runoff (precipitation minus evapotranspiration) than for precipitation. Why is that? We investigate regional runoff sensitivities – how much runoff changes with warming and precipitation – in climate models and find that models have a widespread in runoff sensitivity. A model’s runoff sensitivity can explain directly how much runoff change a model predicts for the future, so this is clearly an important parameter for future projections. We gather observational estimates of runoff sensitivity and ask ‘which models have a realistic runoff sensitivity?’ We then constrain the future projections by using model projections together with observed sensitivity, basically giving weight to models that are better performing than others. This results in a reduction of uncertainty surrounding future projections, which is a result that is useful for both the modeling and stakeholder communities: the modeling community is made aware of systematic biases in climate models that should be focused on in future model development and, in the interim, stakeholders are served future runoff projections with reduced uncertainty.

Point of Contact
Flavio Lehner
National Center for Atmospheric Research (NCAR)
Funding Program Area(s)