The Science                                

Global precipitation is expected to increase with climate change, but accurately predicting these changes is challenging for current models. To better assess future conditions, two key factors must themselves be more accurate—(1) how much global mean precipitation increases per degree of warming (termed hydrological sensitivity, or HS), and (2) how much global mean temperature increases due to human activity (termed climate sensitivity, or CS). Because CS and HS contribute roughly equally to uncertainty in global precipitation change, both terms must be constrained to reliably estimate future precipitation increase.

The Impact

To improve estimates of future precipitation changes, this study better predicts both HS and CS. Researchers found that HS and CS are significantly affected by global surface cloud shortwave feedback, which is the change in the cloud effect (how clouds scatter shortwave radiation from the sun) per unit warming. They further showed that cloud shortwave feedback is related to the climatological pattern of the cloud effect and is thus constrainable by observations. One such constraint suggests a greater increase in global mean precipitation than what is currently estimated and reduces overall uncertainty by ~25%. By more accurately predicting future changes in precipitation, this work provides important information for assessing the impacts of climate change.

Summary

The fractional increase in global mean precipitation is a way to quantify hydrological cycle intensification under anthropogenic warming. However, global mean precipitation varies by a factor of more than three among model projections, hindering credible assessments of the associated climate impacts. This variation stems from uncertainty in both hydrological sensitivity (global mean precipitation increase per unit warming) and climate sensitivity (global mean temperature increase per forcing). By investigating hydrological and climate sensitivities in a unified surface-energy-balance perspective, this study finds that both sensitivities are significantly correlated with surface shortwave cloud feedback, which is further linked to the climatological pattern of the cloud shortwave effect. Therefore, HS, CS, and global mean precipitation are constrained by the observed climatological pattern of cloud effect. The 5 – 95% uncertainty range of global mean precipitation from 1979 – 2005 to 2080 – 2100 under the high and moderate emission scenarios is constrained from 6.34±3.53% and 4.19±2.28%, respectively in the raw ensemble-model projection to 7.03±2.59% and 4.63±1.71%. This constraint thus suggests a higher global mean precipitation increase and reduces the uncertainty by ~25%, providing valuable information for impact assessments.

PNNL Contact

L. Ruby Leung, Pacific Northwest National Laboratory, ruby.leung@pnnl.gov

Funding

This research was supported by the Department of Energy, Office of Science, as part of research in the Regional and Global Model Analysis program area, Earth and Environmental System Modeling program.