Quantifying Components of Aerosol-Cloud-Radiation Interactions in Climate Models

TitleQuantifying Components of Aerosol-Cloud-Radiation Interactions in Climate Models
Publication TypeJournal Article
Year of Publication2014
JournalJournal of Geophysical Research - Atmospheres
Pages7599-7615
Date Published07/2014
Abstract / Summary

The interaction of anthropogenic aerosols with radiation and clouds is the largest source of uncertainty in the radiative forcing of the climate during the industrial period. Here we apply novel techniques to diagnose the contributors to the shortwave (SW) effective radiative forcing (ERF) from aerosol-radiation-interaction (ERFari) and from aerosol cloud interaction (ERFaci) in experiments performed in phase 5 of the Coupled Model Intercomparison Project. We find that the ensemble mean SW ERFari+aci of −1.40±0.56 W m−2 comes roughly 25% from ERFari (−0.35±0.20 W m−2) and 75% from ERFaci (−1.04±0.67 W m−2). ERFari is made up of −0.62±0.30 W m−2 due to aerosol scattering opposed by +0.26 ± 0.12 W m−2 due to aerosol absorption and is largest near emission sources. The ERFari from nonsulfate aerosols is +0.13 ± 0.09 W m−2, consisting of −0.15±0.11 W m−2 of scattering and +0.29 ± 0.15 W m−2 of absorption. The change in clear-sky flux is a negatively biased measure of ERFari, as the presence of clouds reduces the magnitude and intermodel spread of ERFari by 40–50%. ERFaci, which is large both near and downwind of emission sources, is composed of −0.99±0.54 W m−2 from enhanced cloud scattering, with much smaller contributions from increased cloud amount and absorption. In models that allow aerosols to affect ice clouds, large increases in the optical depth of high clouds cause substantial longwave and shortwave radiative anomalies. Intermodel spread in ERFaci is dominated by differences in how aerosols increase cloud scattering, but even if all models agreed on this effect, over a fifth of the spread in ERFaci would remain due solely to differences in total cloud amount.

URLhttp://onlinelibrary.wiley.com/doi/10.1002/2014JD021710/abstract
DOI10.1002/2014JD021710.
Journal: Journal of Geophysical Research - Atmospheres
Year of Publication: 2014
Pages: 7599-7615
Date Published: 07/2014

The interaction of anthropogenic aerosols with radiation and clouds is the largest source of uncertainty in the radiative forcing of the climate during the industrial period. Here we apply novel techniques to diagnose the contributors to the shortwave (SW) effective radiative forcing (ERF) from aerosol-radiation-interaction (ERFari) and from aerosol cloud interaction (ERFaci) in experiments performed in phase 5 of the Coupled Model Intercomparison Project. We find that the ensemble mean SW ERFari+aci of −1.40±0.56 W m−2 comes roughly 25% from ERFari (−0.35±0.20 W m−2) and 75% from ERFaci (−1.04±0.67 W m−2). ERFari is made up of −0.62±0.30 W m−2 due to aerosol scattering opposed by +0.26 ± 0.12 W m−2 due to aerosol absorption and is largest near emission sources. The ERFari from nonsulfate aerosols is +0.13 ± 0.09 W m−2, consisting of −0.15±0.11 W m−2 of scattering and +0.29 ± 0.15 W m−2 of absorption. The change in clear-sky flux is a negatively biased measure of ERFari, as the presence of clouds reduces the magnitude and intermodel spread of ERFari by 40–50%. ERFaci, which is large both near and downwind of emission sources, is composed of −0.99±0.54 W m−2 from enhanced cloud scattering, with much smaller contributions from increased cloud amount and absorption. In models that allow aerosols to affect ice clouds, large increases in the optical depth of high clouds cause substantial longwave and shortwave radiative anomalies. Intermodel spread in ERFaci is dominated by differences in how aerosols increase cloud scattering, but even if all models agreed on this effect, over a fifth of the spread in ERFaci would remain due solely to differences in total cloud amount.

DOI: 10.1002/2014JD021710.
Citation:
Zelinka, MD, T Andrews, PM Forster, and KE Taylor.  2014.  "Quantifying Components of Aerosol-Cloud-Radiation Interactions in Climate Models."  Journal of Geophysical Research - Atmospheres 7599-7615.  https://doi.org/10.1002/2014JD021710..