Technical Note: Estimating aerosol effects on cloud radiative forcing
By Steven Ghan. 2013
251 citations recorded by the source corpus.
Abstract. Estimating anthropogenic aerosol effects on the planetary energy balance through the aerosol influence on clouds using the difference in cloud radiative forcing from simulations with and without anthropogenic emissions produces estimates that are positively biased. A more representative method is suggested using the difference in cloud radiative forcing calculated as a diagnostic with aerosol scattering and absorption neglected. The method also yields an aerosol radiative forcing decomposition that includes a term quantifying the impact of changes in surface albedo. The method requires only two additional diagnostic calculations: the whole-sky and clear-sky top-of-atmosphere radiative flux with aerosol scattering and absorption neglected.
Subfields: Atmospheric Science, Global and Planetary Change
View Paper: https://www.semanticscholar.org/paper/f5d8d4855c291ff4143d3074d7fe544e468d7b4c
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Atmospheric Science
- Stephen A. Klein
- M. Zelinka
- Bjorn Stevens
- Robert Pincus
- Piers M. Forster
- T. Andrews
- J. Golaz
- Peter M. Caldwell
In Global and Planetary Change
- Stephen A. Klein
- Bjorn Stevens
- M. Zelinka
- Robert Pincus
- Piers M. Forster
- T. Andrews
- J. Golaz
- Peter M. Caldwell
Citations in the corpus
- The Radiative Forcing Model Intercomparison Project (RFMIP): Experimental Protocol for CMIP6 (in open review: 10.5194/gmd-2016-88) (2016, methodology): “In the same spirit we are interested in comparing radiative perturbations and cloud adjustments estimated from radiative kernels with those explicitly calculated in models employing the “triple radiation call” approach of Ghan (2013) to diagnose instantaneous radiative forcing and cloud adjustments.”
- Recommendations for diagnosing effective radiative forcing from climate models for CMIP6 (2016, background): “Additional radiation calls with aerosol scattering and absorption neglected, and cloud scattering and absorption neglected, to distinguish the forcing from aerosol-cloud interaction from aerosol-radiation interaction are needed to distinguish types of rapid adjustment [Ghan, 2013; Ghan et al., 2012]”
- Quantifying components of aerosol‐cloud‐radiation interactions in climate models (2014, methodology): “These masking terms mean that previously used simple approaches for estimating direct aerosol effects will be biased [see also Ghan, 2013].”
- The DOE E3SM Coupled Model Version 1: Description and Results at High Resolution (2019, background): “As explained and defended in Ghan (2013), this approach allows the total aerosol ERF to be decomposed into ERF due to aerosol-cloud interaction (ERFaci), ERF due to aerosol-radiation interaction (ERFari), and ERF due to surface albedo change.”
- Advanced Two-Moment Bulk Microphysics for Global Models. Part II: Global Model Solutions and Aerosol–Cloud Interactions* (2015, unknown): “It remains to be seen if the different balance of clouds also affects climate feedbacks in CAM5, as in the GFDL model analyzed by Golaz et al. (2013).”
- An Overview of the Atmospheric Component of the Energy Exascale Earth System Model (2019, methodology): “Contributions from aerosol‐radiation interactions and aerosol‐surface interactions (Ghan, 2013) are smaller than 0.1 W/m2 for both models.”