A New Paradigm for Diagnosing Contributions to Model Aerosol Forcing Error

TitleA New Paradigm for Diagnosing Contributions to Model Aerosol Forcing Error
Publication TypeJournal Article
Year of Publication2017
Date Published11/2017
Abstract / Summary

A new paradigm in benchmark absorption-scattering radiative transfer is presented that enables both the globally-averaged and spatially-resolved testing of climate model radiation parameterizations in order to uncover persistent sources of biases in the aerosol Instantaneous Radiative Effect (IRE). A proof-of-concept is demonstrated with the GFDL AM4 and CESM 1.2.2 climate models. Instead of prescribing atmospheric conditions and aerosols, as in prior intercomparisons, native snapshots of the atmospheric state and aerosol optical properties from the participating models are used as inputs to an accurate radiation solver to uncover model-relevant biases. These diagnostic results show that the models’ aerosol IRE bias is of the same magnitude as the persistent range cited (~1 W/m2), and also varies spatially and with intrinsic aerosol optical properties. The findings underscore the significance of native model error analysis and its dispositive ability to diagnose global biases, confirming its fundamental value for the Radiative Forcing Model Intercomparison Project.

DOI10.1002/2017GL075933
Year of Publication: 2017
Date Published: 11/2017

A new paradigm in benchmark absorption-scattering radiative transfer is presented that enables both the globally-averaged and spatially-resolved testing of climate model radiation parameterizations in order to uncover persistent sources of biases in the aerosol Instantaneous Radiative Effect (IRE). A proof-of-concept is demonstrated with the GFDL AM4 and CESM 1.2.2 climate models. Instead of prescribing atmospheric conditions and aerosols, as in prior intercomparisons, native snapshots of the atmospheric state and aerosol optical properties from the participating models are used as inputs to an accurate radiation solver to uncover model-relevant biases. These diagnostic results show that the models’ aerosol IRE bias is of the same magnitude as the persistent range cited (~1 W/m2), and also varies spatially and with intrinsic aerosol optical properties. The findings underscore the significance of native model error analysis and its dispositive ability to diagnose global biases, confirming its fundamental value for the Radiative Forcing Model Intercomparison Project.

DOI: 10.1002/2017GL075933
Citation:
Jones, AL, DR Feldman, S Freidenreich, D Paynter, V Ramaswamy, WD Collins, and R Pincus.  2017.  "A New Paradigm for Diagnosing Contributions to Model Aerosol Forcing Error."  https://doi.org/10.1002/2017GL075933.