TY - JOUR
T1 - Comparison of methods to estimate aerosol effective radiative forcings in climate models
AU - Zelinka, Mark D.
AU - Smith, Christopher J.
AU - Qin, Yi
AU - Taylor, Karl E.
N1 - Funding Information:
Mark D. Zelinka, Yi Qin, and Karl E. Taylor were supported by the U.S. Department of Energy (DOE) Regional and Global Model Analysis program area. Christopher J. Smith was supported by a NERC–IIASA Collaborative Research Fellowship (NE/T009381/1).
Funding Information:
We acknowledge the World Climate Research Programme, which, through its Working Group on Coupled Modelling, coordinated and promoted CMIP. We thank the climate modeling groups for producing and making available their model output, the Earth System Grid Federation (ESGF) for archiving the data and providing access, and the multiple funding agencies who support CMIP and ESGF. The work of Mark D. Zelinka and Karl E. Taylor was performed under the auspices of the U.S. DOE by Lawrence Livermore National Laboratory under contract DE-AC52-07NA27344. The Pacific Northwest National Laboratory is operated for the DOE by the Battelle Memorial Institute under contract DE-AC05-76RL01830. We thank Susanne Bauer for assistance interpreting the GISS results as well as two anonymous reviewers and editor Yuan Wang for helpful comments that improved the paper.
Publisher Copyright:
© 2023 Copernicus GmbH. All rights reserved.
PY - 2023/8/9
Y1 - 2023/8/9
N2 - Uncertainty in the effective radiative forcing (ERF) of climate primarily arises from the unknown contribution of aerosols, which impact radiative fluxes directly and through modifying cloud properties. Climate model simulations with fixed sea surface temperatures but perturbed atmospheric aerosol loadings allow for an estimate of how strongly the planet's radiative energy budget has been perturbed by the increase in aerosols since pre-industrial times. The approximate partial radiative perturbation (APRP) technique further decomposes the contributions to the direct forcing due to aerosol scattering and absorption and to the indirect forcing due to aerosol-induced changes in cloud scattering, amount, and absorption, as well as the effects of aerosols on surface albedo. Here we evaluate previously published APRP-derived estimates of aerosol effective radiative forcings from these simulations conducted in the sixth phase of the Coupled Model Intercomparison Project (CMIP6) and find that they are biased as a result of two large coding errors that - in most cases - fortuitously compensate. The most notable exception is the direct radiative forcing from absorbing aerosols, which is more than 40ĝ€¯% larger averaged across CMIP6 models in the present study. Correcting these biases eliminates the residuals and leads to better agreement with benchmark estimates derived from double calls to the radiation code. The APRP method - when properly implemented - remains a highly accurate and efficient technique for diagnosing aerosol ERF in cases where double radiation calls are not available, and in all cases it provides quantification of the individual contributors to the ERF that are highly useful but not otherwise available.
AB - Uncertainty in the effective radiative forcing (ERF) of climate primarily arises from the unknown contribution of aerosols, which impact radiative fluxes directly and through modifying cloud properties. Climate model simulations with fixed sea surface temperatures but perturbed atmospheric aerosol loadings allow for an estimate of how strongly the planet's radiative energy budget has been perturbed by the increase in aerosols since pre-industrial times. The approximate partial radiative perturbation (APRP) technique further decomposes the contributions to the direct forcing due to aerosol scattering and absorption and to the indirect forcing due to aerosol-induced changes in cloud scattering, amount, and absorption, as well as the effects of aerosols on surface albedo. Here we evaluate previously published APRP-derived estimates of aerosol effective radiative forcings from these simulations conducted in the sixth phase of the Coupled Model Intercomparison Project (CMIP6) and find that they are biased as a result of two large coding errors that - in most cases - fortuitously compensate. The most notable exception is the direct radiative forcing from absorbing aerosols, which is more than 40ĝ€¯% larger averaged across CMIP6 models in the present study. Correcting these biases eliminates the residuals and leads to better agreement with benchmark estimates derived from double calls to the radiation code. The APRP method - when properly implemented - remains a highly accurate and efficient technique for diagnosing aerosol ERF in cases where double radiation calls are not available, and in all cases it provides quantification of the individual contributors to the ERF that are highly useful but not otherwise available.
UR - https://doi.org/10.5194/acp-23-8879-2023
UR - http://www.scopus.com/inward/record.url?scp=85171137758&partnerID=8YFLogxK
U2 - 10.5194/acp-23-8879-2023
DO - 10.5194/acp-23-8879-2023
M3 - Article
VL - 23
SP - 8879
EP - 8898
JO - Atmospheric Chemistry and Physics
JF - Atmospheric Chemistry and Physics
IS - 15
ER -