Articles | Volume 18, issue 17
https://doi.org/10.5194/acp-18-13031-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-18-13031-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
11 Sep 2018
Research article |
| 11 Sep 2018
| 11 Sep 2018
The importance of comprehensive parameter sampling and multiple observations for robust constraint of aerosol radiative forcing
Jill S. Johnson
CORRESPONDING AUTHOR
Institute for Climate and Atmospheric Science, School of Earth and
Environment, University of Leeds, Leeds, LS2 9JT, UK
Leighton A. Regayre
Institute for Climate and Atmospheric Science, School of Earth and
Environment, University of Leeds, Leeds, LS2 9JT, UK
Masaru Yoshioka
Institute for Climate and Atmospheric Science, School of Earth and
Environment, University of Leeds, Leeds, LS2 9JT, UK
Kirsty J. Pringle
Institute for Climate and Atmospheric Science, School of Earth and
Environment, University of Leeds, Leeds, LS2 9JT, UK
Lindsay A. Lee
Institute for Climate and Atmospheric Science, School of Earth and
Environment, University of Leeds, Leeds, LS2 9JT, UK
David M. H. Sexton
Met Office Hadley Centre, Fitzroy Road, Exeter, EX1 3PB, UK
John W. Rostron
Met Office Hadley Centre, Fitzroy Road, Exeter, EX1 3PB, UK
Ben B. B. Booth
Met Office Hadley Centre, Fitzroy Road, Exeter, EX1 3PB, UK
Kenneth S. Carslaw
Institute for Climate and Atmospheric Science, School of Earth and
Environment, University of Leeds, Leeds, LS2 9JT, UK
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- Quantifying the local and remote impacts of sub‐grid physical processes on the Southeast Pacific sea surface fluxes in the Community Atmosphere Model version 5 by a limited‐area parameter perturbation approach S. Liu et al. 10.1002/joc.7308
- Chemical Characterization of Atmospheric Aerosols in Monte Fenton, Punta Arenas, Chilean Southern Patagonia G. Mansilla et al. 10.3390/atmos14071084
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- Effect of aerosol radiative forcing uncertainty on projected exceedance year of a 1.5 °C global temperature rise A. Peace et al. 10.1088/1748-9326/aba20c
- The future of Earth system prediction: Advances in model-data fusion A. Gettelman et al. 10.1126/sciadv.abn3488
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- The hemispheric contrast in cloud microphysical properties constrains aerosol forcing I. McCoy et al. 10.1073/pnas.1922502117
- The impact of performance filtering on climate feedbacks in a perturbed parameter ensemble J. Rostron et al. 10.1007/s00382-020-05281-8
- Ensembles of Global Climate Model Variants Designed for the Quantification and Constraint of Uncertainty in Aerosols and Their Radiative Forcing M. Yoshioka et al. 10.1029/2019MS001628
- Statistical constraints on climate model parameters using a scalable cloud-based inference framework J. Carzon et al. 10.1017/eds.2023.12
- Overview of the Antarctic Circumnavigation Expedition: Study of Preindustrial-like Aerosols and Their Climate Effects (ACE-SPACE) J. Schmale et al. 10.1175/BAMS-D-18-0187.1
- Modelling ultrafine particle growth in a flow tube reactor M. Taylor Jr. et al. 10.5194/amt-15-4663-2022
- Simulating organic aerosol in Delhi with WRF-Chem using the volatility-basis-set approach: exploring model uncertainty with a Gaussian process emulator E. Reyes-Villegas et al. 10.5194/acp-23-5763-2023
- Emulating aerosol optics with randomly generated neural networks A. Geiss et al. 10.5194/gmd-16-2355-2023
- Assessment of aerosol–cloud–radiation correlations in satellite observations, climate models and reanalysis F. Bender et al. 10.1007/s00382-018-4384-z
- Modeling and spatial characterization of aerosols at Middle East AERONET stations C. Anoruo et al. 10.1007/s00704-023-04384-6
- Aerosol and physical atmosphere model parameters are both important sources of uncertainty in aerosol ERF L. Regayre et al. 10.5194/acp-18-9975-2018
26 citations as recorded by crossref.
- Robust observational constraint of uncertain aerosol processes and emissions in a climate model and the effect on aerosol radiative forcing J. Johnson et al. 10.5194/acp-20-9491-2020
- Evaluation and projections of the East Asian summer monsoon in a perturbed parameter ensemble J. Rostron et al. 10.1007/s00382-022-06507-7
- Quantifying the local and remote impacts of sub‐grid physical processes on the Southeast Pacific sea surface fluxes in the Community Atmosphere Model version 5 by a limited‐area parameter perturbation approach S. Liu et al. 10.1002/joc.7308
- Chemical Characterization of Atmospheric Aerosols in Monte Fenton, Punta Arenas, Chilean Southern Patagonia G. Mansilla et al. 10.3390/atmos14071084
- Characterization of size-segregated particles' turbulent flux and deposition velocity by eddy correlation method at an Arctic site A. Donateo et al. 10.5194/acp-23-7425-2023
- Evaluation of global simulations of aerosol particle and cloud condensation nuclei number, with implications for cloud droplet formation G. Fanourgakis et al. 10.5194/acp-19-8591-2019
- Assessing the potential for simplification in global climate model cloud microphysics U. Proske et al. 10.5194/acp-22-4737-2022
- Bounding Global Aerosol Radiative Forcing of Climate Change N. Bellouin et al. 10.1029/2019RG000660
- Correcting a bias in a climate model with an augmented emulator D. McNeall et al. 10.5194/gmd-13-2487-2020
- Radiative forcing of climate change from the Copernicus reanalysis of atmospheric composition N. Bellouin et al. 10.5194/essd-12-1649-2020
- PyCHAM: CHemistry with Aerosol Microphysics in Python S. O’Meara et al. 10.21105/joss.01918
- Aerosol Forcing: Still Uncertain, Still Relevant F. Bender 10.1029/2019AV000128
- Effect of aerosol radiative forcing uncertainty on projected exceedance year of a 1.5 °C global temperature rise A. Peace et al. 10.1088/1748-9326/aba20c
- The future of Earth system prediction: Advances in model-data fusion A. Gettelman et al. 10.1126/sciadv.abn3488
- Calibrating a global atmospheric chemistry transport model using Gaussian process emulation and ground-level concentrations of ozone and carbon monoxide E. Ryan & O. Wild 10.5194/gmd-14-5373-2021
- Interactions between atmospheric composition and climate change – progress in understanding and future opportunities from AerChemMIP, PDRMIP, and RFMIP S. Fiedler et al. 10.5194/gmd-17-2387-2024
- Biomass-burning smoke's properties and its interactions with marine stratocumulus clouds in WRF-CAM5 and southeastern Atlantic field campaigns C. Howes et al. 10.5194/acp-23-13911-2023
- EFFICIENT CALIBRATION FOR HIGH-DIMENSIONAL COMPUTER MODEL OUTPUT USING BASIS METHODS J. Salter & D. Williamson 10.1615/Int.J.UncertaintyQuantification.2022039747
- The hemispheric contrast in cloud microphysical properties constrains aerosol forcing I. McCoy et al. 10.1073/pnas.1922502117
- The impact of performance filtering on climate feedbacks in a perturbed parameter ensemble J. Rostron et al. 10.1007/s00382-020-05281-8
- Ensembles of Global Climate Model Variants Designed for the Quantification and Constraint of Uncertainty in Aerosols and Their Radiative Forcing M. Yoshioka et al. 10.1029/2019MS001628
- Statistical constraints on climate model parameters using a scalable cloud-based inference framework J. Carzon et al. 10.1017/eds.2023.12
- Overview of the Antarctic Circumnavigation Expedition: Study of Preindustrial-like Aerosols and Their Climate Effects (ACE-SPACE) J. Schmale et al. 10.1175/BAMS-D-18-0187.1
- Modelling ultrafine particle growth in a flow tube reactor M. Taylor Jr. et al. 10.5194/amt-15-4663-2022
- Simulating organic aerosol in Delhi with WRF-Chem using the volatility-basis-set approach: exploring model uncertainty with a Gaussian process emulator E. Reyes-Villegas et al. 10.5194/acp-23-5763-2023
- Emulating aerosol optics with randomly generated neural networks A. Geiss et al. 10.5194/gmd-16-2355-2023
3 citations as recorded by crossref.
- Assessment of aerosol–cloud–radiation correlations in satellite observations, climate models and reanalysis F. Bender et al. 10.1007/s00382-018-4384-z
- Modeling and spatial characterization of aerosols at Middle East AERONET stations C. Anoruo et al. 10.1007/s00704-023-04384-6
- Aerosol and physical atmosphere model parameters are both important sources of uncertainty in aerosol ERF L. Regayre et al. 10.5194/acp-18-9975-2018
Latest update: 14 Dec 2024
Short summary
We estimate the uncertainty in an aerosol–climate model that has been tuned to match several common types of observations. We used a large set of model simulations and built emulators so that we could generate 4 million “variants” of our climate model. Even after using nine aerosol and cloud observations to constrain the model, the uncertainty remains large. We conclude that estimates of aerosol forcing from multi-model studies are likely to be more uncertain than currently estimated.
We estimate the uncertainty in an aerosol–climate model that has been tuned to match several...
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