Johnson, JS orcid.org/0000-0002-4587-6722, Regayre, LA orcid.org/0000-0003-2699-929X, Yoshioka, M orcid.org/0000-0003-2223-1734 et al. (16 more authors) (2020) Robust observational constraint of uncertain aerosol processes and emissions in a climate model and the effect on aerosol radiative forcing. Atmospheric Chemistry and Physics, 20 (15). pp. 9491-9524. ISSN 1680-7316
Abstract
The effect of observational constraint on the ranges of uncertain physical and chemical process parameters was explored in a global aerosol–climate model. The study uses 1 million variants of the Hadley Centre General Environment Model version 3 (HadGEM3) that sample 26 sources of uncertainty, together with over 9000 monthly aggregated grid-box measurements of aerosol optical depth, PM2.5, particle number concentrations, sulfate and organic mass concentrations. Despite many compensating effects in the model, the procedure constrains the probability distributions of parameters related to secondary organic aerosol, anthropogenic SO2 emissions, residential emissions, sea spray emissions, dry deposition rates of SO2 and aerosols, new particle formation, cloud droplet pH and the diameter of primary combustion particles. Observational constraint rules out nearly 98 % of the model variants. On constraint, the ±1σ (standard deviation) range of global annual mean direct radiative forcing (RFari) is reduced by 33 % to −0.14 to −0.26 W m−2, and the 95 % credible interval (CI) is reduced by 34 % to −0.1 to −0.32 W m−2. For the global annual mean aerosol–cloud radiative forcing, RFaci, the ±1σ range is reduced by 7 % to −1.66 to −2.48 W m−2, and the 95 % CI by 6 % to −1.28 to −2.88 W m−2. The tightness of the constraint is limited by parameter cancellation effects (model equifinality) as well as the large and poorly defined “representativeness error” associated with comparing point measurements with a global model. The constraint could also be narrowed if model structural errors that prevent simultaneous agreement with different measurement types in multiple locations and seasons could be improved. For example, constraints using either sulfate or PM2.5 measurements individually result in RFari±1σ ranges that only just overlap, which shows that emergent constraints based on one measurement type may be overconfident.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © Author(s) 2020. This work is distributed under the Creative Commons Attribution 4.0 License. |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > School of Earth and Environment (Leeds) > Inst for Climate & Atmos Science (ICAS) (Leeds) |
Funding Information: | Funder Grant number NERC (Natural Environment Research Council) NE/J024252/1 NERC (Natural Environment Research Council) NE/I020059/1 NERC (Natural Environment Research Council) NE/P013406/1 Met Office P100199 EU - European Union 654109 |
Depositing User: | Symplectic Publications |
Date Deposited: | 30 Sep 2020 11:54 |
Last Modified: | 30 Sep 2020 11:54 |
Status: | Published |
Publisher: | European Geosciences Union |
Identification Number: | 10.5194/acp-20-9491-2020 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:166077 |