Aerosol and physical atmosphere model parameters are both important sources of uncertainty in aerosol ERF
<p>Changes in aerosols cause a change in net top-of-the-atmosphere (ToA) short-wave and long-wave radiative fluxes; rapid adjustments in clouds, water vapour and temperature; and an effective radiative forcing (ERF) of the planetary energy budget. The diverse sources of model uncertainty an...
| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2018-07-01
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| Series: | Atmospheric Chemistry and Physics |
| Online Access: | https://www.atmos-chem-phys.net/18/9975/2018/acp-18-9975-2018.pdf |
| _version_ | 1818148018851938304 |
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| author | L. A. Regayre J. S. Johnson M. Yoshioka K. J. Pringle D. M. H. Sexton B. B. B. Booth L. A. Lee N. Bellouin K. S. Carslaw |
| author_facet | L. A. Regayre J. S. Johnson M. Yoshioka K. J. Pringle D. M. H. Sexton B. B. B. Booth L. A. Lee N. Bellouin K. S. Carslaw |
| author_sort | L. A. Regayre |
| collection | DOAJ |
| description | <p>Changes in aerosols cause a change in net top-of-the-atmosphere
(ToA) short-wave and long-wave radiative fluxes; rapid adjustments in clouds,
water vapour and temperature; and an effective radiative forcing (ERF)
of the planetary energy budget. The diverse sources of model uncertainty and
the computational cost of running climate models make it difficult to isolate
the main causes of aerosol ERF uncertainty and to understand how observations
can be used to constrain it. We explore the aerosol ERF uncertainty by using
fast model emulators to generate a very large set of aerosol–climate model
variants that span the model uncertainty due to 27 parameters
related to atmospheric and aerosol processes. Sensitivity analyses shows that
the uncertainty in the ToA flux is dominated (around 80 %) by uncertainties
in the physical atmosphere model, particularly parameters that affect cloud
reflectivity. However, uncertainty in the change in ToA flux caused by
aerosol emissions over the industrial period (the aerosol ERF) is controlled
by a combination of uncertainties in aerosol (around 60 %) and physical
atmosphere (around 40 %) parameters. Four atmospheric and aerosol parameters
account for around 80 % of the uncertainty in short-wave ToA flux (mostly
parameters that directly scale cloud reflectivity, cloud water content or
cloud droplet concentrations), and these parameters also account for around
60 % of the aerosol ERF uncertainty. The common causes of uncertainty mean
that constraining the modelled planetary brightness to tightly match
satellite observations changes the lower 95 % credible aerosol ERF value from
−2.65 to −2.37 W m<sup>−2</sup>. This
suggests the strongest forcings (below around −2.4 W m<sup>−2</sup>)
are inconsistent with observations. These results show that, regardless of
the fact that the ToA flux is 2 orders of magnitude larger than the aerosol
ERF, the observed flux can constrain the uncertainty in ERF because their
values are connected by constrainable process parameters. The key to reducing
the aerosol ERF uncertainty further will be to identify observations that can
additionally constrain individual parameter ranges and/or combined parameter
effects, which can be achieved through sensitivity analysis of perturbed
parameter ensembles.</p> |
| first_indexed | 2024-12-11T12:44:28Z |
| format | Article |
| id | doaj.art-5f25839312a142c3a94b133eeffa4a46 |
| institution | Directory Open Access Journal |
| issn | 1680-7316 1680-7324 |
| language | English |
| last_indexed | 2024-12-11T12:44:28Z |
| publishDate | 2018-07-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Atmospheric Chemistry and Physics |
| spelling | doaj.art-5f25839312a142c3a94b133eeffa4a462022-12-22T01:06:52ZengCopernicus PublicationsAtmospheric Chemistry and Physics1680-73161680-73242018-07-011899751000610.5194/acp-18-9975-2018Aerosol and physical atmosphere model parameters are both important sources of uncertainty in aerosol ERFL. A. Regayre0J. S. Johnson1M. Yoshioka2K. J. Pringle3D. M. H. Sexton4B. B. B. Booth5L. A. Lee6N. Bellouin7K. S. Carslaw8Institute for Climate and Atmospheric Science, School of Earth and Environment, University of Leeds, Leeds, LS2 9JT, UKInstitute for Climate and Atmospheric Science, School of Earth and Environment, University of Leeds, Leeds, LS2 9JT, UKInstitute for Climate and Atmospheric Science, School of Earth and Environment, University of Leeds, Leeds, LS2 9JT, UKInstitute for Climate and Atmospheric Science, School of Earth and Environment, University of Leeds, Leeds, LS2 9JT, UKUK Hadley Centre Met Office, Exeter, Fitzroy Road, Exeter, Devon, EX1 3PB, UKUK Hadley Centre Met Office, Exeter, Fitzroy Road, Exeter, Devon, EX1 3PB, UKInstitute for Climate and Atmospheric Science, School of Earth and Environment, University of Leeds, Leeds, LS2 9JT, UKDepartment of Meteorology, School of Mathematical & Physical Sciences, Faculty of Science,University of Reading, Reading, RG6 6BB, UKInstitute for Climate and Atmospheric Science, School of Earth and Environment, University of Leeds, Leeds, LS2 9JT, UK<p>Changes in aerosols cause a change in net top-of-the-atmosphere (ToA) short-wave and long-wave radiative fluxes; rapid adjustments in clouds, water vapour and temperature; and an effective radiative forcing (ERF) of the planetary energy budget. The diverse sources of model uncertainty and the computational cost of running climate models make it difficult to isolate the main causes of aerosol ERF uncertainty and to understand how observations can be used to constrain it. We explore the aerosol ERF uncertainty by using fast model emulators to generate a very large set of aerosol–climate model variants that span the model uncertainty due to 27 parameters related to atmospheric and aerosol processes. Sensitivity analyses shows that the uncertainty in the ToA flux is dominated (around 80 %) by uncertainties in the physical atmosphere model, particularly parameters that affect cloud reflectivity. However, uncertainty in the change in ToA flux caused by aerosol emissions over the industrial period (the aerosol ERF) is controlled by a combination of uncertainties in aerosol (around 60 %) and physical atmosphere (around 40 %) parameters. Four atmospheric and aerosol parameters account for around 80 % of the uncertainty in short-wave ToA flux (mostly parameters that directly scale cloud reflectivity, cloud water content or cloud droplet concentrations), and these parameters also account for around 60 % of the aerosol ERF uncertainty. The common causes of uncertainty mean that constraining the modelled planetary brightness to tightly match satellite observations changes the lower 95 % credible aerosol ERF value from −2.65 to −2.37 W m<sup>−2</sup>. This suggests the strongest forcings (below around −2.4 W m<sup>−2</sup>) are inconsistent with observations. These results show that, regardless of the fact that the ToA flux is 2 orders of magnitude larger than the aerosol ERF, the observed flux can constrain the uncertainty in ERF because their values are connected by constrainable process parameters. The key to reducing the aerosol ERF uncertainty further will be to identify observations that can additionally constrain individual parameter ranges and/or combined parameter effects, which can be achieved through sensitivity analysis of perturbed parameter ensembles.</p>https://www.atmos-chem-phys.net/18/9975/2018/acp-18-9975-2018.pdf |
| spellingShingle | L. A. Regayre J. S. Johnson M. Yoshioka K. J. Pringle D. M. H. Sexton B. B. B. Booth L. A. Lee N. Bellouin K. S. Carslaw Aerosol and physical atmosphere model parameters are both important sources of uncertainty in aerosol ERF Atmospheric Chemistry and Physics |
| title | Aerosol and physical atmosphere model parameters are both important sources of uncertainty in aerosol ERF |
| title_full | Aerosol and physical atmosphere model parameters are both important sources of uncertainty in aerosol ERF |
| title_fullStr | Aerosol and physical atmosphere model parameters are both important sources of uncertainty in aerosol ERF |
| title_full_unstemmed | Aerosol and physical atmosphere model parameters are both important sources of uncertainty in aerosol ERF |
| title_short | Aerosol and physical atmosphere model parameters are both important sources of uncertainty in aerosol ERF |
| title_sort | aerosol and physical atmosphere model parameters are both important sources of uncertainty in aerosol erf |
| url | https://www.atmos-chem-phys.net/18/9975/2018/acp-18-9975-2018.pdf |
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