Untangling causality in midlatitude aerosol–cloud adjustments
<p>Aerosol–cloud interactions represent the leading uncertainty in our ability to infer climate sensitivity from the observational record. The forcing from changes in cloud albedo driven by increases in cloud droplet number (<span class="inline-formula"><i>N</i><...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2020-04-01
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| Series: | Atmospheric Chemistry and Physics |
| Online Access: | https://www.atmos-chem-phys.net/20/4085/2020/acp-20-4085-2020.pdf |
| _version_ | 1817989597992321024 |
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| author | D. T. McCoy D. T. McCoy P. Field P. Field H. Gordon H. Gordon G. S. Elsaesser G. S. Elsaesser D. P. Grosvenor D. P. Grosvenor |
| author_facet | D. T. McCoy D. T. McCoy P. Field P. Field H. Gordon H. Gordon G. S. Elsaesser G. S. Elsaesser D. P. Grosvenor D. P. Grosvenor |
| author_sort | D. T. McCoy |
| collection | DOAJ |
| description | <p>Aerosol–cloud interactions represent the leading uncertainty in our ability to infer climate sensitivity from the observational
record. The forcing from changes in cloud albedo driven by increases in cloud droplet number (<span class="inline-formula"><i>N</i><sub>d</sub></span>) (the first
indirect effect) is confidently negative and has narrowed its probable range in the last decade, but the sign and strength of
forcing associated with changes in cloud macrophysics in response to aerosol (aerosol–cloud adjustments) remain uncertain. This
uncertainty reflects our inability to accurately quantify variability not associated with a causal link flowing from the cloud
microphysical state to the cloud macrophysical state. Once variability associated with meteorology has been removed, covariance
between the liquid water path (LWP) averaged across cloudy and clear regions (here characterizing the macrophysical state) and
<span class="inline-formula"><i>N</i><sub>d</sub></span> (characterizing the microphysical) is the sum of two causal pathways linking <span class="inline-formula"><i>N</i><sub>d</sub></span> to LWP:
<span class="inline-formula"><i>N</i><sub>d</sub></span> altering LWP (adjustments) and precipitation scavenging aerosol and thus depleting <span class="inline-formula"><i>N</i><sub>d</sub></span>. Only the
former term is relevant to constraining adjustments, but disentangling these terms in observations is challenging. We
hypothesize that the diversity of constraints on aerosol–cloud adjustments in the literature may be partly due to not
explicitly characterizing covariance flowing from cloud to aerosol and aerosol to cloud. Here, we restrict our analysis to the
regime of extratropical clouds outside of low-pressure centers associated with cyclonic activity. Observations from MAC-LWP (Multisensor Advanced Climatology of Liquid Water Path)
and MODIS are compared to simulations in the Met Office Unified Model (UM) GA7.1 (the atmosphere model of HadGEM3-GC3.1 and
UKESM1). The meteorological predictors of LWP are found to be similar between the model and observations. There is also
agreement with previous literature on cloud-controlling factors finding that increasing stability, moisture, and sensible heat
flux enhance LWP, while increasing subsidence and sea surface temperature decrease it. A simulation where cloud microphysics
are insensitive to changes in <span class="inline-formula"><i>N</i><sub>d</sub></span> is used to characterize covariance between <span class="inline-formula"><i>N</i><sub>d</sub></span> and LWP that is
induced by factors other than aerosol–cloud adjustments. By removing variability associated with meteorology and scavenging, we
infer the sensitivity of LWP to changes in <span class="inline-formula"><i>N</i><sub>d</sub></span>. Application of this technique to UM GA7.1 simulations reproduces
the true model adjustment strength. Observational constraints developed using simulated covariability not induced by adjustments
and observed covariability between <span class="inline-formula"><i>N</i><sub>d</sub></span> and LWP predict a 25 %–30 % overestimate by the UM GA7.1 in LWP change
and a 30 %–35 % overestimate in associated radiative forcing.</p> |
| first_indexed | 2024-04-14T00:48:12Z |
| format | Article |
| id | doaj.art-bbc6eaa6ee424c7d80b3d53f55ba2a07 |
| institution | Directory Open Access Journal |
| issn | 1680-7316 1680-7324 |
| language | English |
| last_indexed | 2024-04-14T00:48:12Z |
| publishDate | 2020-04-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Atmospheric Chemistry and Physics |
| spelling | doaj.art-bbc6eaa6ee424c7d80b3d53f55ba2a072022-12-22T02:21:54ZengCopernicus PublicationsAtmospheric Chemistry and Physics1680-73161680-73242020-04-01204085410310.5194/acp-20-4085-2020Untangling causality in midlatitude aerosol–cloud adjustmentsD. T. McCoy0D. T. McCoy1P. Field2P. Field3H. Gordon4H. Gordon5G. S. Elsaesser6G. S. Elsaesser7D. P. Grosvenor8D. P. Grosvenor9Institute for Climate and Atmospheric Science, University of Leeds, Leeds, UKnow at: Department of Atmospheric Science, University of Wyoming, Laramie, WY 82071, USAInstitute for Climate and Atmospheric Science, University of Leeds, Leeds, UKMet Office, Fitzroy Rd, Exeter, UKInstitute for Climate and Atmospheric Science, University of Leeds, Leeds, UKEngineering Research Accelerator, Carnegie Mellon University, Forbes Avenue, Pittsburgh, PA, USADepartment of Applied Physics and Applied Mathematics, Columbia University, New York, NY, USANASA Goddard Institute for Space Studies, New York, NY, USAInstitute for Climate and Atmospheric Science, University of Leeds, Leeds, UKNational Centre for Atmospheric Science, Leeds, UK<p>Aerosol–cloud interactions represent the leading uncertainty in our ability to infer climate sensitivity from the observational record. The forcing from changes in cloud albedo driven by increases in cloud droplet number (<span class="inline-formula"><i>N</i><sub>d</sub></span>) (the first indirect effect) is confidently negative and has narrowed its probable range in the last decade, but the sign and strength of forcing associated with changes in cloud macrophysics in response to aerosol (aerosol–cloud adjustments) remain uncertain. This uncertainty reflects our inability to accurately quantify variability not associated with a causal link flowing from the cloud microphysical state to the cloud macrophysical state. Once variability associated with meteorology has been removed, covariance between the liquid water path (LWP) averaged across cloudy and clear regions (here characterizing the macrophysical state) and <span class="inline-formula"><i>N</i><sub>d</sub></span> (characterizing the microphysical) is the sum of two causal pathways linking <span class="inline-formula"><i>N</i><sub>d</sub></span> to LWP: <span class="inline-formula"><i>N</i><sub>d</sub></span> altering LWP (adjustments) and precipitation scavenging aerosol and thus depleting <span class="inline-formula"><i>N</i><sub>d</sub></span>. Only the former term is relevant to constraining adjustments, but disentangling these terms in observations is challenging. We hypothesize that the diversity of constraints on aerosol–cloud adjustments in the literature may be partly due to not explicitly characterizing covariance flowing from cloud to aerosol and aerosol to cloud. Here, we restrict our analysis to the regime of extratropical clouds outside of low-pressure centers associated with cyclonic activity. Observations from MAC-LWP (Multisensor Advanced Climatology of Liquid Water Path) and MODIS are compared to simulations in the Met Office Unified Model (UM) GA7.1 (the atmosphere model of HadGEM3-GC3.1 and UKESM1). The meteorological predictors of LWP are found to be similar between the model and observations. There is also agreement with previous literature on cloud-controlling factors finding that increasing stability, moisture, and sensible heat flux enhance LWP, while increasing subsidence and sea surface temperature decrease it. A simulation where cloud microphysics are insensitive to changes in <span class="inline-formula"><i>N</i><sub>d</sub></span> is used to characterize covariance between <span class="inline-formula"><i>N</i><sub>d</sub></span> and LWP that is induced by factors other than aerosol–cloud adjustments. By removing variability associated with meteorology and scavenging, we infer the sensitivity of LWP to changes in <span class="inline-formula"><i>N</i><sub>d</sub></span>. Application of this technique to UM GA7.1 simulations reproduces the true model adjustment strength. Observational constraints developed using simulated covariability not induced by adjustments and observed covariability between <span class="inline-formula"><i>N</i><sub>d</sub></span> and LWP predict a 25 %–30 % overestimate by the UM GA7.1 in LWP change and a 30 %–35 % overestimate in associated radiative forcing.</p>https://www.atmos-chem-phys.net/20/4085/2020/acp-20-4085-2020.pdf |
| spellingShingle | D. T. McCoy D. T. McCoy P. Field P. Field H. Gordon H. Gordon G. S. Elsaesser G. S. Elsaesser D. P. Grosvenor D. P. Grosvenor Untangling causality in midlatitude aerosol–cloud adjustments Atmospheric Chemistry and Physics |
| title | Untangling causality in midlatitude aerosol–cloud adjustments |
| title_full | Untangling causality in midlatitude aerosol–cloud adjustments |
| title_fullStr | Untangling causality in midlatitude aerosol–cloud adjustments |
| title_full_unstemmed | Untangling causality in midlatitude aerosol–cloud adjustments |
| title_short | Untangling causality in midlatitude aerosol–cloud adjustments |
| title_sort | untangling causality in midlatitude aerosol cloud adjustments |
| url | https://www.atmos-chem-phys.net/20/4085/2020/acp-20-4085-2020.pdf |
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