Climate Forcing and Trends of Organic Aerosols in the Community Earth System Model (CESM2)
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The Community Earth System Model version 2 (CESM2) includes three main atmospheric configurations: the Community Atmosphere Model version 6 (CAM6) with simplified chemistry and a simplified organic aerosol (OA) scheme, CAM6 with comprehensive tropospheric and stratospheric chemistry representation (CAM6‐chem), and the Whole Atmosphere Community Climate Model version 6 (WACCM6). Both, CAM6‐chem and WACCM6 include a more comprehensive secondary organic aerosols (SOA) approach using the Volatility Basis Set (VBS) scheme and prognostic stratospheric aerosols. This paper describes the different OA schemes available in the different atmospheric configurations of CESM2 and discusses differences in aerosol burden and resulting climate forcings. Derived OA burden and trends differ due to differences in OA formation using the different approaches. Regional differences in Aerosol Optical Depth with larger values using the comprehensive approach occur over SOA source regions. Stronger increasing SOA trends between 1960 and 2015 in WACCM6 compared to CAM6 are due to increasing biogenic emissions aligned with increasing surface temperatures. Using the comprehensive SOA approach further leads to improved comparisons to aircraft observations and SOA formation of ≈143 Tg/yr. We further use WACCM6 to identify source contributions of OA from biogenic, fossil fuel, and biomass burning emissions, to quantify SOA amounts and trends from these sources. Increasing SOA trends between 1960 and 2015 are the result of increasing biogenic emissions aligned with increasing surface temperatures. Biogenic emissions are at least two thirds of the total SOA burden. In addition, SOA source contributions from fossil fuel emissions become more important, with largest values over Southeast Asia. The estimated total anthropogenic forcing of OA in WACCM6 for 1995–2010 conditions is −0.43 W/m 2, mostly from the aerosol direct effect.
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CESM2(WACCM6) has been evaluated against earlier model versions and observations, showing good agreement with ozonesonde data and seasonality of surface ozone, though with some regional spatial biases.
“CESM2(WACCM6) has been evaluated against earlier model versions and observations - including NASA ATom aircraft profiles (Tilmes et al., 2019), Tropospheric Ozone Assessment Report (TOAR) surface ozone data (Emmons et al., 2020), and Measurements of Pollution in The Troposphere (MOPITT) carbon monoxide observations (Schwantes et al., 2020) - showing good agreement with ozonesonde data and season”
From Air quality impacts of stratospheric aerosol injections are likely small and mainly driven by changes in climate, not aerosol settling (2026) · cites this paper as Tilmes et al., 2019
The interactive chemistry-climate framework of WACCM allows capturing coupled meteorological, chemical, and radiative feedbacks that are central to evaluating the air quality response to stratospheric aerosol injection.
“These limitations notwithstanding, the interactive chemistry-climate framework of WACCM allows us to capture coupled meteorological, chemical, and radiative feedbacks that are central to evaluating the air quality response to stratospheric aerosol injection (Tilmes et al., 2019).”
From Air quality impacts of stratospheric aerosol injections are likely small and mainly driven by changes in climate, not aerosol settling (2026) · cites this paper as Tilmes et al., 2019
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Self-citationSpurious Late Historical‐Era Warming in CESM2 Driven by Prescribed Biomass Burning Emissions
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Self-citationOne-third of global population at cancer risk due to elevated volatile organic compounds levels
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Self-citationA multiyear tropical Pacific cooling response to recent Australian wildfires in CESM2
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Self-citationArctic Sea Ice in Two Configurations of the CESM2 During the 20th and 21st Centuries
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Ozone Anomalies in the Free Troposphere During the COVID‐19 Pandemic
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Self-citationAtmospheric nanoparticle growth
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Global Anthropogenic Emissions of Full-Volatility Organic Compounds
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Self-citationChemistry-driven changes strongly influence climate forcing from vegetation emissions
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A Multimodel Investigation of Asian Summer Monsoon UTLS Transport Over the Western Pacific
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Self-citationAnalysis of secondary organic aerosol simulation bias in the Community Earth System Model (CESM2.1)
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Self-citationAttribution of Stratospheric and Tropospheric Ozone Changes Between 1850 and 2014 in CMIP6 Models
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Self-citationGlobal Health and Climate Effects of Organic Aerosols from Different Sources
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Earth system modeling of mercury using CESM2 – Part 1: Atmospheric model CAM6-Chem/Hg v1.0
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Abundant Nitrate and Nitric Acid Aerosol in the Upper Troposphere and Lower Stratosphere
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Self-citationStratospheric Aerosol and Ozone Responses to the Hunga Tonga‐Hunga Ha'apai Volcanic Eruption
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Impact of solar geoengineering on wildfires in the 21st century in CESM2/WACCM6
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Self-citationFate of Pollution Emitted During the 2015 Indonesian Fire Season
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Heat stress in Beijing and its relationship with boundary layer structure and air pollution
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Continental-scale Atmospheric Impacts of the 2020 Western U.S. Wildfires
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Upper stratospheric ClO and HOCl trends (2005–2020): Aura Microwave Limb Sounder and model results
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An Implicit Air Quality Bias Due to the State of Pristine Aerosol
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Influence of land cover change on atmospheric organic gases, aerosols, and radiative effects
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Self-citationAnthropogenic Fingerprint Detectable in Upper Tropospheric Ozone Trends Retrieved from Satellite
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Self-citationGlobal Warming Increases Fire Emissions but Resulting Aerosol Forcing is Uncertain.Preprint
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Reyes‐Villegas, E., Lowe, D., Johnson, J. S., Carslaw, K. S., Darbyshire, E., Flynn, M. J., Allan, J. D., Coe, H., Chen, Y., Wild, O., et al. (2023) · Atmospheric chemistry and physics · doi:10.5194/acp-23-5763-2023 · Cited by 7 · see citing works
Self-citation
- Authors
- Tilmes, S., Hodzic, A., Emmons, L. K., Mills, M. J., Gettelman, A., Kinnison, D. E., Park, M., Lamarque, J. ‐., Vitt, F., Shrivastava, M., Campuzano‐Jost, P., Jimenez, J. L., & Liu, X.
- Affiliations
- NSF National Center for Atmospheric Research (US)
- Atmospheric Chemistry, Observations and Modeling Laboratory National Center for Atmospheric Research Boulder CO USA
- Pacific Northwest National Laboratory (US)
- Cooperative Institute for Research in Environmental Sciences (US)
- University of Wyoming (US)
- Corresponding author
- Tilmes, S.
- ORCID
- Venue
- Journal of Advances in Modeling Earth Systems
- Publisher
- American Geophysical Union (AGU)
- Published
- 2019-12
- Volume
- 11
- Issue
- 12
- Pages
- 4323-4351
- ISSN
- 1942-2466 (ISSN-L)
- OpenAlex
- W2995367207
- Cited by
- 246
- References
- 59
- Citations by year
- 2026: 19 · 2025: 30 · 2024: 40 · 2023: 65 · 2022: 43 · 2021: 31 · 2020: 17 · 2019: 1
- FWCI
- 9.12
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Journal of Advances in Modeling Earth Systems (publishedVersion, cc-by)
- CU Scholar (University of Colorado Boulder) (submittedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- NOAA Institutional Repository (submittedVersion, cc-by)
- Topics
- Physical Sciences › Earth and Planetary Sciences › Atmospheric Science › Atmospheric chemistry and aerosols
- Physical Sciences › Environmental Science › Global and Planetary Change › Atmospheric aerosols and clouds
- Physical Sciences › Earth and Planetary Sciences › Atmospheric Science › Atmospheric Ozone and Climate
- Keywords
- secondary organic aerosol, organic aerosol, radiative forcing, aerosol trends, CESM2, WACCM6, volatility basis set, aerosol optical depth, biogenic emissions, fossil fuel emissions, biomass burning emissions, aerosol direct effect, stratospheric aerosols, aerosol source apportionment
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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