Aerosol absorption in global models from AeroCom phase III
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Published:2021-10-26
Issue:20
Volume:21
Page:15929-15947
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ISSN:1680-7324
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Container-title:Atmospheric Chemistry and Physics
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language:en
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Short-container-title:Atmos. Chem. Phys.
Author:
Sand MariaORCID, Samset Bjørn H., Myhre GunnarORCID, Gliß JonasORCID, Bauer Susanne E.ORCID, Bian Huisheng, Chin Mian, Checa-Garcia RamiroORCID, Ginoux PaulORCID, Kipling ZakORCID, Kirkevåg AlfORCID, Kokkola HarriORCID, Le Sager Philippe, Lund Marianne T.ORCID, Matsui HitoshiORCID, van Noije TwanORCID, Olivié Dirk J. L., Remy Samuel, Schulz MichaelORCID, Stier PhilipORCID, Stjern Camilla W.ORCID, Takemura ToshihikoORCID, Tsigaridis KostasORCID, Tsyro Svetlana G., Watson-Parris DuncanORCID
Abstract
Abstract. Aerosol-induced absorption of shortwave radiation can modify the climate through local atmospheric heating, which affects lapse rates,
precipitation, and cloud formation. Presently, the total amount of aerosol
absorption is poorly constrained, and the main absorbing aerosol species
(black carbon (BC), organic aerosols (OA), and mineral dust) are diversely
quantified in global climate models. As part of the third phase of the
Aerosol Comparisons between Observations and
Models (AeroCom) intercomparison initiative (AeroCom phase III), we here
document the distribution and magnitude of aerosol absorption in current
global aerosol models and quantify the sources of intermodel spread,
highlighting the difficulties of attributing absorption to different
species. In total, 15 models have provided total present-day absorption at 550 nm
(using year 2010 emissions), 11 of which have provided absorption per
absorbing species. The multi-model global annual mean total absorption
aerosol optical depth (AAOD) is 0.0054 (0.0020 to 0.0098; 550 nm), with the range given as the minimum and maximum model values. This is 28 % higher compared to the 0.0042 (0.0021 to 0.0076) multi-model mean in AeroCom phase II (using year 2000 emissions), but the difference is within 1 standard
deviation, which, in this study, is 0.0023 (0.0019 in Phase II). Of the summed component AAOD, 60 % (range 36 %–84 %) is estimated to be due to BC, 31 % (12 %–49 %) is due to dust, and 11 % (0 %–24 %) is due to OA; however, the components are not independent in terms of their absorbing efficiency. In models with internal mixtures of absorbing aerosols, a major
challenge is the lack of a common and simple method to attribute absorption
to the different absorbing species. Therefore, when possible, the models
with internally mixed aerosols in the present study have performed
simulations using the same method for estimating absorption due to BC, OA,
and dust, namely by removing it and comparing runs with and without the
absorbing species. We discuss the challenges of attributing absorption to
different species; we compare burden, refractive indices, and density; and
we contrast models with internal mixing to models with external mixing. The
model mean BC mass absorption coefficient (MAC) value is 10.1 (3.1 to 17.7) m2 g−1 (550 nm), and the model mean BC AAOD is 0.0030 (0.0007 to
0.0077). The difference in lifetime (and burden) in the models explains as
much of the BC AAOD spread as the difference in BC MAC values. The
difference in the spectral dependency between the models is striking. Several models have an absorption Ångstrøm exponent (AAE) close to 1, which likely is too low given current knowledge of spectral aerosol optical properties. Most models do not account for brown carbon and underestimate the spectral dependency for OA.
Funder
Norges Forskningsråd
Publisher
Copernicus GmbH
Subject
Atmospheric Science
Reference75 articles.
1. Ackerman, A. S., Toon, O. B., Stevens, D. E., Heymsfield, A. J., Ramanathan,
V., and Welton, E. J.: Reduction of Tropical Cloudiness by Soot, Science,
288, 1042–1047, https://doi.org/10.1126/science.288.5468.1042, 2000. 2. Adebiyi, A. A. and Kok, J. F.: Climate models miss most of the coarse dust
in the atmosphere, Science Advances, 6, eaaz9507, https://doi.org/10.1126/sciadv.aaz9507,
2020. 3. Andreae, M. O. and Gelencsér, A.: Black carbon or brown carbon? The nature of light-absorbing carbonaceous aerosols, Atmos. Chem. Phys., 6, 3131–3148, https://doi.org/10.5194/acp-6-3131-2006, 2006. 4. Balkanski, Y., Schulz, M., Claquin, T., Moulin, C., and Ginoux, P.: Global
Emissions of Mineral Aerosol: Formulation and Validation using Satellite
Imagery, in: Emissions of
Atmospheric Trace Compounds, edited by: Granier, C., Artaxo, P., and Reeves, C. E., Springer, Dordrecht, 18, 239–267, https://doi.org/10.1007/978-1-4020-2167-1_6, 2004. 5. Bauer, S. E., Wright, D. L., Koch, D., Lewis, E. R., McGraw, R., Chang, L.-S., Schwartz, S. E., and Ruedy, R.: MATRIX (Multiconfiguration Aerosol TRacker of mIXing state): an aerosol microphysical module for global atmospheric models, Atmos. Chem. Phys., 8, 6003–6035, https://doi.org/10.5194/acp-8-6003-2008, 2008.
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