An AeroCom assessment of black carbon in Arctic snow and sea ice

Though many global aerosols models prognose surface deposition, only a few models have been used to directly simulate the radiative effect from black carbon (BC) deposition to snow and sea ice. Here, we apply aerosol deposition fields from 25 models contributing to two phases of the Aerosol Comparis...

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Published in:Atmospheric Chemistry and Physics
Main Authors: Jiao, C., Flanner, M. G., Balkanski, Y., Bauer, S. E., Bellouin, N., Berntsen, T. K., Bian, H., Carslaw, K. S., Chin, M., De Luca, N., Diehl, T., Ghan, S. J., Iversen, T., Kirkevåg, A., Koch, D., Liu, X., Mann, G. W., Penner, J. E., Pitari, G., Schulz, M., Seland, Ø., Skeie, R. B., Steenrod, S. D., Stier, P., Takemura, T., Tsigaridis, K., van Noije, T., Yun, Y., Zhang, K.
Format: Article in Journal/Newspaper
Language:English
Published: Copernicus Publications 2014
Subjects:
Online Access:https://doi.org/10.5194/acp-14-2399-2014
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collection Niedersächsisches Online-Archiv NOA
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language English
topic article
Verlagsveröffentlichung
spellingShingle article
Verlagsveröffentlichung
Jiao, C.
Flanner, M. G.
Balkanski, Y.
Bauer, S. E.
Bellouin, N.
Berntsen, T. K.
Bian, H.
Carslaw, K. S.
Chin, M.
De Luca, N.
Diehl, T.
Ghan, S. J.
Iversen, T.
Kirkevåg, A.
Koch, D.
Liu, X.
Mann, G. W.
Penner, J. E.
Pitari, G.
Schulz, M.
Seland, Ø.
Skeie, R. B.
Steenrod, S. D.
Stier, P.
Takemura, T.
Tsigaridis, K.
van Noije, T.
Yun, Y.
Zhang, K.
An AeroCom assessment of black carbon in Arctic snow and sea ice
topic_facet article
Verlagsveröffentlichung
description Though many global aerosols models prognose surface deposition, only a few models have been used to directly simulate the radiative effect from black carbon (BC) deposition to snow and sea ice. Here, we apply aerosol deposition fields from 25 models contributing to two phases of the Aerosol Comparisons between Observations and Models (AeroCom) project to simulate and evaluate within-snow BC concentrations and radiative effect in the Arctic. We accomplish this by driving the offline land and sea ice components of the Community Earth System Model with different deposition fields and meteorological conditions from 2004 to 2009, during which an extensive field campaign of BC measurements in Arctic snow occurred. We find that models generally underestimate BC concentrations in snow in northern Russia and Norway, while overestimating BC amounts elsewhere in the Arctic. Although simulated BC distributions in snow are poorly correlated with measurements, mean values are reasonable. The multi-model mean (range) bias in BC concentrations, sampled over the same grid cells, snow depths, and months of measurements, are −4.4 (−13.2 to +10.7) ng g−1 for an earlier phase of AeroCom models (phase I), and +4.1 (−13.0 to +21.4) ng g−1 for a more recent phase of AeroCom models (phase II), compared to the observational mean of 19.2 ng g−1. Factors determining model BC concentrations in Arctic snow include Arctic BC emissions, transport of extra-Arctic aerosols, precipitation, deposition efficiency of aerosols within the Arctic, and meltwater removal of particles in snow. Sensitivity studies show that the model–measurement evaluation is only weakly affected by meltwater scavenging efficiency because most measurements were conducted in non-melting snow. The Arctic (60–90° N) atmospheric residence time for BC in phase II models ranges from 3.7 to 23.2 days, implying large inter-model variation in local BC deposition efficiency. Combined with the fact that most Arctic BC deposition originates from extra-Arctic emissions, these results suggest that aerosol removal processes are a leading source of variation in model performance. The multi-model mean (full range) of Arctic radiative effect from BC in snow is 0.15 (0.07–0.25) W m−2 and 0.18 (0.06–0.28) W m−2 in phase I and phase II models, respectively. After correcting for model biases relative to observed BC concentrations in different regions of the Arctic, we obtain a multi-model mean Arctic radiative effect of 0.17 W m−2 for the combined AeroCom ensembles. Finally, there is a high correlation between modeled BC concentrations sampled over the observational sites and the Arctic as a whole, indicating that the field campaign provided a reasonable sample of the Arctic.
format Article in Journal/Newspaper
author Jiao, C.
Flanner, M. G.
Balkanski, Y.
Bauer, S. E.
Bellouin, N.
Berntsen, T. K.
Bian, H.
Carslaw, K. S.
Chin, M.
De Luca, N.
Diehl, T.
Ghan, S. J.
Iversen, T.
Kirkevåg, A.
Koch, D.
Liu, X.
Mann, G. W.
Penner, J. E.
Pitari, G.
Schulz, M.
Seland, Ø.
Skeie, R. B.
Steenrod, S. D.
Stier, P.
Takemura, T.
Tsigaridis, K.
van Noije, T.
Yun, Y.
Zhang, K.
author_facet Jiao, C.
Flanner, M. G.
Balkanski, Y.
Bauer, S. E.
Bellouin, N.
Berntsen, T. K.
Bian, H.
Carslaw, K. S.
Chin, M.
De Luca, N.
Diehl, T.
Ghan, S. J.
Iversen, T.
Kirkevåg, A.
Koch, D.
Liu, X.
Mann, G. W.
Penner, J. E.
Pitari, G.
Schulz, M.
Seland, Ø.
Skeie, R. B.
Steenrod, S. D.
Stier, P.
Takemura, T.
Tsigaridis, K.
van Noije, T.
Yun, Y.
Zhang, K.
author_sort Jiao, C.
title An AeroCom assessment of black carbon in Arctic snow and sea ice
title_short An AeroCom assessment of black carbon in Arctic snow and sea ice
title_full An AeroCom assessment of black carbon in Arctic snow and sea ice
title_fullStr An AeroCom assessment of black carbon in Arctic snow and sea ice
title_full_unstemmed An AeroCom assessment of black carbon in Arctic snow and sea ice
title_sort aerocom assessment of black carbon in arctic snow and sea ice
publisher Copernicus Publications
publishDate 2014
url https://doi.org/10.5194/acp-14-2399-2014
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https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00044743/acp-14-2399-2014.pdf
https://acp.copernicus.org/articles/14/2399/2014/acp-14-2399-2014.pdf
geographic Arctic
Norway
geographic_facet Arctic
Norway
genre Arctic
black carbon
Sea ice
genre_facet Arctic
black carbon
Sea ice
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spelling ftnonlinearchiv:oai:noa.gwlb.de:cop_mods_00045123 2023-05-15T14:33:13+02:00 An AeroCom assessment of black carbon in Arctic snow and sea ice Jiao, C. Flanner, M. G. Balkanski, Y. Bauer, S. E. Bellouin, N. Berntsen, T. K. Bian, H. Carslaw, K. S. Chin, M. De Luca, N. Diehl, T. Ghan, S. J. Iversen, T. Kirkevåg, A. Koch, D. Liu, X. Mann, G. W. Penner, J. E. Pitari, G. Schulz, M. Seland, Ø. Skeie, R. B. Steenrod, S. D. Stier, P. Takemura, T. Tsigaridis, K. van Noije, T. Yun, Y. Zhang, K. 2014-03 electronic https://doi.org/10.5194/acp-14-2399-2014 https://noa.gwlb.de/receive/cop_mods_00045123 https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00044743/acp-14-2399-2014.pdf https://acp.copernicus.org/articles/14/2399/2014/acp-14-2399-2014.pdf eng eng Copernicus Publications Atmospheric Chemistry and Physics -- http://www.atmos-chem-phys.net/volumes_and_issues.html -- http://www.bibliothek.uni-regensburg.de/ezeit/?2069847 -- 1680-7324 https://doi.org/10.5194/acp-14-2399-2014 https://noa.gwlb.de/receive/cop_mods_00045123 https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00044743/acp-14-2399-2014.pdf https://acp.copernicus.org/articles/14/2399/2014/acp-14-2399-2014.pdf uneingeschränkt info:eu-repo/semantics/openAccess article Verlagsveröffentlichung article Text doc-type:article 2014 ftnonlinearchiv https://doi.org/10.5194/acp-14-2399-2014 2022-02-08T22:39:42Z Though many global aerosols models prognose surface deposition, only a few models have been used to directly simulate the radiative effect from black carbon (BC) deposition to snow and sea ice. Here, we apply aerosol deposition fields from 25 models contributing to two phases of the Aerosol Comparisons between Observations and Models (AeroCom) project to simulate and evaluate within-snow BC concentrations and radiative effect in the Arctic. We accomplish this by driving the offline land and sea ice components of the Community Earth System Model with different deposition fields and meteorological conditions from 2004 to 2009, during which an extensive field campaign of BC measurements in Arctic snow occurred. We find that models generally underestimate BC concentrations in snow in northern Russia and Norway, while overestimating BC amounts elsewhere in the Arctic. Although simulated BC distributions in snow are poorly correlated with measurements, mean values are reasonable. The multi-model mean (range) bias in BC concentrations, sampled over the same grid cells, snow depths, and months of measurements, are −4.4 (−13.2 to +10.7) ng g−1 for an earlier phase of AeroCom models (phase I), and +4.1 (−13.0 to +21.4) ng g−1 for a more recent phase of AeroCom models (phase II), compared to the observational mean of 19.2 ng g−1. Factors determining model BC concentrations in Arctic snow include Arctic BC emissions, transport of extra-Arctic aerosols, precipitation, deposition efficiency of aerosols within the Arctic, and meltwater removal of particles in snow. Sensitivity studies show that the model–measurement evaluation is only weakly affected by meltwater scavenging efficiency because most measurements were conducted in non-melting snow. The Arctic (60–90° N) atmospheric residence time for BC in phase II models ranges from 3.7 to 23.2 days, implying large inter-model variation in local BC deposition efficiency. Combined with the fact that most Arctic BC deposition originates from extra-Arctic emissions, these results suggest that aerosol removal processes are a leading source of variation in model performance. The multi-model mean (full range) of Arctic radiative effect from BC in snow is 0.15 (0.07–0.25) W m−2 and 0.18 (0.06–0.28) W m−2 in phase I and phase II models, respectively. After correcting for model biases relative to observed BC concentrations in different regions of the Arctic, we obtain a multi-model mean Arctic radiative effect of 0.17 W m−2 for the combined AeroCom ensembles. Finally, there is a high correlation between modeled BC concentrations sampled over the observational sites and the Arctic as a whole, indicating that the field campaign provided a reasonable sample of the Arctic. Article in Journal/Newspaper Arctic black carbon Sea ice Niedersächsisches Online-Archiv NOA Arctic Norway Atmospheric Chemistry and Physics 14 5 2399 2417