Seasonality of global and Arctic black carbon processes in the Arctic Monitoring and Assessment Programme models
This study quantifies black carbon (BC) processes in three global climate models and one chemistry transport model, with focus on the seasonality of BC transport, emissions, wet and dry deposition in the Arctic. In the models, transport of BC to the Arctic from lower latitudes is the major BC source...
Published in: | Journal of Geophysical Research: Atmospheres |
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Main Authors: | , , , , , , |
Format: | Article in Journal/Newspaper |
Language: | unknown |
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Wiley Periodicals, Inc.
2016
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Subjects: | |
Online Access: | https://hdl.handle.net/2027.42/133539 https://doi.org/10.1002/2016JD024849 |
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ftumdeepblue:oai:deepblue.lib.umich.edu:2027.42/133539 |
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record_format |
openpolar |
institution |
Open Polar |
collection |
University of Michigan: Deep Blue |
op_collection_id |
ftumdeepblue |
language |
unknown |
topic |
black carbon budgets Arctic pollution aerosols wet scavenging transport Atmospheric and Oceanic Sciences Science |
spellingShingle |
black carbon budgets Arctic pollution aerosols wet scavenging transport Atmospheric and Oceanic Sciences Science Mahmood, Rashed Salzen, Knut Flanner, Mark Sand, Maria Langner, Joakim Wang, Hailong Huang, Lin Seasonality of global and Arctic black carbon processes in the Arctic Monitoring and Assessment Programme models |
topic_facet |
black carbon budgets Arctic pollution aerosols wet scavenging transport Atmospheric and Oceanic Sciences Science |
description |
This study quantifies black carbon (BC) processes in three global climate models and one chemistry transport model, with focus on the seasonality of BC transport, emissions, wet and dry deposition in the Arctic. In the models, transport of BC to the Arctic from lower latitudes is the major BC source for this region. Arctic emissions are very small. All models simulated a similar annual cycle of BC transport from lower latitudes to the Arctic, with maximum transport occurring in July. Substantial differences were found in simulated BC burdens and vertical distributions, with Canadian Atmospheric Global Climate Model (CanAM) (Norwegian Earth System Model, NorESM) producing the strongest (weakest) seasonal cycle. CanAM also has the shortest annual mean residence time for BC in the Arctic followed by Swedish Meteorological and Hydrological Institute Multiscale Atmospheric Transport and Chemistry model, Community Earth System Model, and NorESM. Overall, considerable differences in wet deposition efficiencies in the models exist and are a leading cause of differences in simulated BC burdens. Results from model sensitivity experiments indicate that convective scavenging outside the Arctic reduces the mean altitude of BC residing in the Arctic, making it more susceptible to scavenging by stratiform (layer) clouds in the Arctic. Consequently, scavenging of BC in convective clouds outside the Arctic acts to substantially increase the overall efficiency of BC wet deposition in the Arctic, which leads to low BC burdens and a more pronounced seasonal cycle compared to simulations without convective BC scavenging. In contrast, the simulated seasonality of BC concentrations in the upper troposphere is only weakly influenced by wet deposition in stratiform clouds, whereas lower tropospheric concentrations are highly sensitive.Key PointsSeasonal variations of black carbon (BC) mass budgets in the Arctic are simulatedGood agreement in simulated annual mean transport of BC to the Arctic in modelsConvective wet removal is important ... |
format |
Article in Journal/Newspaper |
author |
Mahmood, Rashed Salzen, Knut Flanner, Mark Sand, Maria Langner, Joakim Wang, Hailong Huang, Lin |
author_facet |
Mahmood, Rashed Salzen, Knut Flanner, Mark Sand, Maria Langner, Joakim Wang, Hailong Huang, Lin |
author_sort |
Mahmood, Rashed |
title |
Seasonality of global and Arctic black carbon processes in the Arctic Monitoring and Assessment Programme models |
title_short |
Seasonality of global and Arctic black carbon processes in the Arctic Monitoring and Assessment Programme models |
title_full |
Seasonality of global and Arctic black carbon processes in the Arctic Monitoring and Assessment Programme models |
title_fullStr |
Seasonality of global and Arctic black carbon processes in the Arctic Monitoring and Assessment Programme models |
title_full_unstemmed |
Seasonality of global and Arctic black carbon processes in the Arctic Monitoring and Assessment Programme models |
title_sort |
seasonality of global and arctic black carbon processes in the arctic monitoring and assessment programme models |
publisher |
Wiley Periodicals, Inc. |
publishDate |
2016 |
url |
https://hdl.handle.net/2027.42/133539 https://doi.org/10.1002/2016JD024849 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic Arctic Arctic pollution black carbon |
genre_facet |
Arctic Arctic Arctic pollution black carbon |
op_relation |
Mahmood, Rashed; Salzen, Knut; Flanner, Mark; Sand, Maria; Langner, Joakim; Wang, Hailong; Huang, Lin (2016). "Seasonality of global and Arctic black carbon processes in the Arctic Monitoring and Assessment Programme models." Journal of Geophysical Research: Atmospheres 121(12): 7100-7116. 2169-897X 2169-8996 https://hdl.handle.net/2027.42/133539 doi:10.1002/2016JD024849 Journal of Geophysical Research: Atmospheres Robertson, L., J. Langner, and M. Engardt ( 1999 ), An Eulerian limited‐area atmospheric transport model, J. Appl. Meteorol., 38, 190 – 210. Liu, X., et al. ( 2012 ), Toward a minimal representation of aerosols in climate models: Description and evaluation in the Community Atmosphere Model CAM5, Geosci. Model Dev., 5, 709 – 739, doi:10.5194/gmd-5-709-2012. Liu, X., P.‐L. Ma, H. Wang, S. Tilmes, B. Singh, R. C. Easter, S. J. Ghan, and P. J. Rasch ( 2016 ), Description and evaluation of a new 4‐mode version of Modal Aerosol Module (MAM4) within version 5.3 of the Community Atmosphere Model, Geosci. Model Dev., 9, 505 – 522, doi:10.5194/gmd-9-505-2016. Ma, P.‐L., P. J. Rasch, H. Wang, K. Zhang, R. C. Easter, S. Tilmes, J. D. Fast, X. Liu, J.‐H. Yoon, and J.‐F. Lamarque ( 2013 ), The role of circulation features on black carbon transport into the Arctic in the Community Atmosphere Model version 5 (CAM5), J. Geophys. Res. Atmos., 118, 4657 – 4669, doi:10.1002/jgrd.50411. Ma, P.‐L., P. J. Rasch, J. D. Fast, R. C. Easter, W. I. Gustafson Jr., X. Liu, S. J. Ghan, and B. Singh ( 2014 ), Assessing the CAM5 physics suite in the WRF‐Chem model: Implementation, resolution sensitivity, and a first evaluation for a regional case study, Geosci. Model Dev., 7, 755 – 778, doi:10.5194/gmd-7-755-2014. Neale, R. B., et al. ( 2012 ), Description of the NCAR Community Atmosphere Model (CAM5.0), NCAR Tech. Note. [Available at http://www.cesm.ucar.edu/models/cesm1.0/cam/docs/description/cam5_desc.pdf.] Ramshaw, J. D. ( 1985 ), Conservative rezoning algorithm for generalized two‐dimensional meshes, J. Comp. Phys., 59, 193 – 199, doi:10.1016/0021-9991(85)90141-X. Rasch, P. J., M. C. Barth, J. T. Kiehl, S. E. Schwartz, and C. M. Benkovitz ( 2000 ), A description of the global sulfur cycle and its controlling processes in the National Center for Atmospheric Research Community Climate Model, version 3, J. Geophys. Res., 105, 1367 – 1385, doi:10.1029/1999JD900777. Real, E., et al. ( 2010 ), Cross‐hemispheric transport of central African biomass burning pollutants: Implications for downwind ozone production, Atmos. Chem. Phys., 10, 3027 – 3046. Samset, B. H., et al. ( 2014 ), Modelled black carbon radiative forcing and atmospheric lifetime in AeroCom phase II constrained by aircraft observations, Atmos. Chem. Phys., 14, 12,465 – 12,477, doi:10.5194/acp-14-12465-2014. Sand, M., T. K. Berntsen, Ø. Seland, and J. E. Kristja ́nsson ( 2013 ), Arctic surface temperature change to emissions of black carbon within Arctic or midlatitudes, J. Geophys. Res. Atmos., 118, 7788 – 7798, doi:10.1002/jgrd.50613. Sand, M., T. Berntsen, K. von Salzen, M. Flanner, J. Langner, and D. Victor ( 2015 ), Response of Arctic temperature to changes in emissions of short‐lived climate forcers, Nat. Clim. Change, doi:10.1038/NCLIMATE2880. Sawa, Y., T. Machida, and H. Matsueda ( 2012 ), Aircraft observation of the seasonal variation in the transport of CO 2 in the upper atmosphere, J. Geophys. Res., 117, D05305, doi:10.1029/2011JD016933. Seland, Ø., T. Iversen, A. Kirkevag, and T. Storelvmo ( 2008 ), Aerosol‐climate interactions in the CAM‐Oslo atmospheric GCM and investigations of associated shortcomings, Tellus Ser.A, 60, 459 – 491. Sharma, S., E. Andrews, L. A. Barrie, J. A. Ogren, and D. Lavoué ( 2006 ), Variations and sources of the equivalent black carbon in the high Arctic revealed by long‐term observations at Alert and Barrow: 1989–2003, J. Geophys. Res., 111, D14208, doi:10.1029/2005JD006581. Shindell, D. T., et al. ( 2008 ), A multi‐model assessment of pollution transport to the Arctic, Atmos. Chem. Phys., 8, 5353 – 5372, doi:10.5194/acp-8-5353-2008. Staudt, A. C., D. J. Jacob, J. A. Logan, D. Bachiochi, T. N. Krishnamurti, and G. W. Sachse ( 2001 ), Continental sources, transoceanic transport, and interhemispheric exchange of carbon monoxide over the Pacific, J. Geophys. Res., 106, 32,571 – 32,589, doi:10.1029/2001JD900078. Stohl, A. ( 2006 ), Characteristics of atmospheric transport into the Arctic troposphere, J. Geophys. Res., 111, D11306, doi:10.1029/2005JD006888. Stohl, A., et al. ( 2015 ), Evaluating the climate and air quality impacts of short‐lived pollutants, Atmos. Chem. Phys., 15, 10,529 – 10,566, doi:10.5194/acp-15-10529-2015. Sudo, K., and H. Akimoto ( 2007 ), Global source attribution of tropospheric ozone: Long‐range transport from various source regions, J. Geophys. Res., 112, D12302, doi:10.1029/2006JD007992. van der Werf, G. R., J. T. Randerson, L. Giglio, G. J. Collatz, M. Mu, P. S. Kasibhatla, D. C. Morton, R. S. DeFries, Y. Jin, and T. T. van Leeuwen ( 2010 ), Global fire emissions and the contribution of deforestation, savanna, forest, agricultural, and peat fires (1997–2009), Atmos. Chem. Phys., 10, 11,707 – 11,735, doi:10.5194/acp-10-11707-2010. Vignati, E., M. Karl, M. Krol, J. Wilson, P. Stier, and F. Cavalli ( 2010 ), Sources of uncertainties in modeling black carbon at global scale, Atmos. Chem. Phys., 10, 2595 – 2611. von Salzen, K. ( 2006 ), Piecewise log‐normal approximation of size distributions for aerosol modelling, Atmos. Chem. Phys., 6, 1351 – 1372. von Salzen, K., H. G. Leighton, P. A. Ariya, L. A. Barrie, S. L. Gong, J.‐P. Blanchet, L. Spacek, U. Lohmann, and L. I. Kleinman ( 2000 ), Sensitivity of sulphate aerosol size distributions and CCN concentrations over North America to SO x emissions and H 2 O 2 concentrations, J. Geophys. Res., 105, 9741 – 9765, doi:10.1029/2000JD900027. von Salzen, K., et al. ( 2013 ), The Canadian Fourth Generation Atmospheric Global Climate Model (CanAM4). Part I: Representation of physical processes, Atmos. Ocean, 51, 104 – 125, doi:10.1080/07055900.2012.755610. Wang, H., R. C. Easter, P. J. Rasch, M. Wang, X. Liu, S. J. Ghan, Y. Qian, J.‐H. Yoon, P.‐L. Ma, and V. Vinoj ( 2013 ), Sensitivity of remote aerosol distributions to representation of cloud‐aerosol interactions in a global climate model, Geosci. Model Dev., 6, 765 – 782, doi:10.5194/gmd-6-765-2013. Wang, H., P. J. Rasch, R. C. Easter, B. Singh, R. Zhang, P.‐L. Ma, Y. Qian, S. J. Ghan, and N. Beagley ( 2014 ), Using an explicit emission tagging method in global modeling of source‐receptor relationships for black carbon in the Arctic: Variations, sources, and transport pathways, J. Geophys. Res. Atmos., 119, 12,888 – 12,909, doi:10.1002/2014JD022297. Allen, R. J., and W. Landuyt ( 2014 ), The vertical distribution of black carbon in CMIP5 models: Comparison to observations and the importance of convective transport, J. Geophys. Res. Atmos., 119, 4808 – 4835, doi:10.1002/2014JD021595. AMAP ( 2015 ), AMAP Assessment 2015: Black carbon and ozone as Arctic climate forcers. Arctic Monitoring and Assessment Programme (AMAP), Oslo, Norway. vii + 116 pp. [Available at http://www.amap.no/documents/doc/AMAP‐Assessment‐2015‐Black‐carbon‐and‐ozone‐as‐Arctic‐climate‐forcers/1299.] Andersson, C., J. Langner, and R. Bergstrom ( 2007 ), Interannual variation and trends in air pollution over Europe due to climate variability during 1958–2001 simulated with a regional CTM coupled to the ERA40 reanalysis, Tellus Ser. B, 59, 77 – 98, doi:10.1111/j.1600-0889.2006.00196.x. Barrie, L. A. ( 1986 ), Arctic air pollution—An overview of current knowledge, Atmos. Environ., 20, 643 – 663. Barth, M. C., P. J. Rasch, J. T. Kiehl, C. M. Benkovitz, and S. E. Schwartz ( 2000 ), Sulfur chemistry in the National Center for Atmospheric Research Community Climate Model: Description, evaluation, features and sensitivity to aqueous chemistry, J. Geophys. Res., 105, 1387 – 1415, doi:10.1029/1999JD900773. Bentsen, M., et al. ( 2013 ), The Norwegian Earth System Model, NorESM1‐M—Part 1: Description and basic evaluation of the physical climate, Geosci. Model Dev., 6, 687 – 720, doi:10.5194/gmd-6-687-2013. Bond, T. C., D. G. Streets, K. F. Yarber, S. M. Nelson, J. H. Woo, and Z. Klimont ( 2004 ), A technology‐based global inventory of black and organic carbon emissions from combustion, J. Geophys. Res., 109, D14203, doi:10.1029/2003JD003697. Bond, T. C., et al. ( 2013 ), Bounding the role of black carbon in the climate system: A scientific assessment, J. Geophys. Res. Atmos., 118, 5380 – 5552, doi:10.1002/jgrd.50171. Boucher, O., et al. ( 2013 ), Clouds and aerosols, in Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, edited by T. F. Stocker et al., Cambridge Univ. Press, Cambridge, U. K., and New York. Browse, J., K. S. Carslaw, S. R. Arnold, K. Pringle, and O. Boucher ( 2012 ), The scavenging processes controlling the seasonal cycle in Arctic sulphate and black carbon aerosol, Atmos. Chem. Phys., 12, 6775 – 6798, doi:10.5194/acp-12-6775-2012. Eckhardt, S., et al. 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Nazarenko ( 2004 ), Soot climate forcing via snow and ice albedos, Proc. Natl. Acad. Sci. U.S.A., 101 ( 2 ), 423 – 428, doi:10.1073/pnas.2237157100. Hansen, J., M. Sato, and R. Ruedy ( 1997 ), Radiative forcing and climate response, J. Geophys. Res., 102, 6831 – 6864, doi:10.1029/96JD03436. Hodnebrog, Ø., G. Myhre, and B. H. Samset ( 2014 ), How shorter black carbon lifetime alters its climate effect, Nat. Commun., 5, 5065, doi:10.1038/ncomms6065. |
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ftumdeepblue:oai:deepblue.lib.umich.edu:2027.42/133539 2023-08-20T04:03:06+02:00 Seasonality of global and Arctic black carbon processes in the Arctic Monitoring and Assessment Programme models Mahmood, Rashed Salzen, Knut Flanner, Mark Sand, Maria Langner, Joakim Wang, Hailong Huang, Lin 2016-06-27 application/pdf https://hdl.handle.net/2027.42/133539 https://doi.org/10.1002/2016JD024849 unknown Wiley Periodicals, Inc. Cambridge Univ. Press Mahmood, Rashed; Salzen, Knut; Flanner, Mark; Sand, Maria; Langner, Joakim; Wang, Hailong; Huang, Lin (2016). "Seasonality of global and Arctic black carbon processes in the Arctic Monitoring and Assessment Programme models." Journal of Geophysical Research: Atmospheres 121(12): 7100-7116. 2169-897X 2169-8996 https://hdl.handle.net/2027.42/133539 doi:10.1002/2016JD024849 Journal of Geophysical Research: Atmospheres Robertson, L., J. Langner, and M. Engardt ( 1999 ), An Eulerian limited‐area atmospheric transport model, J. Appl. Meteorol., 38, 190 – 210. Liu, X., et al. ( 2012 ), Toward a minimal representation of aerosols in climate models: Description and evaluation in the Community Atmosphere Model CAM5, Geosci. Model Dev., 5, 709 – 739, doi:10.5194/gmd-5-709-2012. Liu, X., P.‐L. Ma, H. Wang, S. Tilmes, B. Singh, R. C. Easter, S. J. Ghan, and P. J. Rasch ( 2016 ), Description and evaluation of a new 4‐mode version of Modal Aerosol Module (MAM4) within version 5.3 of the Community Atmosphere Model, Geosci. Model Dev., 9, 505 – 522, doi:10.5194/gmd-9-505-2016. Ma, P.‐L., P. J. Rasch, H. Wang, K. Zhang, R. C. Easter, S. Tilmes, J. D. Fast, X. Liu, J.‐H. Yoon, and J.‐F. Lamarque ( 2013 ), The role of circulation features on black carbon transport into the Arctic in the Community Atmosphere Model version 5 (CAM5), J. Geophys. Res. Atmos., 118, 4657 – 4669, doi:10.1002/jgrd.50411. Ma, P.‐L., P. J. Rasch, J. D. Fast, R. C. Easter, W. I. Gustafson Jr., X. Liu, S. J. Ghan, and B. Singh ( 2014 ), Assessing the CAM5 physics suite in the WRF‐Chem model: Implementation, resolution sensitivity, and a first evaluation for a regional case study, Geosci. Model Dev., 7, 755 – 778, doi:10.5194/gmd-7-755-2014. Neale, R. B., et al. ( 2012 ), Description of the NCAR Community Atmosphere Model (CAM5.0), NCAR Tech. Note. [Available at http://www.cesm.ucar.edu/models/cesm1.0/cam/docs/description/cam5_desc.pdf.] Ramshaw, J. D. ( 1985 ), Conservative rezoning algorithm for generalized two‐dimensional meshes, J. Comp. Phys., 59, 193 – 199, doi:10.1016/0021-9991(85)90141-X. Rasch, P. J., M. C. Barth, J. T. Kiehl, S. E. Schwartz, and C. M. Benkovitz ( 2000 ), A description of the global sulfur cycle and its controlling processes in the National Center for Atmospheric Research Community Climate Model, version 3, J. Geophys. Res., 105, 1367 – 1385, doi:10.1029/1999JD900777. Real, E., et al. ( 2010 ), Cross‐hemispheric transport of central African biomass burning pollutants: Implications for downwind ozone production, Atmos. Chem. Phys., 10, 3027 – 3046. Samset, B. H., et al. ( 2014 ), Modelled black carbon radiative forcing and atmospheric lifetime in AeroCom phase II constrained by aircraft observations, Atmos. Chem. Phys., 14, 12,465 – 12,477, doi:10.5194/acp-14-12465-2014. Sand, M., T. K. Berntsen, Ø. Seland, and J. E. Kristja ́nsson ( 2013 ), Arctic surface temperature change to emissions of black carbon within Arctic or midlatitudes, J. Geophys. Res. Atmos., 118, 7788 – 7798, doi:10.1002/jgrd.50613. Sand, M., T. Berntsen, K. von Salzen, M. Flanner, J. Langner, and D. Victor ( 2015 ), Response of Arctic temperature to changes in emissions of short‐lived climate forcers, Nat. Clim. Change, doi:10.1038/NCLIMATE2880. Sawa, Y., T. Machida, and H. Matsueda ( 2012 ), Aircraft observation of the seasonal variation in the transport of CO 2 in the upper atmosphere, J. Geophys. Res., 117, D05305, doi:10.1029/2011JD016933. Seland, Ø., T. Iversen, A. Kirkevag, and T. Storelvmo ( 2008 ), Aerosol‐climate interactions in the CAM‐Oslo atmospheric GCM and investigations of associated shortcomings, Tellus Ser.A, 60, 459 – 491. Sharma, S., E. Andrews, L. A. Barrie, J. A. Ogren, and D. Lavoué ( 2006 ), Variations and sources of the equivalent black carbon in the high Arctic revealed by long‐term observations at Alert and Barrow: 1989–2003, J. Geophys. Res., 111, D14208, doi:10.1029/2005JD006581. Shindell, D. T., et al. ( 2008 ), A multi‐model assessment of pollution transport to the Arctic, Atmos. Chem. Phys., 8, 5353 – 5372, doi:10.5194/acp-8-5353-2008. Staudt, A. C., D. J. Jacob, J. A. Logan, D. Bachiochi, T. N. Krishnamurti, and G. W. Sachse ( 2001 ), Continental sources, transoceanic transport, and interhemispheric exchange of carbon monoxide over the Pacific, J. Geophys. Res., 106, 32,571 – 32,589, doi:10.1029/2001JD900078. Stohl, A. ( 2006 ), Characteristics of atmospheric transport into the Arctic troposphere, J. Geophys. Res., 111, D11306, doi:10.1029/2005JD006888. Stohl, A., et al. ( 2015 ), Evaluating the climate and air quality impacts of short‐lived pollutants, Atmos. Chem. Phys., 15, 10,529 – 10,566, doi:10.5194/acp-15-10529-2015. Sudo, K., and H. Akimoto ( 2007 ), Global source attribution of tropospheric ozone: Long‐range transport from various source regions, J. Geophys. Res., 112, D12302, doi:10.1029/2006JD007992. van der Werf, G. R., J. T. Randerson, L. Giglio, G. J. Collatz, M. Mu, P. S. Kasibhatla, D. C. Morton, R. S. DeFries, Y. Jin, and T. T. van Leeuwen ( 2010 ), Global fire emissions and the contribution of deforestation, savanna, forest, agricultural, and peat fires (1997–2009), Atmos. Chem. Phys., 10, 11,707 – 11,735, doi:10.5194/acp-10-11707-2010. Vignati, E., M. Karl, M. Krol, J. Wilson, P. Stier, and F. Cavalli ( 2010 ), Sources of uncertainties in modeling black carbon at global scale, Atmos. Chem. Phys., 10, 2595 – 2611. von Salzen, K. ( 2006 ), Piecewise log‐normal approximation of size distributions for aerosol modelling, Atmos. Chem. Phys., 6, 1351 – 1372. von Salzen, K., H. G. Leighton, P. A. Ariya, L. A. Barrie, S. L. Gong, J.‐P. Blanchet, L. Spacek, U. Lohmann, and L. I. Kleinman ( 2000 ), Sensitivity of sulphate aerosol size distributions and CCN concentrations over North America to SO x emissions and H 2 O 2 concentrations, J. Geophys. Res., 105, 9741 – 9765, doi:10.1029/2000JD900027. von Salzen, K., et al. ( 2013 ), The Canadian Fourth Generation Atmospheric Global Climate Model (CanAM4). Part I: Representation of physical processes, Atmos. Ocean, 51, 104 – 125, doi:10.1080/07055900.2012.755610. Wang, H., R. C. Easter, P. J. Rasch, M. Wang, X. Liu, S. J. Ghan, Y. Qian, J.‐H. Yoon, P.‐L. Ma, and V. Vinoj ( 2013 ), Sensitivity of remote aerosol distributions to representation of cloud‐aerosol interactions in a global climate model, Geosci. Model Dev., 6, 765 – 782, doi:10.5194/gmd-6-765-2013. Wang, H., P. J. Rasch, R. C. Easter, B. Singh, R. Zhang, P.‐L. Ma, Y. Qian, S. J. Ghan, and N. Beagley ( 2014 ), Using an explicit emission tagging method in global modeling of source‐receptor relationships for black carbon in the Arctic: Variations, sources, and transport pathways, J. Geophys. Res. Atmos., 119, 12,888 – 12,909, doi:10.1002/2014JD022297. Allen, R. J., and W. Landuyt ( 2014 ), The vertical distribution of black carbon in CMIP5 models: Comparison to observations and the importance of convective transport, J. Geophys. Res. Atmos., 119, 4808 – 4835, doi:10.1002/2014JD021595. AMAP ( 2015 ), AMAP Assessment 2015: Black carbon and ozone as Arctic climate forcers. Arctic Monitoring and Assessment Programme (AMAP), Oslo, Norway. vii + 116 pp. [Available at http://www.amap.no/documents/doc/AMAP‐Assessment‐2015‐Black‐carbon‐and‐ozone‐as‐Arctic‐climate‐forcers/1299.] Andersson, C., J. Langner, and R. Bergstrom ( 2007 ), Interannual variation and trends in air pollution over Europe due to climate variability during 1958–2001 simulated with a regional CTM coupled to the ERA40 reanalysis, Tellus Ser. B, 59, 77 – 98, doi:10.1111/j.1600-0889.2006.00196.x. Barrie, L. A. ( 1986 ), Arctic air pollution—An overview of current knowledge, Atmos. Environ., 20, 643 – 663. Barth, M. C., P. J. Rasch, J. T. Kiehl, C. M. Benkovitz, and S. E. Schwartz ( 2000 ), Sulfur chemistry in the National Center for Atmospheric Research Community Climate Model: Description, evaluation, features and sensitivity to aqueous chemistry, J. Geophys. Res., 105, 1387 – 1415, doi:10.1029/1999JD900773. Bentsen, M., et al. ( 2013 ), The Norwegian Earth System Model, NorESM1‐M—Part 1: Description and basic evaluation of the physical climate, Geosci. Model Dev., 6, 687 – 720, doi:10.5194/gmd-6-687-2013. Bond, T. C., D. G. Streets, K. F. Yarber, S. M. Nelson, J. H. Woo, and Z. Klimont ( 2004 ), A technology‐based global inventory of black and organic carbon emissions from combustion, J. Geophys. Res., 109, D14203, doi:10.1029/2003JD003697. Bond, T. C., et al. ( 2013 ), Bounding the role of black carbon in the climate system: A scientific assessment, J. Geophys. Res. Atmos., 118, 5380 – 5552, doi:10.1002/jgrd.50171. Boucher, O., et al. ( 2013 ), Clouds and aerosols, in Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, edited by T. F. Stocker et al., Cambridge Univ. Press, Cambridge, U. K., and New York. Browse, J., K. S. Carslaw, S. R. Arnold, K. Pringle, and O. 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IndexNoFollow black carbon budgets Arctic pollution aerosols wet scavenging transport Atmospheric and Oceanic Sciences Science Article 2016 ftumdeepblue https://doi.org/10.1002/2016JD02484910.5194/gmd-5-709-201210.5194/gmd-9-505-201610.1002/jgrd.5041110.5194/gmd-7-755-201410.1016/0021-9991(85)90141-X10.1029/1999JD90077710.5194/acp-14-12465-201410.1002/jgrd.5061310.1038/NCLIMATE288010.1029/2011JD01693310.1 2023-07-31T21:20:31Z This study quantifies black carbon (BC) processes in three global climate models and one chemistry transport model, with focus on the seasonality of BC transport, emissions, wet and dry deposition in the Arctic. In the models, transport of BC to the Arctic from lower latitudes is the major BC source for this region. Arctic emissions are very small. All models simulated a similar annual cycle of BC transport from lower latitudes to the Arctic, with maximum transport occurring in July. Substantial differences were found in simulated BC burdens and vertical distributions, with Canadian Atmospheric Global Climate Model (CanAM) (Norwegian Earth System Model, NorESM) producing the strongest (weakest) seasonal cycle. CanAM also has the shortest annual mean residence time for BC in the Arctic followed by Swedish Meteorological and Hydrological Institute Multiscale Atmospheric Transport and Chemistry model, Community Earth System Model, and NorESM. Overall, considerable differences in wet deposition efficiencies in the models exist and are a leading cause of differences in simulated BC burdens. Results from model sensitivity experiments indicate that convective scavenging outside the Arctic reduces the mean altitude of BC residing in the Arctic, making it more susceptible to scavenging by stratiform (layer) clouds in the Arctic. Consequently, scavenging of BC in convective clouds outside the Arctic acts to substantially increase the overall efficiency of BC wet deposition in the Arctic, which leads to low BC burdens and a more pronounced seasonal cycle compared to simulations without convective BC scavenging. In contrast, the simulated seasonality of BC concentrations in the upper troposphere is only weakly influenced by wet deposition in stratiform clouds, whereas lower tropospheric concentrations are highly sensitive.Key PointsSeasonal variations of black carbon (BC) mass budgets in the Arctic are simulatedGood agreement in simulated annual mean transport of BC to the Arctic in modelsConvective wet removal is important ... Article in Journal/Newspaper Arctic Arctic Arctic pollution black carbon University of Michigan: Deep Blue Arctic Journal of Geophysical Research: Atmospheres 121 12 7100 7116 |