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Volume 13, issue 4
Atmos. Chem. Phys., 13, 1853–1877, 2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
Atmos. Chem. Phys., 13, 1853–1877, 2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 19 Feb 2013

Research article | 19 Feb 2013

Radiative forcing of the direct aerosol effect from AeroCom Phase II simulations

G. Myhre1, B. H. Samset1, M. Schulz2, Y. Balkanski3, S. Bauer4, T. K. Berntsen1, H. Bian5, N. Bellouin6,*, M. Chin7, T. Diehl7,8, R. C. Easter9, J. Feichter10, S. J. Ghan9, D. Hauglustaine3, T. Iversen2,11, S. Kinne10, A. Kirkevåg2, J.-F. Lamarque12, G. Lin13, X. Liu8, M. T. Lund1, G. Luo14, X. Ma14, T. van Noije15, J. E. Penner13, P. J. Rasch9, A. Ruiz15,16, Ø. Seland2, R. B. Skeie1, P. Stier17, T. Takemura18, K. Tsigaridis4, P. Wang15, Z. Wang19, L. Xu13,20, H. Yu5, F. Yu14, J.-H. Yoon9, K. Zhang9,10, H. Zhang21, and C. Zhou13 G. Myhre et al.
  • 1Center for International Climate and Environmental Research – Oslo (CICERO), Oslo, Norway
  • 2Norwegian Meteorological Institute, Oslo, Norway
  • 3Laboratoire des Sciences du Climat et de l'Environnement, CEA-CNRS-UVSQ, Gif-sur-Yvette, France
  • 4NASA Goddard Institute for Space Studies and Columbia Earth Institute, New York, NY, USA
  • 5Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD, USA
  • 6Met Office Hadley Centre, Exeter, UK
  • 7NASA Goddard Space Flight Center, Greenbelt, MD, USA
  • 8Universities Space Research Association, Columbia, MD, USA
  • 9Pacific Northwest National Laboratory, Richland, WA, USA
  • 10Max Planck Institute for Meteorology, Hamburg, Germany
  • 11Department of Geosciences, University of Oslo, Oslo, Norway
  • 12NCAR Earth System Laboratory, National Center for Atmospheric Research, Boulder, CO, USA
  • 13Department of Atmospheric, Oceanic, and Space Sciences, University of Michigan, Ann Arbor, Michigan, USA
  • 14Atmospheric Sciences Research Center, State University of New York at Albany, New York, USA
  • 15Royal Netherlands Meteorological Institute, De Bilt, The Netherlands
  • 16LIFTEC, CSIC-Universidad de Zaragoza, Zaragoza, Spain
  • 17Department of Physics, University of Oxford, Oxford, UK
  • 18Research Institute for Applied Mechanics, Kyushu University, Fukuoka, Japan
  • 19Chinese Academy of Meteorological Sciences, Beijing 100081, China
  • 20Scripps Institution of Oceanography, University of California, San Diego, La Jolla, California, USA
  • 21Laboratory for Climate Studies, National Climate Center, China Meteorological Administration, Beijing 100081, China
  • *now at: Department of Meteorology, University of Reading, Reading, UK

Abstract. We report on the AeroCom Phase II direct aerosol effect (DAE) experiment where 16 detailed global aerosol models have been used to simulate the changes in the aerosol distribution over the industrial era. All 16 models have estimated the radiative forcing (RF) of the anthropogenic DAE, and have taken into account anthropogenic sulphate, black carbon (BC) and organic aerosols (OA) from fossil fuel, biofuel, and biomass burning emissions. In addition several models have simulated the DAE of anthropogenic nitrate and anthropogenic influenced secondary organic aerosols (SOA). The model simulated all-sky RF of the DAE from total anthropogenic aerosols has a range from −0.58 to −0.02 Wm−2, with a mean of −0.27 Wm−2 for the 16 models. Several models did not include nitrate or SOA and modifying the estimate by accounting for this with information from the other AeroCom models reduces the range and slightly strengthens the mean. Modifying the model estimates for missing aerosol components and for the time period 1750 to 2010 results in a mean RF for the DAE of −0.35 Wm−2. Compared to AeroCom Phase I (Schulz et al., 2006) we find very similar spreads in both total DAE and aerosol component RF. However, the RF of the total DAE is stronger negative and RF from BC from fossil fuel and biofuel emissions are stronger positive in the present study than in the previous AeroCom study. We find a tendency for models having a strong (positive) BC RF to also have strong (negative) sulphate or OA RF. This relationship leads to smaller uncertainty in the total RF of the DAE compared to the RF of the sum of the individual aerosol components. The spread in results for the individual aerosol components is substantial, and can be divided into diversities in burden, mass extinction coefficient (MEC), and normalized RF with respect to AOD. We find that these three factors give similar contributions to the spread in results.

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