Authors

C. Jiao, University of Michigan
M.G. Flanner, University of Michigan
Y. Balkanski, Laboratoire des Sciences du Climat et de l'Environnement, CEA, CNRS, Gif-sur-Yvette, France
S.E. Bauer, Columbia University; NASA Goddard Institute for Space Studies, NY
N. Bellouin, Met Office Hadley Centre, Exeter, United Kingdom; University of Reading, United Kingdom
T.K. Berntsen, University of Oslo, Norway
H. Bian, University of Maryland
K.S. Carslaw, University of Leeds, United Kingdom
M. Chin, NASA Goddard Space Flight Center, Greenbelt, MD
N. De Luca, Università Degli Studi l'Aquila, Coppito, L'Aquila, Italy
T. Diehl, NASA Goddard Space Flight Center, Greenbelt, MD
S.J. Ghan, Pacific Northwest National Laboratory, Richland, WA
T. Iversen, Norwegian Meteorological Institute, Oslo, Norway
A. Kirkeväg, Norwegian Meteorological Institute, Oslo, Norway
D. Koch, Office of Biological and Environmental Research
Xiaohong Liu, University of Wyoming; Pacific Northwest National Laboratory, Richland, WA
G.W. Mann, University of Leeds, United Kingdom
J.E. Penner, University of Michigan
G. Pitari, Università Degli Studi l'Aquila, Coppito, L'Aquila, Italy
M. Schulz, Norwegian Meteorological Institute, Oslo, Norway
Ø Seland Ø., Norwegian Meteorological Institute, Oslo, Norway
R.B. Skeie, Center for International Climate and Environmental Research-Oslo (CICERO), Oslo, Norway
S.D. Steenrod, University Space Research Association, MD
P. Stier, University of Oxford, United Kingdom
T. Takemura, Kyushu University, Fukuoka, Japan
K. Tsigaridis, Columbia University; NASA Goddard Institute for Space Studies, NY
T. Van Noije, Royal Netherlands Meteorological Institute, De Bilt, Netherlands
Y. Yun, Geophysical Fluid Dynamics Laboratory, NOAA, Princeton, NJ
K. Zhang, Pacific Northwest National Laboratory, Richland, WA; Max Planck Institute for Meteorology, Hamburg, Germany

Document Type

Article

Publication Date

3-7-2014

Abstract

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. © 2014 Author (s).

DOI

10.5194/acp-14-2399-2014

Comments

Copyright 2014. The Authors

Creative Commons License

Creative Commons Attribution 3.0 License
This work is licensed under a Creative Commons Attribution 3.0 License.

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