Do anthropogenic aerosols enhance or suppress the
surface cloud forcing in the Arctic?
K.
1
Alterskjær ,
1Department
J. E.
1
Kristjánsson
1
Hoose
and C.
of Geosciences, University of Oslo, Norway
Problem
W/m2
• We investigate a proposed increase in the warming effect of Arctic clouds due to anthropogenic
aerosols.
• Observational studies from Alaska suggest that the longwave (LW) radiative flux at the surface may
increase by 3.3 to 8.2 W/m2 due to aerosol-cloud interactions (Garrett and Zhao, 2006 and Lubin
and Vogelmann, 2006).
• We use a global climate model to study the annual and seasonal total radiative effect of
interactions between anthropogenic aerosols and clouds over the entire Arctic region.
• Over highly reflecting snow
and ice surfaces, clouds have a
small effect on the shortwave
(SW) radiation budget. Hence,
the longwave warming effect
of the clouds dominates.
Surface net cloud forcing,
summer season (Jun-Sep)
Model validation
Indirect effect
• Otherwise similar clouds are
optically thicker in polluted
than in clean environments
due to reduced cloud droplet
effective radius (re) and
increased cloud liquid water
path (LWP) (Twomey, 1977
and Albrecht, 1989).


Clean (left) and polluted (right) environment.
Figure from Lohmann (2005).
Simulated re, surface albedo and surface concentrations of
particulate sulfate are consistent with observations.
LWP and surface cloud forcing (CFS) was validated against data from
the SHEBA campaign (Zhang et al., 2002 and Intrieri et al., 2002):
Results shown are from simulations in which the model LWP is
reduced by a factor of five through reducing the cloud droplet
number concentration (CDNC). This gave LWP and CFS closest to
what was observed.
Model tools and method
Sensitivity experiments
• CAM-Oslo global climate model
• 5-year simulations
• Off-line: Meteorological evolution the same in all model
runs
• Aerosols affect droplet nucleation only
• Model modifications: Liquid water absorption coefficient
depends on re:

Manipulations of the simulated LWP and SO4 concentrations show
that our conclusions are robust against changes in both cloud
properties and aerosol concentrations.
Change in annual
cloud forcing
[W/m2]
LWP/5
∆CDNC
Min
Max
LW
0.55
0.10
0.85
SW
-0.85
-1.29
-0.52
Net
-0.30
-0.98
0.12 1
Results of sensitivity experiments
• Averaged north of 71o N.
• Experiments included reducing the LWP through reducing the CDNC, reducing the re, increasing the cloud
ice fraction and increasing the auto-conversion so that more water is lost through precipitation. Also
included were two experiments in which the SO4 concentrations were increased.
• 1 Only one in ten experiments resulted in a positive annual change in CFS with anthropogenic aerosols.
• Emission scenarios (AeroCom)
• Pre-industrial
• Present day
Simulated changes in cloud properties
Simulated anthropogenic change in re [µm] (left) and LWP
∆LWP
[g/m2]
(right), annual average.
Simulated contribution to surface cloud forcing
by anthropogenic aerosols [W/m2]
∆LW
Observed (green) and simulated (blue) SO4
concentrations [µg S/m3]. Observational data
from AMAP (2006) have been averaged over
five years and error bars show the maximum
and the minimum observed monthly means. The
median of 10 AeroCom A models (Textor et al.,
2006) for Spitsbergen (including Zeppelin) and
Janiskoski for the year 2000 is shown in red.
Conclusion
Anthropogenic aerosols lead to:
• A simulated decrease in re
• A simulated increase in LWP
∆re
Black dots: Observed surface albedos obtained
from aircraft measurements in the vicinity of the
SHEBA ship (Curry et al., 2000).
Blue lines: CAM-Oslo simulated albedo.
∆SW
• Stronger simulated surface
cloud forcing both in the LW
and the SW
• An overall negative radiative
effect (cooling) due to SW
dominance.
∆ Total
• Anthropogenic aerosols in the Arctic are likely to lead to
an overall decrease in the radiative flux at the surface
under cloudy skies.
Change in surface
cloud forcing [W/m2]
Winter
(Oct –May)
Summer
(Jun – Sep)
Annual average
LW
0.33
0.99
0.55
SW
-0.19
-2.17
-0.85
Net
0.14
-1.18
-0.30
Averaged north of 71o N.
• In the future, sulfate concentrations are expected to
decrease, reducing the cooling effect, causing an enhanced
melting of snow and ice.
Contact information
• Kari Alterskjær, kari.alterskjar@geo.uio.no – 228 55775
References
∆LW
∆SW
Top: Annual averages. Bottom: Summer/Melt season averages (June to September). Note that color bars differ.
∆ Total
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•
•
•
•
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Alterskjær et al. (2010), J. Geophys. Res., 115(D22204), doi: 10.1029/2010JD014015
Albrecht, B. A., (1989) Science, 245, 1227–1230.
Curry et al. (2000), Bull. Am. Meteorol. Soc., 81, 5–29.
Garrett, T. J., and C. Zhao (2006), Nature, 440, 787–789, doi:10.1038/nature04636.
Intrieri et al. (2002), J. Geophys. Res., 107(C10), 8039, doi:10.1029/2000JC000439.
Lohmann, U. (2005). Indirect Effects: Aerosol and Cloud Microphysics. IPCC Expert Meeting on
Aerosols, Geneva.
• Lubin, D., and A. M. Vogelmann (2006), Nature, 439, 453–456, doi:10.1038/nature04449.
• Twomey, S. (1977), J. Atmos. Sci., 34, 11491152.
• Zhang et al. (2002), J. Geophys. Res., 107(D24), 4750, doi:10.1029/2001JD001484.
This study was partly funded by the Norwegian Research Council through
the projects POLARCAT (grant No. 175916) and NorClim (grant No. 178246).