The key uncertainties in the climate sensitivity to the increasing greenhouse gases lie in the behavior and impact of short-lived species, such as tropospheric aerosols and ozone, and secondly, in the response and impact of the ocean circulation

Bauer, Susanne

Del Genio, Anthony

Nazarenko, Larissa

Rind, David

NASA Technical Reports Server

Fig. 1. Anomalies relative to 1850: (a) sulfates; (b) sea salt; (c) dust; (d) nitrates; 
(e) black carbon; (f) organic carbon.
The change of SAT between 1880 and 2012
based on linear trend ranges between +0.8°C and
+1.2°C (Fig. 2a), which agrees with the observed
temperature increase estimated as 0.9°C. The
largest warming is simulated in the TCAM model
globally, in the Northern and Southern
Hemispheres, and over the land and ocean
surfaces. The smallest warming is in the TCADI
model. Clouds become optically thicker with
increasing temperatures (Fig. 2b).
Fig. 2. Anomalies relative to 1850: (a) global annual mean surface air temperature; (b)
water cloud optical depth; (c) low level cloud cover; (d) high level cloud cover .
The largest warming in the TCAM model is 
accompanied by the largest decrease of the low 
level clouds (Fig. 2c) and the largest increase of 
the high level clouds (Fig. 2d) compared to the 
other two models.
Due to stronger warming in the TCAM model, the
liquid water content of clouds shows strong
increase despite the fact that low level cloud cover
reduced. The increase of the liquid water content in
clouds is pronounced over the ocean due to more
evaporation from the surface. The ice water content
in the TCAM model increased the largest of the
three models as the result of the more high level
clouds in this model.
The TCADI model produces larger increase of the
large scale CDNC for tropical and sub-tropical low
and middle level clouds between the present day
and the pre-industrial times (Fig. 3a). The smaller
change of CDNC in the TCAM model is reflected
in larger size of the cloud particles (Fig. 3b).
Fig. 3. The change of annual means (2003-2012) and (1850-1859) for (a) large-scale cloud
CDNC (cm-3), TCADI-TCAM; (b) large-scale cloud particle size (micron), TCADI-TCAM;
(c) the same as b but for TCADI-TCAD.
The TCADI model simulates optically thicker
water clouds over low latitudes (Fig. 4a). Over the
Southern Ocean and over the high and middle
northern latitudes, the water clouds are optically
thicker in the TCAM model due to larger increase
of liquid water content in this model (Fig. 4b).
Role of clouds, aerosols, and aerosol-cloud interaction 
in 20th century simulations with GISS ModelE2
Larissa Nazarenko, David Rind, Susanne Bauer, Anthony Del Genio
Columbia University/NASA Goddard Institute for Space Studies, New York, NY, USA
Introduction
The key uncertainties in the climate sensitivity to
the increasing greenhouse gases lie in the behavior
and impact of short-lived species, such as
tropospheric aerosols and ozone, and secondly, in
the response and impact of the ocean circulation.
Model and experiment descriptions
We use the new version of NASA GISS climate
model, modelE2 [Schmidt et al., 2014]. We use two
different treatments of the atmospheric composition
and aerosol indirect effect: (1) TCAD(I) version
has fully interactive Tracers of Aerosols and
Chemistry for total aerosol number and mass
concentrations in both the troposphere and
stratosphere [Shindell et al., 2013]; (2) TCAM is the
aerosol microphysics and chemistry model [Bauer
et al., 2008]. Both TCADI and TCAM models
include the first indirect effect of aerosols on clouds
[Menon et al., 2010]; the TCAD model includes
only the direct aerosol effect.
We consider the results of the TCAD, TCADI and
TCAM models coupled to “Russell ocean model”
[Russell et al., 1995], E2-R.
We examine the climate response, the effect of
clouds, their feedbacks, and the aerosol-cloud
interactions for the “historical period” that include
the natural and anthropogenic forcings for 1850 to
2012.
Results
Simulated global mean total mass of sulfate, nitrate,
organic carbon, black carbon, sea salt and dust are
presented in Figure 1 as a time-series of anomalies
relative to the year 1850 values. The evolutions of
aerosol total masses follow specified time-varying
emissions with differences between the mass-based
and microphysical aerosol models.
Since there is no indirect effect parameterization
is included to the TCAD model, the larger size
cloud particles are simulated for the present day
aerosol loaded atmosphere in this model
compared to the TCADI model (Fig. 3c). As a
result of it, the clouds are optically thinner in the
TCAD model (Fig. 4c) consistent with the change
of the global mean water cloud optical depth (Fig.
2b).
Fig. 4. The change of annual means (2003-2012) and (1850-1859) for (a) water cloud
optical depth, TCADI-TCAM; (b) liquid water path (10-2 kg/m2), TCADI-TCAM; (c) the
same as a but for TCADI-TCAD.
Literature Cited
Schmidt, G. A., et al. (2014), Configuration and assessment of the Giss
ModelE2 contributions to the CMIP5 archive, J. Adv. Model. Earth Syst., 6,
141-184, doi:10.1002/2013MS000265.
Shindell, D.T., O. Pechony, A. Voulgarakis, G. Faluvegi, L. Nazarenko, J.-
F. Lamarque, K. Bowman, G. Milly, B. Kovari, R. Ruedy, and G. Schmidt
(2013), Interactive ozone and methane chemistry in GISS-E2 historical and
future climate simulations. Atmos. Chem. Phys., 13, 2653-2689,
doi:10.5194/acp-13-2653-2013.
Bauer, S.E., D. Wright, D. Koch, E.R. Lewis, R. McGraw, L.-S. Chang,
S.E. Schwartz, and R. Ruedy (2008), MATRIX (Multiconfiguration
Aerosol TRacker of mIXing state): An aerosol microphysical module for
global atmospheric models. Atmos. Chem. Phys., 8, 6603-6035,
doi:10.5194/acp-8-6003-2008.
Menon, S., D. Koch, G. Beig, S. Sahu, J. Fasullo, and D. Orlikowski
(2010), Black carbon aerosols and the third polar ice cap, Atmos. Chem.
Phys., 10, 4559–4571.
Russell, G.L., J.R. Miller, and D.H. Rind (1995), A coupled atmosphere-
ocean model for transient climate change, Atmosphere-ocean, 33, 683-730.
https://ntrs.nasa.gov/search.jsp?R=20150023482 2019-08-31T05:11:54+00:00Z


Role of Clouds, Aerosols, and Aerosol-Cloud Interaction in 20th Century Simulations with GISS ModelE2

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