Estimate the Indirect Aerosol Effect and Retrieval of Related Parameters from Satellite Measurement
Qingyuan Han, PI
William B. Rossow, Co-I
Abstract:
Aerosol effects on climate change have drawn increased attention in
recent years due to the significant uncertainty of the magnitude of its
climate forcing and its possible role in other feedback mechanisms.
Aside from a direct radiative forcing by aerosol changes, there might
also be indirect effects because cloud changes are also induced. Due to
a lack of observational data, the range of the indirect aerosol effects
has remained large and highly uncertain. In order to narrow the range of
uncertainty in evaluating the indirect aerosol effect, combined studies
using models, field measurements and satellite observations are needed.
In particular, satellite observations can be used to monitor large-scale,
long-term variations of aerosols and cloud properties, to suggest
specific regions for field campaigns, and to supply a basis for and test
of parameterizations for climate models.
Based on the techniques developed in our previous studies and using the
currently available multi-channel AVHRR and GOES radiance data, this
proposal focuses on the following scientific questions:
(1) How does cloud droplet size change with variations in aerosol optical
thickness? The relation may vary with region because it changes for
different sources of aerosols (sulfate, dust, biomass burning). We can
try to observe such relations from satellites and investigate specific
cases with targeted field campaigns.
(2) What is the relation between cloud albedo and cloud droplet size?
Modelers need a quantitative description of this relationship in order to
evaluate the indirect aerosol effect.
(3) What parameters can satellite observations supply for model
studies of the indirect effect? Limited by the principles of remote
sensing and the instruments available, satellite observations have
difficulties providing all the desired quantities (such as volume liquid
water content and cloud geometrical thickness). Moreover, current
observations are limited to measuring EITHER aerosols or clouds, but not
both together.
(4) What regions appear more susceptible to the indirect aerosol effect?
There is general agreement that remote ocean areas are more susceptible
to the indirect effect. A quantitative estimate will be helpful in
estimate will be helpful in determining the place to conduct field
experiments.
(5) How much is the climate forcing by the indirect aerosol effect?
Due to the fact that there are no simultaneous satellite observations
of aerosol and cloud properties at the same location, this forcing can
only be estimated using a area-mean approach. Such an evaluation can
supply a lower limit and narrow the range of uncertainty in the climate
effects. We can also try to use models to estimate this effect.
To address the above questions, we plan to analyze twelve years of
AVHRR observations that can be used to relate changes of cloud
properties to changes of aerosol abundance and to estimate the indirect
aerosol forcing using two different approaches: statistical and
trajectory methods. Each method has its own advantages. The results of
analysis will be used in the GISS GCM as a basis for development and
validation of new parameterizations.
INPUT: Associated cloud and aerosol properties from other investigators;
Full resolution AVHRR and GOES radiances.
PLANNED OUTPUT:
a: Global distribution of column droplet number concentrations;
b: Global distribution of cloud column susceptibility;
c: Aerosol optical thickness retrieval using 1 channel technique;
d: Confirmation of relation between cloud albedo and cloud droplet size;
e: Estimate of relationship between cloud droplet size and aerosol optical
thickness;
f: Estimate of climate forcing by the indirect aerosol effect;
CONTRIBUTION:
The planned output(a,b,d,e) will be used by model studies (GISS GCM;
PI: Dr. Del Genio) as input. The output (c) can be used to compare with
estimates by other investigators in creating a global aerosol climatology.
The output(f) addresses the overall science team objective.
