GACP Projects
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:
- 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.
- 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.
- 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.
- 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.
- 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.
