Atmospheric Chemistry and Physics
www.atmos-chem-phys.net
1680-7316
1680-7324
8
2
2008
10.5194/acp-8-209-2008
http://www.atmos-chem-phys.net/8/209/2008/
http://www.atmos-chem-phys.net/8/209/2008/acp-8-209-2008.html
http://www.atmos-chem-phys.net/8/209/2008/acp-8-209-2008.pdf
209
250
2008-01-18
Retrieving global aerosol sources from satellites using inverse modeling
O. Dubovik
dubovik@loa.univ-lille1.fr
T. Lapyonok
Y. J. Kaufman
M. Chin
P. Ginoux
R. A. Kahn
A. Sinyuk
Laboratoire de Optique Atmosphérique, Université de Lille 1/CNRS, Villeneuve d 'Ascq, France
Substantial part of this study was done while worked at: Laboratory for Terrestrial Physics, NASA Goddard Space Flight Center, Greenbelt, MD, USA
Laboratory for Terrestrial Physics, NASA Goddard Space Flight Center, Greenbelt, MD, USA
Science Systems and Applications, Inc., Lanham, MD, USA
Laboratory for Atmospheres, NASA Goddard Space Flight Center, Greenbelt, MD, USA
Geophysical Fluid Dynamics Laboratory, NOAA, Princeton, NJ, USA
Geophysical Jet Propulsion Laboratory, Pasadena, CA, USA
Understanding aerosol effects on global climate requires knowing the global distribution
of tropospheric aerosols. By accounting for aerosol sources, transports, and removal
processes, chemical transport models simulate the global aerosol distribution using
archived meteorological fields. We develop an algorithm for retrieving global aerosol
sources from satellite observations of aerosol distribution by inverting the GOCART aerosol transport model.
<br><br>
The inversion is based on a generalized, multi-term least-squares-type fitting,
allowing flexible selection and refinement of a priori algorithm constraints.
For example, limitations can be placed on retrieved quantity partial derivatives,
to constrain global aerosol emission space and time variability in the results.
Similarities and differences between commonly used inverse modeling and remote sensing
techniques are analyzed. To retain the high space and time resolution of long-period,
global observational records, the algorithm is expressed using adjoint operators.
<br><br>
Successful global aerosol emission retrievals at 2°×2.5 resolution
were obtained by inverting GOCART aerosol transport model output, assuming constant
emissions over the diurnal cycle, and neglecting aerosol compositional differences.
In addition, fine and coarse mode aerosol emission sources were inverted separately
from MODIS fine and coarse mode aerosol optical thickness data, respectively. These
assumptions are justified, based on observational coverage and accuracy limitations,
producing valuable aerosol source locations and emission strengths. From two weeks
of daily MODIS observations during August 2000, the global placement of fine mode
aerosol sources agreed with available independent knowledge, even though the inverse
method did not use any a priori information about aerosol sources, and was initialized
with a "zero aerosol emission" assumption. Retrieving coarse mode aerosol emissions was
less successful, mainly because MODIS aerosol data over highly reflecting desert dust
sources is lacking.
<br><br>
The broader implications of applying our approach are also discussed.
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