AERONET Inversions: Progress and Perspectives

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AERONET Inversions Progress and Perspectives
Oleg Dubovik (NASA / GSFC)
Alexander Sinyuk (NASA / GSFC)
Tatyana Lapyonok (NASA / GSFC) Brent
Holben (NASA / GSFC) Tom Eck
(NASA / GSFC) Alexander
Smirnov (NASA / GSFC) Anne Vermeulen
(NASA / GSFC) Teruyuki Nakajima
(CCSR, Tokyo, Japan) Takashi Nakajima
(CCSR, Tokyo, Japan) Charles Gatebe
(NASA / GSFC) Michael King
(NASA / GSFC) Francois-Marie Breon
(CEA/DSM/LSCE, France) Michael Sorokin
(NASA / GSFC) Ilya Slutsker
(NASA / GSFC) AERONET/PHOTON (Word-Wide)
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Retrieval scheme
Forward model -Spectral and angular scattering
by particles with different sizes, compositions
and shapes - Accounting for multiple scattering
in atmosphere

• (Dubovik and King, JGR, 2000)

Numerical inversion -Accounting for
noise -Solving Ill-posed problem - Setting a
priori constraints
Observations
aerosol particle sizes, refractive index,
single scattering albedo, etc.
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Multiple Scattering
Multiple Scattering
Multiple scattering effects are accounted by
solving scalar radiative transfer equation with
assuming Lambertian ground reflectance (Nakajima
Tanaka code)
Aerosol scattering
Gaseous absorption


Surface reflection
Molecular scattering
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Single Scattering
Single Scattering by Single Particle
Scattering and Absorption is modeled assuming
aerosol particle as homogeneous sphere with
spectrally dependent complex refractive index (
m(l) n(l) - i k(l)) - Mie particles
Iscat(???)
m(l) Radius
I0(?)
Itrans(?)
P(Q)- Phase Function ?0(l) -single
scattering albedo ?(l) - extinction optical
thickness ?(l)?0(l)?? absorption?optical
thickness
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AERONET model of aerosol
AERONET model of aerosol
spherical
Randomly oriented spheroids (Mishchenko et al.,
1997)
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Inversion

• Statistically optimized fitting
• (Dubovik and King, 2000)

Lagrange parameters
weighting

• Measurements
• i1 - optical thickness
• i2 - sky radiances
• their covariances
• (should depend on l and Q)
• -lognormal error distributions

a priori restrictions on norms of derivatives
of i3 -size distr. variability i4 -n spectral
variability i5 -k spectral variability
consistency Indicator
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Fitting as a retrieval strategy
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The averaged optical properties of various
aerosol types (Dubovik et al., 2002, JAS)
_

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AERONET inversion developments

• Forward model
• accounting for particle shape
• - using non-lambertian surface
• modeling polarization

• Output improvements
• detailed phase function
• degree of polarization
• flexible separation of modes
• - fluxes and forcing
• details of fitting (biases and random)

• Retrieval flexibility
• additional spectral channels
• different geometries

• Errors estimation
• for individual retrieval
• for absorption optical thickness
• for phase functions, etc.

• Inversion of combined data
• different geometries
• combining with satellite
• - combining with aircraft

• Perspectives
• assuming bi-component aerosols
• combining with polarimetric
• satellite observations
• - retrieval of shape distribution

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AERONET inversion scenarios

• Almucantar
• t(l), I(l,Q)
• 0.38, 0.44, 0.5, 0.67,
• 0.87, 1.02, 1.64, mm

Inversion Products dV/dln(ri)
n(l) k(l) BRDF errors
spheres

• Principal Plane
• t(l), I(l,Q)
• l 0.38, 0.44, 0.5, 0.67,
• 0.87, 1.02, 1.64, mm

spheroids
Polarized Principal Plane t(l), I(l,Q),P(l,Q) l
0.87mm
w0(l) P11(l), P12(l), ... fine coarse fluxes,
satellite, aircraft, etc.
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Utilizing additional spectral channels

• Almucantar
• t(l), I(l,Q)
• 0.44, 0.67,0.87,
• 1.02, 1.64, mm

Potential enhancement of information Increased
calibration efforts
Desert Dust (Dhabi, UAI)
dV/dln(ri)
n(l)
w0(l)
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Utilizing additional spectral channels

• Almucantar
• t(l), I(l,Q)
• 0.38, 0.44, 0.67,
• 0.87, 1.02, mm

Potential enhancement of information Increased
calibration efforts
GSFC aerosol
dV/dln(ri)
n(l)
w0(l)
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Fitting additional spectral channels
GSFC aerosol
Dhabi dust
0.5, 1.64 mm
1.64 mm
0.38 mm
0.02
- 0.02
???
water vapor ?
fine ?
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Utilizing principal plane
Enhanced range of scattering angles Sensitivity
to vertical structure of aerosol Challenging
cloud screening

• Principal Plane
• t(l), I(l,Q)
• l 0.44, 0.67, 0.87,
• 1.02, 1.64, mm

Desert Dust (Dhabi, UAI)
dV/dln(ri)
n(l)
w0(l)
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Utilizing principal plane
Enhanced range of scattering angles Sensitivity
to vertical structure of aerosol Challenging
cloud screening

• Principal Plane
• t(l), I(l,Q)
• l 0.44, 0.5, 0.67,
• 0.87,1.02, 1.64, mm

GSFC aerosol
dV/dln(ri)
n(l)
w0(l)
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AERONET Polarized Inversion
Forward Model
Single Scat
Multiple Scat
DEUZE JL, HERMAN M, SANTER R, JQSRT, 1989
Successive Orders of Scattering Code
t(l), I(l,Q),P(l,Q)
Numerical inversion -Accounting for uncertainty
(F11 -F12/F11 !!!) - Setting a priori
constraints
aerosol particle sizes, refractive index,
single scattering albedo
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Utilizing polarization

• Principal Plane
• t(l), I(l,Q)
• l 0.44, 0.5, 0.67,
• 0.87,1.02, 1.64, mm
• Polarization
• t(l), I(l,Q),P(l,Q)
• l 0.87mm

Enhanced range of scattering angles Sensitivity
to vertical structure of aerosol Challenging
cloud screening Calibration verification
Cape Verde aerosol
dV/dln(ri)
n(l)
w0(l)
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Fitting polarization
Principal Plane t(l), I(l,Q) l
0.87mm Polarization t(l), I(l,Q),P(l,Q) l
0.87mm
Enhanced range of scattering angles Sensitivity
to vertical structure of aerosol Challenging
cloud screening Calibration verification
Cape Verde aerosol
Radiance
Linear Polarizartion
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Fine and Coarse modes separations
Beijing aerosol
Radiance
0.45mm
Flexible separation between fine and coarse
modes (curently 0.6 mm)
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Retrieval using combinations of up-looking
Ground-based and down-looking satellite observati
ons
Retrieved
Aerosol Properties - size distribution - real
ref. ind. - imag. ref. ind (AERONET sky channels)

• Surface Parameters
• BRDF (MISR channels)
• Albedo (MODIS IR channels)

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AERONET / POLDER-2 retrieval
POLDER-2 fit
Biomass burning Mongu, Zambia, June, 2003
Size distribution
BRDF
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AERONET/ MISR/ MODIS retrieval

• AERONET Ground-based Sun-sky radiometer
• - t(l) 0.02 at
• 6 channels 0.34, 0.38, 0.44, 0.67, 0.87, 1.02,
  1.65 mm
• I(l,Q) 0.05 at
• 4 channels 0.38, 0.44, 0.67, 0.87, 1.02, 1.65 mm
• 3 scattering angles 70
• P(l,Q) 0.02 at 0.87
• MISR
• Reflectance at
• 4 channels 0.45, 0.55, 0.67, 0.87 mm
• 9 viewing angles 70.5o, 60o, 45.6o,
  26.1o, 0o
• MODIS
• Reflectance at
• 7 channels 0.47, 0.55, 0.66, 0.87,1.2, 1.6, 2.1

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Retrieval using combinations of up- and
down-looking observations
Retrieved
Aerosol above plane - size distribution - real
ref. ind. - imag. ref. ind
Aerosol below plane - size distribution - real
ref. ind. - imag. ref. ind
Surface Parameters - BRDF, albedo, etc.
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CAR - Cloud Absorption Radiometer
Univ. of Washington CV-580
Flown by CV-580 aircraft at 700 m above ground
8 spectral channels 0.34, 0.38, 0.47, 0.68,
0.87, 1.03, 1.19, 1.27 mm
Measures radiation transmitted and
reflected 0 Obs. Zenith 180 0 Obs.
Azimuth 360
Stray light problems for scattering angles
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Optical thickness t(l) on September 6, 2000

• AERONET
• daily variations

AATS-14 versus AERONET
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Aerosol retrieved from combinedCAR - AERONET -
AATS-14 obs.
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Comparison of model retrieved BRDFwith corrected
direct BRDF
BRDF constrains model - positive and smooth -
PP symmetrical
Gatebe et al. 2003
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Comparison of retrieved surface reflectance with
other observations
Mongu, Zambia
Lambertian approximation
Mongu, September 6, 2000
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New Inversion Options

• Almucatars (any numbers of spectral channels)
• Principal planes (any numbers of spectral
  channels)
• Polarized Principle Planes (0.87 mm)
• Combined Principle Planes Polarized (0.87 mm)
  Regular (0.44 - 1.02mm)
• Other Combined Cimel Data
• Almucantar Principle Plane (?)
• Several Almucantars Principle Planes (??)
• AERONET satellite data (MODIS, MISR, POLDER )
• AERONET aircraft (CAR) satellite
• Spherical Nonspherical model (for all
  retrievals)

• Perspectives
• assuming bi-component aerosols
• combining with polarimetric satellite
  observations
• - retrieval of shape distribution

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Offsets
Sensitivity to instrumental offsets
Offsets were considered in - optical thickness
- sky-channel calibration - azimuth angle
pointing - assumed ground reflectance
Aerosol models considered (bi - modal
log-normal) - Water-soluble aerosol for 0.05
t(440) 1 - Desert dust for 0.5 t(440)
1 - Biomass burning for 0.5 t(440) 1
Results summary - t(440) 0.2 - dV/dlnr (),
n(l) (-), k(l) (-), w0(l) (-) - t(440) gt 0.2 -
dV/dlnr (), n(l) (), k(l) (), w0(l) () -
Angular pointing accuracy is critical for dV/dlnr
of dust
() CAN BE retrieved (-) CAN NOT BE retrieved
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Dt bias influence at Dw0
Dt bias
Sky Radiance bias
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Random ERRORS in AERONET retrievals
ASSUMPTIONS - measurements have Normal Noise
- optical thickness s 0.01
- sky-radiances s 5

• CONCLUSIONS
• the retrievals stable
• important tendencies
• outlined

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Rigorous ERRORS estimates General case large
number of unknowns and redundant measurements
U - matrix of partial derivatives in the vicinity
of solution
Above is valid - in linear approximation -
for Normal Noise - no a priori constraints
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ERRORS estimates with a priori constraints
ISSUES - in linear approximation - for Normal
Noise - strongly dependent on a priori
constraints - very challenging in most
interesting cases
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ERROR Factors
Important Factors - Aerosol Loading -
Scattering Angle Range - Number of Angles
(homogeneity) - Aerosol Type etc.
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Examples of error estimates
high loading
low loading
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ABSORPTION of SMOKE
flaming combustion Rio Branco, Brazil
smoldering combustion Quebec fires, July 2002