Polarization in Earth Remote Sensing: Aerosol monitoring, and more

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Polarization in Earth Remote Sensing Aerosol
monitoring, and more

• François-Marie Bréon
• Laboratoire des Sciences du Climat et de
  lEnvironnement
• Visiting GSFC until August 29th

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Overview of POLDER-Parasol saga

• POLDER-1 onboard the ADEOS platform (1996-1997).
  Solar panel failure terminated operations (8
  months of continuous acquisition)
• POLDER-2 onboard the ADEOS-2 platform (2003).
  Solar panel failure terminated operations (7
  months of continuous acquisition)
• Parasol onboard a CNES microsat satellite. Fly
  in formation with the Aqua Train.
  Near-continuous acquisition since March 2005 (3
  year worth of data)
• Eight spectral bands from 440 (blue) to 910 (near
  IR) nm
• Bi-dimensional CCD matrix. 2400x1800 km IFOV
• Spatial Resolution 6 km
• Three Polarized bands 440/490, 670, 865 nm.

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POLDER Multidirectional acquisition
Multispectral measurements acquired every 20 sec
14 POLDER views
Phase angles
Nadir
Principal Plane
View Angles
Perpendicular Plane
Backscattering
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Parasol polarization measurements
Three successive measurements with polarizer
turned by step of 60 Inversion of radiometric
model yield linear polarization parameters I, Q,
U Three spectral bands 490, 670, 865 nm
Rough correction for molecular scattering. Three
colour composites
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A few examples of Directional/Spectral /
Polarized signatures
3 color composites in total light 443-670-865 nm
Directional signatures. Total light
Location of swath and image
3 color composites in polarized light 443-670-865
nm
Directional signatures. Polarized light
Directional sampling View angle Phase or Glint
angle
Simple formula for polarized reflectance
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Sunglint over Mediterranean Sea
qs36
Wave slope
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Vegetation (Amazonian)
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Desert
Overestimate at large phase angles
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Aerosols over the Ganges Valley
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Biomass Burning Aerosol
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Antarctic Cloud Bow
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Low Cloud and High Cloud
Goloub Ph et al., JGR, 2000 Riedi J. et al., GRL,
2000
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Aerosol retrieval over the oceans
Best fit of both radiance and polarized radiance
against tabulated TOA simulated
radiances Different number of free parameters
depending on the signal level and the observation
geometry (a wide range of scattering angles,
including 150 is best) Two modes can vary
independently Small mode with effective radius
between 0.04 and 0.13 µm (fixed variance)
Large mode with both a spherical component (Mie
simulations) and a non-spherical component
(empirical phase function, Volten et al.
2001) Search for model and optical thickness
that fits the simulations best Quality indices
based on the measurement-model fit and
observation geometry
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Aerosol Inversion over the oceans
Large to small particles
Spectral effect increases 150 arc decreases
Deuzé JL. et al., GRL, 1999 Deuzé JL. et al.,
JGR, 2000
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Main Parasol products over the oceans
Sept. 2005
Total Optical Thickness
Angström Coefficient
Fine Mode Optical Thickness
Coarse Mode Optical Thickness
Effective radii, info on scattering phase
function and quality indices
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A movie
Dark Low aerosol load Red Fine mode
aerosols Green Coarse mode aerosols Grey No
data
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Identification of non spherical particles
150 arc indicates the presence of large,
spherical particles
Small spectral effect but no Arc Non spherical
particles.
Fraction of non-spherical particles in coarse mode
Herman M. et al., JGR, 2005
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Aerosol non-sphericity (2/2)
Total Optical Thickness
Coarse mode Non-Spherical Optical Thickness
Fraction of non spherical in Coarse Mode
Coarse mode Spherical Optical Thickness
Non spherical particles downwind of dust sources.
Spherical particles where hydrated, sea-salts
are expected.
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Over land
Why is polarization so useful for aerosol remote
sensing over land ?
Rayleigh
Aerosols
Surface

• is small compared to atmospheric contribution
• is spectrally neutral
• is rather uniform (varies little with surface
  type)
• can be roughly estimated from surface
  classification

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Variability of surf. polarized reflectance
Surf. Pol. Reflectance _at_865 nm
Scattering angle
Measurements show that the surface polarized
reflectance is little variable, even over rather
heterogeneous surfaces
Fan et al., 2007
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Aerosol reflectance is highly polarized
AEROSOL
Clear atmosphere (AOT0.03) the reflectance
at TOA is close to the surface values
Hazy atmosphere large aerosol contribution,
1.010-2 at 110-120 for AOT0.31
Illustration for Biomass Burning Aerosols
Deuzé et al., 2001
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Aerosol inversion over land
Based on the hypothesis that surface polarized
reflectance is small and varies
little Parameterization of the surface polarized
reflectance (semi empirical model as a function
of surface type and NDVI NadalBréon,
1998) Model optical thickness estimate based on
measured polarized reflectance at 670 and 865
nm. Works well for small aerosol (sulfates,
biomass burning) over vegetated areas BUT Does
not work for coarse aerosols (desert dust) Does
not work over desert or snow due to their larger
polarized reflectance
Polarized reflectance
Deuzé JL et al., JGR, 2001
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Fine mode optical thickness
Fine mode optical Thickness 550 nm
Aerosol load by sub-micronic particles (fine
mode) Over land based on multi-directional
polarized measurements Over the ocean Uses both
reflectance and polarized meas.
Note annual cycle of biomass burning activity,
pollution over China, Galapagos volcanic eruption
late October 2005
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Time series against Aeronet
Fan et al., 2007
78 coincident days
70 coincident days
(03/2005-05/2006)
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Validation against AERONET
AOTgt1
POLDER
Optical Thickness
Angström Coefficient
Sunphotometer
Good agreement on optical thickness and Angström
coefficient Largest scatter on small mode optical
thickness stay tuned
Fine mode
Marine Retrievals
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Validation against AERONET
Optical Thickness
Angström coefficient
Fine r lt 0.3 µm
Fine r lt 0.4 µm
Land Retrievals
Resuts affected by the definition of fine mode
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Validation against Aeronet
Australia
Medit. Europe
Non Med. Europe
India SE Asia
Sahel
China
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Parasol-MODIS comparison 1 Trends
Mar.05 - Feb.06 PARA. MOD. 0.136 0.138 0.016 0.01
0 Mar.06 - Dec.06 PARA. MOD. 0.137 0.140 0.012
0.006

• Calibration procedures are different
• LUTs are different
• Spectral versus directional/polarization

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Parasol-MODIS comparison. 2 JJA 2006
MODIS
Parasol
Fine mode AOD
Tanre et al. 2008
Total AOD
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Parasol-MODIS comparison. 3 DJF 2007
MODIS
Parasol
Tanre et al. 2008
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Parasol concept for aerosol Pros and con
Multispectral multidirectional Polarization
measurements provide a lot of constrains for the
aerosol model retrieval Depending on the target
location with respect to the satellite, the range
of scatterinig angle varies Multidirectional
acquisition reduces the glint issue. Spatial
resolution of POLDER. Limits daily coverage in
the presence of broken clouds (a problem in the
tropics, in particular for Parasol afternoon
views). Surface contribution to the measured
polarized reflectance. Although small, the
surface contribution is not fully negligible A
longer wavelength polarized channel would help
constraining the surface polarization
contribution. Airborne measurements indicate
that the surface polarized reflectance is
spectrally neutral. gt APS on glory
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Cloud Droplet Radiusfrom Multidirectional
polarisation measurements
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Liquid phase clouds
Scattering angle
Stratocumulus cloud field
Baja California
Same scene in polarized light
3-color composite 443-670-865 nm
In some cases, clouds fields show specific
features in polarized light for scattering angles
between 140 and 170
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Many such examples...
The position of color bands relative to the
scattering angle is variable !
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Droplet polarized phase function
Size distribution
Rainbow
Spectral signature
Dampening for wider size distributions
The polarized phase function shows oscillations
that explain the observed features. Angular
position of maxima and minima depend on
wavelength and effective radius. Such feature
require a narrow size distribution. Polarized
reflectance mostly generated by single scattering
Bréon FM and Ph Goloub, GRL, 1998
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Measurement-model fit
Polarized Reflectance
443nm 670nm 865nm
Scattering Angle
Bréon FM and M. Doutriaux Boucher, IEEE TGARS,
2005
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Retrieved spatial distributions of CDR
August
April
June
October
Poor sampling because of limitations on viewing
geometry, extended cloud field and narrow size
distribution. Shows smaller droplets over
continents, and in particular polluted areas
Bréon FM and S. Colzy, GRL, 2000
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Comparison with MODIS
Excellent correlation over the Oceans Poor
correlations for small droplets in particular
found over land surfaces Bias of 2 µm (POLDER lt
MODIS). - CDR at the very cloud are smaller
than deeper in the cloud ? - Spatial
heterogeneity ? - Size distribution different
than assumed ?
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CDR with polarization. Conclusions
Multidirectional polarization provides an
alternative (to spectral) method for the estimate
of CDR Advantage of polarization Measures the
single scattering, which provides a near-direct
measurement of the scattering phase
function Requires specific conditions (geometry
and cloud properties) so that its statistic is
poor Measurements have shown that the CDR
distribution is not as expected, in particular
over stratocumulus clouds. Bias with MODIS.
Several hypothesis. I believe bias is due to
measurement depth into the cloud. Still not clear
why MODIS shows large spatial variability in CDR
when Parasol retrieval indicates a more
homogeneous CDR field