GE0-CAPE Workshop University of North Carolina-Chapel Hill 18-20 August 2008 Aerosols: What is...
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![Page 1: GE0-CAPE Workshop University of North Carolina-Chapel Hill 18-20 August 2008 Aerosols: What is measurable and by what remote sensing technique? Omar Torres.](https://reader033.fdocuments.us/reader033/viewer/2022051517/56649f1f5503460f94c38260/html5/thumbnails/1.jpg)
GE0-CAPE WorkshopUniversity of North Carolina-Chapel Hill
18-20 August 2008
Aerosols: What is measurable and by what remote sensing technique?
Omar TorresHampton University
(with contributions from Lorraine Remer, Ralph Kahn, Shohba Kondragunta,Sundar Christopher, Ana Prados)
![Page 2: GE0-CAPE Workshop University of North Carolina-Chapel Hill 18-20 August 2008 Aerosols: What is measurable and by what remote sensing technique? Omar Torres.](https://reader033.fdocuments.us/reader033/viewer/2022051517/56649f1f5503460f94c38260/html5/thumbnails/2.jpg)
Aerosol Types and Origin• Aerosol particles larger than about 1
m in size are produced by windblown dust and sea salt from sea spray and bursting bubbles
• Aerosols smaller than 1 µm are
mostly formed by condensation processes such as conversion of sulfur dioxide (SO2) gas to sulfate particles and by formation of soot and smoke during burning processes.
• After formation, the aerosols are
mixed and transported by atmospheric motions and are primarily removed by cloud and precipitation processes.
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MicrophysicalSize distribution Refractive indexShape Vertical distribution
Macrophysical propertiesScattering function (P)Single scattering albedo (SSA)Ext. Optical thickness (AOT)
Particle Scattering Theory
AOText = AOTsca + AOTabs
SSA = AOTsca /(AOTsca + AOTabs)
Scattering Phase Function (P):
AERONET Measurements
Aerosol Physical Properties
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Aerosol properties measurable from passive satellite remote sensing
-Visible and Near-IR scattering AOT (usually reported as extinction AOT with an assumption on single scattering albedo) by MODIS, MISR.
-Observations at 412 nm (Deep Blue) used to derive aerosol AOT and SSA over deserts (MODIS)
-Near-UV observations can be used to derive information on aerosol absorptionQualitative (Aerosol Index TOMS / OMI) Quantitative if aerosol vertical distribution is known.
Polarization measurements (POLDER, PARASOL, Glory-APS) n/a to GEO-CAPE
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Retrieval Issues
Correction for gas absorption (minor issue)sub-pixel cloud contamination (depends on spatial resolution) (7km resolution better than OMI’s (13X24) but still non-optimum)
‘Surface’ correction:
Ocean:-Ocean color effects (chlorophyll conc., dissolved organic matter)- Glint effects (viewing geometry)- White caps (foam reflectance, wind speed) Land : High surface reflectance -Difficulty to separate aerosol signal from bright background in the vis and near IR -Less of a problem in the near UV BRDF effects Angular dependence of surface reflection
380 nm
440 nm
630 nmSurface Albedo from GOME observations
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Aerosol reflectance at 2.1 microns is negligibly small so that TOA measurementsare a direct measurement of surface albedo (R2.1).
Relationships between (R2.1) and R0.47 and R0.66 were developed based onobservations.
R0.47 = 0.25R2.1
R0.66 = 0.5R2.1
Handling of land reflectance issue in MODIS algorithm
(collection 4 model)
In collection 5, proportionality constantsare a function of geographical location.
This parameterization of surface reflectanceallows AOT retrievals over most land surfaces.It does not work over deserts.
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Current VIS and near-IR satellite aerosol products
MODIS aerosol product over oceans: - AOT at 0.47, 0.55, 0.66, 0.87, 1.24, 1.63, 2.13 microns - AOTfine / AOTtotal
- Effective radius (Based on spectral dependence of AOT)
MODIS aerosol product over land:
- AOT at 0.47 and 0.66 microns:- AOTfine / AOTtotal
-Qualitative Information on particle size distribution via the Angstrom Exponent
- AOT- SSA over deserts from Deep Blue Algorithm
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• Ocean product (10kmx10km):
– Total Spectral Optical thickness
– Effective radius
– Optical thickness of small & large modes/ratio between the 2 modes
• ~ ±0.03±0.05 (dust
excepted)
Aerosol Effective Radius2.00.0 1.00.5 1.5
Aerosol Optical Depth0.80.0 0.40.2 0.6
September, 2000
Small Mode Fraction1.00.0 0.500.25 0.75
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One MODIS Aerosol Type Classification: Low AOT (blue), High AOT+Coarse (green), High AOT+Fine (red)
Kaufman et al., JGR, 2005
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Absorbing aerosols as seen in the near-UV
Long-range aerosol transport takes place in the free troposphere, frequently above clouds.
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The Absorbing Aerosol Index
]))(
)((log)([log100
331
360
331
360calc
sfc
sfcmeas RI
RI
I
IAAI
calcmeas II )()( 331331
Thus, the AAI definition reduces to:
])((
)([log100
360
360
calcsfc
meas
RI
IAAI
Rsfc is a Lambert Equivalent effective surface reflectvity value such that
Rsfc is assumed wavelength independent
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Advantages of near-UV aerosol observations
Sensitivity to Aerosol Absorption-Aerosol Detection Capability over all surface types:
All vegetated surfaces deserts Oceans
Ice-snow covered surfaces Above clouds and inter-mingled with clouds
-Sensitive to Aerosol Layer Height
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Quantitative Near UV Retrieval Products (OMI)
By means of an inversion algorithm AOD and SSA are derived
March 9, 2007
The observed near-UV spectral contrast is conveniently ‘packed’ as the UV Aerosol Index
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June 27-08 (OMI) July 6-06 (OMI)
April 25-98 (TOMS) May 16 1998 (TOMS) Oct 1-07 (OMI)
Long range transport of aerosols into GE0-CAPE’s coverage area
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Aerosol type identification with UV-VIS observations
-Near UV-VIS spectral information can be used for aerosol type identification -Requires knowledge of spectral surface albedo
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• Satellite data have gaps due to clouds. Problem is particularly bad for polar-orbiting satellites as they see a particular location on the Earth only once a day (in UV-VIS)
• Geostationary satellites due to their rapid refresh rate, can obtain a more complete temporal coverage
Advantage of aerosol observations from Geostationary Satellites
Single snap shot of MODISComposite image from multiple snap shots of GOES-12
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No MODIS retrieval due to bright surface
Aerosols close to the surface?
MODIS treats thick smoke as cloud
Combined use of MODIS-OMI observations for aerosol detection
From Shohba Kondragunta