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AERONET Inversions: Progress AERONET Inversions: Progress and Perspectivesand Perspectives
Numerical inversion:Numerical inversion:-Accounting for noise-Solving Ill-posed problem- Setting a priori constraints
Forward model:Forward model:-Spectral and angular scattering by particles with different sizes, compositions and shapes- Accounting for multiple scattering in atmosphere
single scattering albedosingle scattering albedo, etc.
(Dubovik and King, JGR, 2000(Dubovik and King, JGR, 2000)
Multiple ScatteringMultiple ScatteringMultiple scattering effects Multiple scattering effects are accounted by solving are accounted by solving scalarscalar radiative transfer equation with assuming radiative transfer equation with assuming Lambertian Lambertian ground reflectanceground reflectance (Nakajima – Tanaka code) (Nakajima – Tanaka code)
Aerosol scatteringAerosol scattering
Molecular scatteringMolecular scattering
Gaseous absorptionGaseous absorption
Surface reflectionSurface reflection
Single Scattering by Single ParticleSingle Scattering by Single Particle
Scattering and AbsorptionScattering and Absorption is modeled assuming aerosol is modeled assuming aerosol particle as particle as homogeneoushomogeneous sphere sphere with with spectrally dependentspectrally dependent complex complex refractive index refractive index ( m(( m()= n()= n() - i k() - i k()) - “Mie particles”)) - “Mie particles”
(Mishchenko et al., 1997)(Mishchenko et al., 1997)
Statistically optimized fittingStatistically optimized fitting:: (Dubovik and King, 2000)
Measurements:i=1 - optical thicknessi=2 - sky radiances-their covariances(should depend on and )-lognormal error distributions
a priori restrictions on norms of derivatives of:i=3 -size distr. variability;i=4 -n spectral variability; i=5 -k spectral variability;
Lagrange parameters
consistencyIndicator
weighting
ε0
2
εi2 fi
∗−fi x( )( )2
λ,θ( )i
∑ + ε0
2
εi2 fi
a −fi x( )( )2
i∑ → (Ntotal-Nx)ˆ ε 0
2
0.01
0.1
1
10
100
1000
0 20 40 60 80 100 120 140
Almucantar Fitting
Intensity
Scattering Angle (degree)
Int(0.44) * 1000
Int(0.67) * 100
Int(0.87) * 10
Int(1.02)
0
0.1
0.2
0.3
0.4
0.5
0.40 0.60 0.80 1.0
Fitting of optical thicknessin retrievals
MeasurementsFitting
Optical thickness
Wavelenths (micron)
0
0.05
0.1
0.15
0.2
0.25
0. 1 10
Retireved size distribution
Radius (microns)
dV/dlnR (
μm3/μm
2)
1.35
1.40
1.45
1.50
1.55
1.60
Wavelength (μ )m.44 .67 .87 1.2
Real Part
0.00
0.01
0.10
Wavelength (μ )m.44 .67 .87 1.2
Imarinary PartImaginary Part
Fitting as a retrieval strategy
The averaged optical properties of The averaged optical properties of various aerosol types various aerosol types (Dubovik et al., 2002, JAS)(Dubovik et al., 2002, JAS)
+
_
AERONET inversion developments
Forward model:- accounting for particle shape- using non-lambertian surface- modeling polarization
Retrieval flexibility:- additional spectral channels- different geometries
Inversion of combined data:- different geometries - combining with satellite- combining with aircraft
Output improvements:- detailed phase function- degree of polarization- flexible separation of modes- fluxes and forcing- details of fitting (biases and random)
Errors estimation:-for individual retrieval-for absorption optical thickness-for phase functions, etc.
Perspectives:- assuming bi-component aerosols- combining with polarimetric satellite observations- retrieval of shape distribution
Enhanced range of scattering anglesEnhanced range of scattering anglesSensitivity to vertical structure of aerosolSensitivity to vertical structure of aerosolChallenging cloud screeningChallenging cloud screening
Enhanced range of scattering anglesEnhanced range of scattering anglesSensitivity to vertical structure of aerosolSensitivity to vertical structure of aerosolChallenging cloud screeningChallenging cloud screening
Multiple Scat:Multiple Scat: DEUZE JL, HERMAN M, SANTER R, JQSRT, 1989
Successive Orders of Scattering CodeSuccessive Orders of Scattering Code
Utilizing polarizationEnhanced range of scattering anglesEnhanced range of scattering anglesSensitivity to vertical structure of aerosolSensitivity to vertical structure of aerosolChallenging cloud screeningChallenging cloud screeningCalibration verificationCalibration verification
28:9:23,18:7:54, _ , _ ,47Principal Plane Capo Verde
Fitting polarizationEnhanced range of scattering anglesEnhanced range of scattering anglesSensitivity to vertical structure of aerosolSensitivity to vertical structure of aerosolChallenging cloud screeningChallenging cloud screeningCalibration verificationCalibration verification
RadianceRadiance Linear PolarizartionLinear Polarizartion
- AERONET + satellite data (MODIS, MISR, POLDER …)AERONET + satellite data (MODIS, MISR, POLDER …)- AERONET + aircraft (CAR) + …satelliteAERONET + aircraft (CAR) + …satellite
- Spherical & Nonspherical modelSpherical & Nonspherical model ( (for all retrievalsfor all retrievals))
Perspectives:Perspectives:- assuming bi-component aerosolsassuming bi-component aerosols- combining with polarimetric satellite observationscombining with polarimetric satellite observations- retrieval of shape distribution- retrieval of shape distribution
Sensitivity to instrumental offsetsSensitivity to instrumental offsets