Accounting for non-sphericity of aerosol particles in photopolarimetric remote sensing of desert dust Oleg Dubovik (UMBC / GSFC, Code 923) Alexander Sinyuk (SSAI, Code 923) Tatyana Lapyonok ( GSFC, Code 923) Brent Holben ( GSFC, Code 923) Michael Mishchenko (NASA/GISS) Ping Yang (Texas A&M University) Anne Vermeulen (SSAI, Code 923) Tom Eck (UMBC/GSFC, Code 923) Ilya Slutsker (SSAI, Code 923) Hester Volten (Free University,Netherlan Ben Veihelmann (SRON Space Res., Netherlands)
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Accounting for non-sphericity of aerosol particles in photopolarimetric remote sensing of desert dust Oleg Dubovik (UMBC / GSFC, Code 923) Alexander Sinyuk.
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Accounting for non-sphericity of aerosol particles in photopolarimetric remote
measurements of dust light scatteringmeasurements of dust light scattering
Sensitivity of polarimetric Sensitivity of polarimetric measurements to aerosol parametersmeasurements to aerosol parameters
Applications to AERONET polarimetric Applications to AERONET polarimetric retrievalsretrievals
Difficulties of accounting for particle Difficulties of accounting for particle non-sphericity in aerosol retrievals:non-sphericity in aerosol retrievals:
1. many limitations in simulating light scattering by non-spherical particles (on particle size, shape, refractive index, etc.)
2. Simulation are too slow for operational retrievals (much slower than Mie scattering by spherical particle)
3. Concept of choosing particle shape is unclear
4. Validation of models is ambigious
Main limitations of T-Matrix code (Mishchenko et al.):- only spheroid shape (?)- size parameter ≤ ~ 60- aspect ratio ≤ 2.4- speed (for large aspect raitos) ~ 100 times slower than Mie
Difficulties of accounting for particle non-Difficulties of accounting for particle non-sphericitysphericity
SimplestSimplest model of non-spherical model of non-spherical aerosolaerosol
(Mishchenko et al., 1997)(Mishchenko et al., 1997)
How to implement operationally ???
Is this correct???
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0.1 1 10
dV/dlnR (
μm3 /μm2)
(Radius μ )m
Modeling Polydispersions
τ λ( )= Kτ(rmin
rmax
∫ k;n;r)V(r)dr≈ V(ri ) Kτ(ri −Δ/2
ri +Δ/2
∫ k;n;r)dr∑
K k;n;ri( ) - Kernel look-up table for fixed ri (22 points) (1.33 ≤ n ≤ 1.6; 0.0005 ≤ k ≤ 0.5)
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0.1 1 10
dV/dlnR (
μm3 /μm2 )
(Radius μ )m
V(ri) V(ri)
Single Scattering using Single Scattering using spheroids:spheroids:
Model by Mishchenko et al. 1997:Model by Mishchenko et al. 1997:
particles are randomly oriented homogeneous spheroids () - size independent aspect ratio distribution
€
τ λ( )≈ Viωp Kτ ...;r;ε( )drdεΔri
∫Δεp
∫⎡
⎣
⎢ ⎢ ⎢
⎤
⎦
⎥ ⎥ ⎥ i;p( )
∑
= Kip ...;n;k( )i;p( )∑ ωpVi
K - kernel matrix:
0.05 ≤ r ≤ 15 (μm)1.33 ≤ n ≤ 1.6
0.0005 ≤ k ≤ 0.50.4 ≤ ≤ 2.4
spheroidspheroid kernels data basekernels data basefor for operational modeling !!!operational modeling !!!
Basic Model by Mishchenko et al. Basic Model by Mishchenko et al. 1997:1997:randomly oriented homogeneous spheroids () - size independent shape distribution
€
τ λ( ),F11,...,F44 ≈ K ip ...;n;k( )i;p( )∑ ω p V ri( )
Spheroid Spheroid model model is successfully is successfully employed inemployed in both intensity and both intensity and polarized polarized AERONET retrievalsAERONET retrievals
Sensitivity to particle Sensitivity to particle shape is a shape is a challenge forchallenge for utilizing utilizing polarizationpolarization for for aerosol retrievalsaerosol retrievals