AERONET Inversions: Progress and Perspectives Oleg Dubovik (NASA / GSFC) Alexander Sinyuk (NASA /...

AERONET Inversions: Progress AERONET Inversions: Progress and Perspectivesand 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…AERONET/PHOTON… (Word-Wide)

ObservationsObservations

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

aerosol particle sizes,aerosol particle sizes, refractive index, refractive index,

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”

m()Radius

P(P()-)- Phase Function; -single scattering albedo() - extinction optical thickness; () absorptionoptical thickness

II00(())

IIscatscat(())

IItranstrans(())

Single ScatteringSingle Scattering

AERONETAERONET model of aerosol model of aerosolspherical:spherical:

Randomly orientedRandomly orientedspheroids :spheroids :

(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

Almucantar: ((), I(), I())= 0.38, 0.44, 0.5, 0.67, 0.87, 1.02, 1.64, μm

AERONET inversion scenarios

Principal Plane: ((), I(), I()) = 0.38, 0.44, 0.5, 0.67, 0.87, 1.02, 1.64, μm

Polarized Principal Plane: ((), I(), I(),P(),P()) = 0.87μm

spheres

spheroids

Inversion Products: dV/dln(rdV/dln(rii) )

n(n(k(k(

BRDFBRDFerrorserrors

satellite, aircraft, etc.

(P11(P12(

fine & coarsefine & coarsefluxes, …, …

Utilizing additional spectral channels

Potential enhancement of informationPotential enhancement of informationIncreased calibration effortsIncreased calibration efforts

0

0.05

0.1

0.15

0.2

0.1 1 10

4 channels5 channels (+ 1.637 μ )m

/ (dV dlnR

μm3 /μm

2 )

( )Particle Radius micron

21:2:24,5:21:34, Dhabi

1.35

1.4

1.45

1.5

1.55

1.6

0.4 0.6 0.8 1 1.2 1.4 1.6


Real Part of Refractive Index

(Wavelength μ )m

21:2:24,5:21:34,Dhabi

0.65

0.7

0.75

0.8

0.85

0.9

0.95

1

0.4 0.6 0.8 1 1.2 1.4 1.6


Single Scattering Albedo

(Wavelength μ )m

21:2:24,5:21:34,Dhabi

Desert Dust (Dhabi, UAI)

dV/dln(rdV/dln(rii)) n(n( (

Almucantar: ((), I(), I())= 0.44, 0.67,0.87, 1.02, 1.64, μm

Utilizing additional spectral channels

Potential enhancement of informationPotential enhancement of informationIncreased calibration effortsIncreased calibration efforts

GSFC aerosol


Almucantar: ((), I(), I())= 0.38, 0.44, 0.67, 0.87, 1.02, μm

0

0.005

0.01

0.015

0.02

0.025

0.03

0.035

0.1 1 10

4 channels5 channels (+0.38 μ )m

/ (dV dlnR

μm3 /μm

2 )


19:2:24,21:25:19, , ,33Almucantar GSFC

1.34

1.36

1.38

1.4

1.42

1.44

1.46

1.48

1.5

0.4 0.5 0.6 0.7 0.8 0.9 1

4 channels5 channels (+0.38 μ )m


(Wavelength μ )m

19:2:24,21:25:19, , ,33Almucantar GSFC

0.65

0.7

0.75

0.8

0.85

0.9

0.95

1

0.4 0.5 0.6 0.7 0.8 0.9 1



(Wavelength μ )m

19:2:24,21:25:19, , ,33Almucantar GSFC

0.04

0.06

0.08

0.1

0.3

0.5

0.4 0.5 0.6 0.7 0.8 0.9 1

measurementsfitted

Optical Thickness

Wavelength (μ )m

19:2:24,21:25:19, , ,33Almucantar GSFC

0.04

0.06

0.08

0.1

0.3

0.5

0.4 0.5 0.6 0.7 0.8 0.9 1 2

measurementsfitted

Optical Thickness

Wavelength (μ )m

2:3:24, 12:59:4, , ,131Almucantar GSFC

GSFC aerosolGSFC aerosol Dhabi dustDhabi dust

+ 0.38 μm+ 0.5, 1.64 μm+ 1.64 μm

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0.4 0.5 0.6 0.7 0.8 0.9 1 2

measurementsfitted

Optical Thickness

Wavelength (μ )m

21:2:24, 5:21:34,Dhabi

Fitting additional spectral channels

+ 0.02 - 0.02

??? water vapor ? fine ?

Utilizing principal plane

Enhanced range of scattering anglesEnhanced range of scattering anglesSensitivity to vertical structure of aerosolSensitivity to vertical structure of aerosolChallenging cloud screeningChallenging cloud screening

Desert Dust (Dhabi, UAI)


Principal Plane: ((), I(), I()) = 0.44, 0.67, 0.87, 1.02, 1.64, μm

0

0.05

0.1

0.15

0.2

0.25

0.1 1 10

almucantarprinciple plane (4 channels)principle plane (5 channels: + 1.64 μ )m

/ (dV dlnR

μm3 /μm

2 )


21:2:24,5:47:17, _ , ,132Principal Plane Dhabi

1.3

1.35

1.4

1.45

1.5

1.55

1.6

1.65

0.4 0.6 0.8 1 1.2 1.4 1.6 1.8

AlmucantarPrinciple Plane (4 channels)Principle Plane (5 channels)

Real Part of Reffactive Index

Wavelengths (μ )m


0.6

0.7

0.8

0.9

1

0.4 0.6 0.8 1 1.2 1.4 1.6 1.8



Wavelengths (μ )m


Utilizing principal plane

Enhanced range of scattering anglesEnhanced range of scattering anglesSensitivity to vertical structure of aerosolSensitivity to vertical structure of aerosolChallenging cloud screeningChallenging cloud screening

dV/dln(rdV/dln(rii)) n(n( ((

Principal Plane: ((), I(), I()) = 0.44, 0.5, 0.67, 0.87,1.02, 1.64, μm

GSFC aerosol

0

0.02

0.04

0.06

0.08

0.1

0.1 1 10

almucantar (4 channels)principle plane (4 channels)principle plane (6 channels: + 0.5, +1.64 μ )m

/ (dV dlnR

μm3 /μm

2 )


2:3:24,12:59:4, , ,131Almucantar GSFC

1.3

1.35

1.4

1.45

1.5

1.55

1.6

1.65

0.4 0.6 0.8 1 1.2 1.4 1.6 1.8



Wavelengths (μ )m


0.6

0.7

0.8

0.9

1

0.4 0.6 0.8 1 1.2 1.4 1.6 1.8



Wavelengths (μ )m

2:3:24,12:59:4, , ,131Almucantar GSFC

((), I(), I(),P(),P()) Numerical inversion:Numerical inversion:-Accounting for uncertainty (F(F1111; -F; -F1212/F/F11 11 !!!)!!!) - Setting a priori constraints

aerosol particle sizes,aerosol particle sizes, refractive index, refractive index,

single scattering albedosingle scattering albedo

AERONET Polarized InversionAERONET Polarized Inversion

€

P11

,P12

,P22

,P33 ,,P34 ,,P44 , ≈ K ip λ;θ ;n;k( )

i;p( )

∑ ω p V ri( )

Forward Model:Forward Model:

Single Scat:Single Scat:

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

dV/dln(rdV/dln(rii)) n(n( ((

Principal Plane: ((), I(), I()) = 0.44, 0.5, 0.67, 0.87,1.02, 1.64, μmPolarization : ((), I(), I(),P(),P()) = 0.87μm Cape Verde aerosol

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.1 1 10

almucantarprinciple plane 0.87 μ ( )m with polarization

(4 + )principle plane channels polarization

/ (dV dlnR

μm3 /μm

2 )


28:9:23,18:7:54, _ , _ ,47Principal Plane Capo Verde

1.3

1.35

1.4

1.45

1.5

1.55

1.6

1.65

0.4 0.5 0.6 0.7 0.8 0.9 1

almucantarprinciple plane 0.87 μ ( )m with polarization

(4 + )principle plane channels polarization


(Wavelengths μ )m


0.6

0.7

0.8

0.9

1

0.4 0.5 0.6 0.7 0.8 0.9 1 1.1

almucantarprincipal plane (radiances)principal plane (polarization, 0.87 μ )m

(4 + )principal plane channels polar


(Wavelengths μ )m


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

Principal Plane: ((), I(), I()) =0.87μmPolarization : ((), I(), I(),P(),P()) = 0.87μm

Cape Verde aerosol

0.01

0.1

1

10

0 30 60 90 120 150

Measurements

Fitting

Radiance in Principle Plane

Scattering Anlge (degrees)

0

0.1

0.2

0.3

0.4

0.5

0.6

50 75 100 125 150

Measurements

Fitting

Linear Polarization (-F

12/F

11)

Scattering Anlge (degrees)

Fine and Coarse modes separations

RadianceRadiance

Beijing aerosol

0.1

1

10

100

0 45 90 135 180

totalfine modecoarse mode

Phase Function

Particle Radius (micron)

02:05:2003,09:27:51,PolarPP,Beijing,14

0

0.3

0.6

0.9

0 45 90 135 180

totalfine modecoarse mode

Linear Polarization (-F

12/F

11)

Particle Radius (micron)

02:05:2003,09:27:51,PolarPP,Beijing,14

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.1 1 10

dV/dlnR (

μm3 /μm

2 )


Coarse

Fine

Coarse

2:5:23,9:27:51, , ,14PolarPP Beijing

Beijing Aerosol

Flexible separation betweenfine and coarse modes

(curently: ~0.6 μm)

0.45μm

Retrieval using combinations of up-looking Ground-based and down-looking satellite

observations

Retrieved:

Aerosol Properties:- size distribution- real ref. ind. - imag. ref. ind(AERONET sky channels)

Surface Parameters:-BRDF (MISR channels)-Albedo (MODIS IR channels)

AERONET / POLDER-2 retrievalPOLDER-2 fit

Size distribution

BRDF

Biomass burningMongu, Zambia, June, 2003

AERONET Ground-based Sun-sky radiometer:AERONET Ground-based Sun-sky radiometer:

± 0.02 at± 0.02 at 6 channels6 channels: 0.34, 0.38, 0.44, 0.67, 0.87, 1.02, : 0.34, 0.38, 0.44, 0.67, 0.87, 1.02, 1.651.65 μμmm

± 0.05% at± 0.05% at4 channels4 channels: : 0.380.38, 0.44, 0.67, 0.87, 1.02, , 0.44, 0.67, 0.87, 1.02, 1.651.65 μμmm3° ≤ scattering angles ≤ ~70°3° ≤ scattering angles ≤ ~70°- PP± 0.02% at ± 0.02% at 0.870.87

MISR MISR Reflectance atReflectance at4 channels4 channels: 0.45, 0.55, 0.67, 0.87 : 0.45, 0.55, 0.67, 0.87 μμmm9 viewing angles9 viewing angles: ±70.5: ±70.5oo, ± 60, ± 60oo,, ± 45.6± 45.6oo, ± 26.1, ± 26.1oo, 0, 0oo

MODISMODISReflectance atReflectance at7 channels7 channels: 0.47, 0.55, 0.66, 0.87,1.2, 1.6, 2.1: 0.47, 0.55, 0.66, 0.87,1.2, 1.6, 2.1

AERONET/ MISR/ MODIS retrieval

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.

CAR - Cloud Absorption Radiometer

8 spectral channels: 0.34, 0.38, 0.47, 0.68, 0.87, 1.03, 1.19, 1.27 μm

Measures radiation transmitted* and reflected:

0° ≤ Obs. Zenith ≤ 180°0° ≤ Obs. Azimuth ≤ 360°

* Stray light problems for

scattering angles ≤ 10°

Flown by CV-580 aircraftat ~ 700 m above ground

Univ. of Washington CV-580

Optical thickness on September 6, 2000

AERONETAERONETdaily variationsdaily variations

0

0.5

1

1.5

2

2.5

5:00 7:00 9:00 11:00 13:00 15:00

Mongu/Zambia, September 6, 2000

1.02 μm.87μm.67μm.44μm.38μm.34μm

Optical Thickness

Time of DayCAR

AERONETalmucantar

AATS-14 AATS-14 versus AERONETAERONET

0

0.5

1

1.5

2

0.2 0.4 0.6 0.8 1 1.2

AERONET (ground-based)

AATS-14 (airborne)

"AERONET - AATS-14"

Optical Thickness

Wavelengths (μ )m

α=1.82

α=1.74α=2.12

Aerosol retrieved from combinedCAR - AERONET - AATS-14 obs.

0.4

0.5

0.6

0.7

0.8

0.9

0.4 0.6 0.8 1.0 1.2


Below PlaneAbove PlaneAERONET


Wavelength (μ )m

1.3

1.35

1.4

1.45

1.5

1.55

1.6

1.65

0.4 0.6 0.8 1 1.2

Real Part of Ref. Index

BelowAboveAERONET

Real Part of the Ref. Index

Wavelengths (μ )m

0

0.05

0.1

0.15

0.2

0.1 1.0 10

Volume Size Distribution

Below PlaneAbove PlaneBelow + AboveAERONET

dV/dlnR (

μm3 /μm

2 )

(Radius μ )m

Comparison of model retrieved BRDFwith corrected direct BRDF

Gatebe et al. 2003

0

0.1

0.2

0.3

0.4

0.5

-50 0 50

Vegetation model BRDF (lines)

6S corrected BRDF (points)

1.22 μm.87μm.67μm.47μm.34μm

( )Angle degree

Reflectance

BRDF constrains model:- positive and smooth;- PP symmetrical

Comparison of retrieved surface reflectance with other observations

Mongu, September 6, 2000

LambertianLambertian approximation

Mongu, Zambia

0

0.1

0.2

0.3

0.4

0.5

0.6

0.2 0.4 0.6 0.8 1 1.2 1.4

Lambertian Surface Albedo

AERONET/ POLDER (June, 2003)

CAR (Gatebe et al., 2000)

MODIS (Sept. 2 , Sept. 10)

Albedo

Wavelengths (μ )m

0

0.1

0.2

0.3

0.4

0.5

0.6

0.2 0.4 0.6 0.8 1 1.2 1.4

Lambertian Surface Albedo

CAR + AERONET inversion

CAR (Gatebe et al., 2000)

MODIS (Sept. 2 , Sept. 10)

Albedo

Wavelengths (μ )m

New Inversion Options:- Almucatars (any numbers of spectral channels)Almucatars (any numbers of spectral channels)- Principal planes (any numbers of spectral channels)Principal planes (any numbers of spectral channels)- Polarized Principle Planes Polarized Principle Planes (0.87 mm)(0.87 mm)

- Combined Principle Planes: Combined Principle Planes: Polarized (0.87 mm) + Regular (0.44 - 1.02mm)Polarized (0.87 mm) + Regular (0.44 - 1.02mm)

- Other Combined Cimel Data:Other Combined Cimel Data:-Almucantar + Principle Plane (?)Almucantar + Principle Plane (?)- Several Almucantars + Principle Planes (??)Several Almucantars + Principle Planes (??)

- 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

Offsets were considered in:

- optical thickness: - optical thickness:

- sky-channel calibration:- sky-channel calibration:

- azimuth angle pointing: - azimuth angle pointing:

- assumed ground reflectance:- assumed ground reflectance:

Aerosol models considered (bi - modal log-normal):(bi - modal log-normal):

- Water-soluble aerosol for 0.05 ≤ - Water-soluble aerosol for 0.05 ≤ (440) ≤ 1;(440) ≤ 1;

- Desert dust for 0.5 ≤ - Desert dust for 0.5 ≤ (440) ≤ 1;(440) ≤ 1;

- Biomass burning for 0.5 ≤ - Biomass burning for 0.5 ≤ (440) ≤ 1;(440) ≤ 1;

Δτ λ( )=±0.01; ±0.02;

ΔI λ;Θ( ) I λ;Θ( ) 100% = ±5%;Δφ=0.5o; 1o;

ΔA λ( )/ A λ( ) 100%= ±30%; ±50%;

Results summary:

--(440) ≤ 0.2(440) ≤ 0.2 - - ddV/V/ddlnr (lnr (++), ), nn(() () (--), ), kk(() () (--), ), (() () (--))

--(440) > 0.2(440) > 0.2 - - ddV/V/ddlnr (lnr (++), ), nn(() () (++),), k k(() () (++), ), (() () (++))

- - Angular pointing accuracy is critical for Angular pointing accuracy is critical for ddV/V/ddlnr of dustlnr of dust

((++) ) CAN BECAN BE retrievedretrieved ( (--) ) CAN NOT BECAN NOT BE retrieved retrieved

bias influence at 0

bias:

€

˜ ω 0 =τscat

τext+Δτ

0.7

0.75

0.8

0.85

0.9

0.95

0 0.2 0.4 0.6 0.8 1

0(real)

ω0(real)-0.03

τ+0.01

τ+0.02

τ+0.03

ω0

(retrieved)

τ

Sky Radiance bias:

€

˜ ω 0 =τscat 1-Δ( )

τext

=ω0 1-Δ( )

Random ERRORS in AERONET Random ERRORS in AERONET retrievalsretrievals

ASSUMPTIONS:- measurements have Normal Noise: - optical thickness: - optical thickness: 0.01 0.01

- sky-radiances: - sky-radiances: 5% 5%

0.00

20.00

40.00

60.00

80.00

0.1 1 10

(.44)=.5(.44)=.2(.44)=.5(.44)=1.

(%)Errors

(Radius μ )m

CONCLUSIONS:- the retrievals stable- important tendencies outlined

Rigorous ERRORS estimates:Rigorous ERRORS estimates: General caseGeneral case: : large number of unknownslarge number of unknowns

andand redundant measurements redundant measurements

U - matrix of partial derivatives in the vicinity of solution €

ˆ x i( )2

≈ Δˆ x irandom

( )2

+ Δˆ x ibias

( )2

€

CΔˆ x random = UTC-1U( )

-1

€

ˆ x bias = UTC-1U( )−1

UTC-1ΔIbias

ˆ x

Above is valid:- in linear approximation - for Normal Noise

- no a priori constraints

ERRORS estimates withERRORS estimates with a priori constraints a priori constraints

€

CΔˆ x random = UTC-1U + U a

T Ca−1Ua( )

-1

€

ˆ x bias = UTC-1U + U aT Ca

−1Ua( )−1

UTC-1ΔIbias + U aT Ca

−1ΔIabias

( )

ISSUES:- in linear approximation - for Normal Noise

- strongly dependent on a priori constraints- very challenging in most interesting cases

ERROR ERROR Factors:Factors:

Important Factors:- Aerosol Loading - Scattering Angle Range

- Number of Angles (homogeneity)- Aerosol Type

etc.

Examples of error estimates

0

0.05

0.1

0.15

0.1 1 10

dV/dlnR (

μm3 /μm

2 )

(Radius μ )m

,GSFC (.44)=.7

1.25

1.3

1.35

1.4

1.45

0.4 0.6 0.8 1

GSFC, (.44)=.7


(Wavelength μ )m

0.6

0.7

0.8

0.9

1

0.4 0.6 0.8 1

GSFC, (.44)=.7


(Wavelength μ )m

0.8

0.9

1

0.4 0.6 0.8 1

GSFC, (.44)=.7


(Wavelength μ )mhigh

loading

low loading

flaming combustionRio Branco, Brazil

smoldering combustion Quebec fires, July 2002

ABSORPTION of SMOKE

AERONET Inversions: Progress and Perspectives Oleg Dubovik (NASA / GSFC) Alexander Sinyuk (NASA /...

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Transcript of AERONET Inversions: Progress and Perspectives Oleg Dubovik (NASA / GSFC) Alexander Sinyuk (NASA /...