Radiative Transfer Codes for Atmospheric Radiative Transfer Codes for Atmospheric Correction and Aerosol Retrievals:Correction and Aerosol Retrievals:

Intercomparison StudyIntercomparison Study

AEROCENTER Fall Seminar Series, October 2nd, 2007

Svetlana Y. Kotchenova & Eric F. Vermote

The study is being performed in collaboration with: Robert Levy, Alexei Lyapustin, and Omar Torres

Project DescriptionProject Description

2

The project is devoted to the comparison and detailed evaluation of five

atmospheric RT codes

incorporated in different

satellite data processing

algorithms

Coulson’s tabulated

values(benchmark)

6SV1.1(vector)

Svetlana & Eric

SHARM(scalar)

Alexei

RT3(vector)

Robert

VPD(vector)

Omar

MODTRAN(scalar)Svetlana

Monte Carlo(benchmark)

Svetlana & Ericonly molecular

atmosphere

only molecular atmosphere

Applications of the codesApplications of the codes

6SV1.1 (Second Simulation of a Satellite Signal in the Solar Spectrum, Vector, version 1.1): MODIS atmospheric correction and internal aerosol inversion

RT3 (Radiative Transfer 3): MODIS coarse resolution (10-km) aerosol retrieval

VPD (Vector Program D): TOMS (Total Ozone Mapping Spectrometer) aerosol inversion

SHARM (Spherical Harmonics): MAIAC (Multi-Angle Implementation of Atmospheric Correction for MODIS)

3

MODTRAN (Moderate Resolution Atmospheric Transmittance and Radiance Code): AVIRIS (Airborne Visible/Infrared Imaging Spectrometer) atmospheric correction

Description of the codes: 6SV1.1Description of the codes: 6SV1.1

4

Spectrum: 350 to 3750 nmMolecular atmosphere:

6 code-embedded & 2 user-defined

modelsAerosol atmosphere:

6 code-embedded & 4 user-defined

models & AERONET

homogeneous &non-homogeneous with & without directional effect (10 BRDF + 1 user-defined models)

Ground surface:

AATSR, ALI, ASTER, AVHRR, ETM, GLI,

GOES, HRV, HYPBLUE, MAS,

MERIS, METEO, MSS, TM, MODIS, POLDER,

SeaWiFS, VIIRS, & VGT – 19 in total

Instruments:

Author: E. Vermote (University of Maryland, USA)

Modified: E. Vermote et al.

Language: Fortran 77, 95

Features:

http://6s.ltdri.org

Publications + Interface to create input files

Description of the codes: RT3Description of the codes: RT3

5

Author: F. Evan (Colorado State University)

Language: Fortran 77

Input:

Disadvantages:

1) pre-computed sets of output angles (interpolation might be needed)

2) no embedded MIE-code (combination with a MIE-code is needed to simulate aerosols)

Description of the codes: SHARMDescription of the codes: SHARM

6

Author: T. Muldashev (Space Research Institute, Kazakhstan)

Modified: A. Lyapustin

Language: C/C++

Input:

Advantages: very fast, simultaneous simulations for multiple geometries and wavelengths

1.atmMIE

config.par

1L.sfc

Description of the codes: MODTRANDescription of the codes: MODTRAN

7

Author: Berk et al. (Air Force Research Laboratory)

Language: Fortran 77

Modeling Features: molecular atmospheres (a lot of effort is put into gas absorption!), aerosols (with the help of DISORT at 16 Gaussian angles), clouds, surface

Input: in the form of formatted “cards” (quite painful!)

Output: single geometry but for a range of wavelengths

card 1acard 1

tape

5 –

mol

ecu

lar

atm

osph

ere

card 2

Project HistoryProject History

8

2005 2006 2007 2008

6SV&

VPD

&RT3

&SHARM

Coulson’s tables

MonteCarlo

6SV&

&RT3

&SHARM

VPD

discussions, calculations,

Web site creation ...

Why do you ignore MODTRAN?

MODTRAN

Goals of the projectGoals of the project

to evaluate the accuracy of each code based on the comparison with standard benchmark references such as Coulson’s tabulated values and a Monte Carlo approach

to illustrate differences between individual simulations of the code

to determine how the revealed differences influence on the accuracy of aerosol optical thickness and surface reflectance retrievals

to create reference (benchmark) data sets that can be used in future code comparison studies

9

Presentation of the resultsPresentation of the results

10

All results will be put on the Internet and summarized in a manuscript titled “Radiative Transfer Codes for Atmospheric Correction and Aerosol Retrievals:

Intercomparison Study” which will be submitted to Applied Optics.

http://rtcodes.ltdri.org

Characterization of a RT codeCharacterization of a RT code

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In regard to remote sensing applications...

1. Versatility

2. Accuracy

3. User-friendliness

4. Speed

6SV1.16SV1.1, , SHARMSHARM, , MODTRANMODTRAN, , VPDVPD & & RT3RT3 (RT3 needs to be combined with a MIE-code) (RT3 needs to be combined with a MIE-code)

to be determinedto be determined

6SV1.16SV1.1 & & SHARMSHARM, , RT3RT3, , MODTRANMODTRAN, , VPDVPD (VPD is not publicly available) (VPD is not publicly available)

to be determinedto be determined

Code AccuracyCode Accuracy

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The general atmospheric RT code accuracy requirement for pure simulation studies is 1%.

Reference: Muldashev et al., Spherical harmonics method in the problem of radiative transfer in the atmosphere-surface system, Journal of Quantitative Spectroscopy and Radiative Transfer, 61(3), 393-404, 1999.

Will violation of this requirement

have a significant effect on the

resulting satellite product?

Step 1: comparison with benchmarks to see if there is violation

Step 2: evaluation of the impact of violation

Benchmarks: Coulson’s tablesBenchmarks: Coulson’s tables

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Coulson’s tabulated values represent the complete solution of the Rayleigh problem for a molecular atmosphere.

Reference: Coulson et al., Tables related to radiation emerging from a planetary atmosphere with Rayleigh scattering (1960).

Benchmarks: Monte CarloBenchmarks: Monte Carlo

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The code is written by F.M. Bréon (le Laboratoire des Sciences du Climat et de l'Environnement, France) based on the Stokes vector approach.

Languages: Fortran, C.

Limitations: large amounts of calculation time and angular space discretization.

Comparison ProcedureComparison Procedure

larger particles

direction of incident light

direction of incident light

1. Molecular Atmosphere (surf = 0.0; 0.25)

3. Mixed Atmosphere (surf = 0.0; 0.25)

2. Aerosol Atmosphere (surf = 0.0)

surf is the reflectance of a

Lambertian surface

The same procedure was usedin the previous comparison study: A. Lyapustin “Radiative transfer code SHARM-3D for radiance simulations over a non-Lambertian nonhomogeneous surface: intercomparison study”, Applied Optics, 41(27), 5607-5615.

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Molecular Atmosphere: ConditionsMolecular Atmosphere: Conditions

mol (, nm) 0.1 (530) 0.25 (440) 0.5 (360)

surf 0.0 0.25 0.0 0.25 0.0 0.25

θs, deg.23.073953.130178.4630

0.036.869966.4218

0.036.869966.4218

23.073953.130178.4630

23.073953.130178.4630

0.036.869966.4218

θv, deg. as in Coulson’s tables

φ, deg. 0.0; 90.0; 180

* mol is the molecular optical thickness

is the wavelength

surf is the surface reflectance

θs is the sun zenith angle

θv is the view zenith angle

φ is the relative azimuth

All RT codes are compared to the Coulson’s tabulated values.

** Monte Carlo is used only as an auxiliary means here.

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Molecular Atmosphere: ResultsMolecular Atmosphere: Results

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SZA AZ surfmolvsCoul

surfmolvscode

surfmolvsCoul

surfmolvmol %100*),,,,(

),,,,(),,,,(

9

1),,(

We calculate the absolute values of average relative differences:

Aerosol Atmosphere: ConditionsAerosol Atmosphere: Conditions

Model Urban-Industrial and Mixed Biomass Burning Biomass Burning

LocationGSFC,

Greenbelt, MD (1993–2000)

Amazonian forest,Brazil (1993-1994),Bolivia (1998-1999)

African savanna,Zambia (1995-2000)

Range of τaer 0.1 ≤ (440) ≤ 1.0 0.1 ≤ (440) ≤ 3.0 0.1 ≤ (440) ≤ 1.5

Values of τaer selected for this study 0.2; 0.8 0.2; 0.8; 2.0 0.2; 0.8

Real and imaginary parts of refractive index

1.41-0.03(440); 0.003 1.47;0.0093

1.51;0.021

SSA at = 412/440/670 nm 0.97/0.98/0.97 0.94/0.94/0.93 0.88/0.88/0.84

rVf , m 0.12+0.11(440) 0.14+0.013(440) 0.12+0.025(440)

f, m 0.38 0.40 0.40

rVc, m 3.03+0.49(440) 3.27+0.58(440) 3.22+0.71(440)

c, m 0.75 0.79 0.73

CVf , m3/m2 0.15(440) 0.12(440) 0.12(440)

CVc, m3/m2 0.01+0.04(440) 0.05(440) 0.09(440)

6SV1.1 is compared to Monte Carlo and then the other codes are compared to 6SV1.1...

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Aerosol Atmosphere: Results (compared to MC)Aerosol Atmosphere: Results (compared to MC)

... 6SV1.1 can be used as benchmark because it demonstrates good agreement with MC

θs = {0.0°, 23.0°, 50.0°}

black soil

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Aerosol Atmosphere: Results (compared to 6SV)Aerosol Atmosphere: Results (compared to 6SV)

SZA AZ aeraervs1SV6

aeraervscode

aeraervs1SV6

aeraervaer %100*)m,,,,,(

)m,,,,,()m,,,,,(

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1)m,,,(

We calculate the absolute values of average relative differences:

* maer is the selected aerosol model20

Mixed Atmosphere: ConditionsMixed Atmosphere: Conditions

Ground Surface

Ozone, Stratospheric Aerosols

8 Km

20 Km

Molecules (Rayleigh Scattering)

H2O, Tropospheric Aerosol

2-3 Km

O2, CO2

Trace Gases

We simply added a molecular atmosphere to all considered aerosol models.

)aeraeraer

molmolmol

H/zexp()0()z(

)H/zexp()0()z(

Profiles:

Mixture:

Molecular optical thickness:

= 412 nm - mol = 0.303

= 440 nm - mol = 0.232

= 670 nm - mol = 0.042

)]z()z()[z()z(

)]z()z(/[)z()z(

aermolaeraer

aermolmolmol

21

Mixed Atmosphere: Results (compared to MC)Mixed Atmosphere: Results (compared to MC)

6SV1.1 demonstrates relatively good agreement with MC (within 0.85%)

θs = {0.0°, 23.0°, 50.0°}

mol = 0.303

black soil

aer = 0.2, θs = 0.0°

aer = 0.8, θs = 0.0°

Molecular + Urban-industrial aerosol

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Mixed Atmosphere: Results (compared to 6SV)Mixed Atmosphere: Results (compared to 6SV)

Again, we calculate the absolute values of average relative differences:

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Accuracy vs. SpeedAccuracy vs. Speed

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Time for 1 run (the case of a mixed atmosphere (λ = 440 nm, AF, aer = 0.8) + surface):

SHARM: ≈ 5.6 s (7.3 s for a number of angles 6 x 16 x 3)

6SV1.1: ≈ 3 s (this time x number of SZA)

Monte Carlo: ≈ 45 min (for one SZA)

Time is important: code comparison like this one

Time is not that important: calculation of LUTs

Accuracy depends on many factors:

SHARM: the number of harmonics

6SV1: the number of Legendre coefficients, calculation layers and angles

VPD for a molecular atmosphereVPD for a molecular atmosphere

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Molecular atmosphere by VPD:

Good results for a molecular

atmosphere do not mean that

the accuracy of aerosol

simulations will be satisfactory!

Aerosol atmosphere by MODTRAN:

Error on AOT Retrieval: TheoryError on AOT Retrieval: Theory

Reflectance as function of AOT(calculated by SHARM)

0.11000

0.11500

0.12000

0.12500

0.13000

0.13500

0.14000

0.14500

0.15000

0.18 0.20 0.22 0.24 0.26 0.28

AOT

TO

A R

efle

ctan

ce VZA = 0.0

VZA = 16.2602

VZA = 32.8599

VZA = 50.2082

)(v

)(s

)(s

)()()()()( sssv

)()(

)()()( 1

1

s1

ss

)()( 1sv

)(

)()( sv

2

s2

s )()()(

1)

is the TOA reflectance of a vector code,

is the TOA reflectance of a scalar code,

is the error of a scalar code,

2)

From (1) and (2) we can calculate the AOT

retrieval error:

, where

Assumption: TOA reflectance is a linear function of AOT

The accuracy of 6SV retrievals ?

1% (compared to MC)

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Error on AOT retrieval: ResultsError on AOT retrieval: Results

Molecular + Aerosol (African Savanna, aer = 0.2):

SHARM: aer = 0.2 ± 0.14

6SV: aer = 0.2 ± 0.01

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Error on AOT retrieval: Results (Cont.)Error on AOT retrieval: Results (Cont.)

Molecular + Aerosol (African Savanna, aer = 0.8):

SHARM: aer = 0.8 ± 0.15

6SV: aer = 0.8 ± 0.05

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AOT Retrieval from MODIS dataAOT Retrieval from MODIS data

MODIS Land Surface Reflectance algorithm by Vermote et al.

Multi-Angle Implementation of Atmospheric Correction for

MODIS by Lyapustin & Wang490 nm

470 nm

443 nm

412 nm

AOT

0.2

0.4

0.5

Ex.: AERONET site Alta Floresta, day 197 of 2003

Ex.: Part of Arabian Peninsula, day 207 of 2005

470 nm

670 nm

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Error on SR Retrieval: TheoryError on SR Retrieval: Theory

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LLLLLL )()()()()( sssv

LLLLLL

LLL

)()()()(

)( 11

s1

ss

1)

)()( 1sv LL 2)

The SR retrieval error:

)(

)()( sv

L

LLL

LL

LLL

2

s2

s )()()(, where

The same procedure as for AOT retrievals, but is replaced by surface reflectance L

(L = 0.05, dL = 0.01)

Error on SR Retrieval: ResultsError on SR Retrieval: Results

Molecular + Aerosol (Amazonian Forest, aer = 0.2) + Surface (Lambertian, surf = 0.05):

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SHARM: surf = 0.05 ± 0.01

6SV: surf = 0.05 ± 0.002

Error on SR Retrieval: Results (Cont.)Error on SR Retrieval: Results (Cont.)

Molecular + Aerosol (Amazonian Forest, aer = 0.8) + Surface (Lambertian, surf = 0.05):

SHARM: surf = 0.05 ± 0.01

6SV: surf = 0.05 ± 0.003

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Vector ? Scalar for Remote SensingVector ? Scalar for Remote Sensing

Is it important to use a vector code?

1) AOT (+ other aerosol properties) retrievals:

2) surface reflectance retrievals:

pre-assigned set of aerosol models:

Smoke LABSSmoke HABSUrban POLU

Urban CLEAN

+

important, from a theoretical point of view

important

The accuracy of LUTs directly depends on the RT code simulations.

The best solution is to calculate a product error budget.

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Reference data setReference data set

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The goal is to use 6SV1 to create a reference data set for further code comparison studies.

......

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Thank you for your attention!Thank you for your attention!

Questions?..Questions?..

skotchen@ltdri.orgskotchen@ltdri.org