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  Atmospheric Correction for Dust Contaminated Ocean Regions

Menghua Wang and Wei ShiNOAA/NESDIS/STAR

E/RA3, Room 102, 5200 Auth Rd. Camp Springs, MD 20746, USA

Report of FY11 NASA ACE Funded ProjectMarch 14, 2012

Acknowledgements: We thank Oleg Dubovik and the AERONET group for providing dust model data. MODIS and CALIPSO data were obtained from NASA/GSFC and NASA Langley Research Center Atmospheric Science Data Center.

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Project Summary: This is a demonstration study for deriving improved MODIS-Aqua ocean color products over dust-contaminated ocean regions using the dust vertical profile data from CALIPSO and dust models that have been developed from the AERONET ground-based measurements.

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Current Satellite Ocean Color Retrievals Under Dust Condition 

1. World oceans are frequently covered with dust, especially in the West Africa coast, Arabian Sea and Persian Gulf, US west coast, etc.

2. Dust aerosols are strongly absorbing in the blue and deep blue band.

3. Current aerosol models for satellite ocean color processing are not working under dust condition (also need aerosol vertical distribution info).

4. Shi and Wang (2007) developed a method to detect absorbing aerosols, e.g., dust, smoke.

Shi, W., and Wang, M. (2007), Detection of turbid waters and absorbing aerosols for the MODIS ocean color data processing, Remote Sens. Environ., 110, 149-161.

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Efforts in Addressing Absorbing Aerosol Issue There have been significant efforts for addressing dust aerosol issue & its

effects on ocean color remote sensing (list a few):– Gordon, H. R., Du, T., and Zhang, T. (1997), Remote sensing of ocean color and aerosol

properties: resolving the issue of aerosol absorption, Appl. Opt., 36, 8670-8684.– Fukushima, H., and Toratani, H. (1997), Asian dust aerosol: optical effect on satellite

ocean color signal and a scheme of its correction, J. Geophys. Res., 102, 17119-17130.– Moulin, C., Gordon, H. R., Banzon, V. F., and Evans, R. H. (2001a), Assessment of

Saharan dust absorption in the visible from SeaWiFS imagery, J. Geophys. Res., 106, 18,239-218,249.

– Moulin, C., Gordon, H. R., Chomko, R. M., Banzon, V. F., and Evans, R. H. (2001b), Atmospheric correction of ocean color imagery through thick layers of Saharan dust, Geophys. Res. Letters, 28, 5-8.

– Claustre, H., Morel, A., Hooker, S.B., Babin, M., Antoine, D., Oubelkheir, K., Bricaud, A., Leblanc, K., Queuiner, B. and Maritorena, S. (2002), Is desert dust making oligotrophic water greener? Geophy. Research Letter, 29, 1469, doi: 10.1029/2001GL014056.

– Cattrall, C., Carder, K. L., and Gordon, H. R. (2003), Columnar aerosol single-scattering albedo and phase function retrieved from sky radiance over the ocean: Measurements of Saharan dust, J. Geophys. Res., 108 (D9), 4287, doi:10.1029/2002JD002497.

– Wiggert, J. D., Murtugudde, R. G. and Christian, J. R. (2006), Annual ecosystem variability in the tropical Indian Ocean: Results of a coupled bio-physical ocean general circulation model. Deep-Sea Research Part II, 53: 644-676.

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AERONET Dust Aerosol Model

AERONET dust models developed by Dubovik et al. are used for generating aerosol lookup tables:– Dubovik, O., Holben, B. N., Eck, T. F., Smirnov, A., Kaufman, Y. J.,

King, M. D., Tanre, D., and Slutsker, I. (2002a), Variability of absorption and optical properties of key aerosol types observed in worldwide locations, J. Atmos. Sci., 59, 590-608.

– Dubovik, O., Holben, B. N., Lapyonok, T., Sinyuk, A., Mishchenko, M., Yang, P., and Slutsker, I. (2002b), Non-spherical aerosol retrieval method employing light scattering by spheroids, Geophy. Res. Lett., 29, 1451, doi:1410.1029/2001GL014506.

– Dubovik, O., Sinyuk, A., Lapyonok, T., Holben, B. N., Mishchenko, M., Yang, P., Eck, T. F., Volten, H., Munoz, O., Veihelmann, B., Zande, W. J. v. d., Leon, J.-F., Sorokin, M., and Slutsker, I. (2006), Application of spheroid models to account for aerosol particle nonsphericity in remote sensing of desert dust, J. Geophys. Res., 111, D11208, doi:11210.11029/12005JD006619.

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Dust Aerosol Scattering Phase Function

10-1

100

101

102

0 30 60 90 120 150 180

412 nm555 nm667 nm869 nm1240 nm2130 nm

Scattering Angle (Deg.)

(a)

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Dust Aerosol Properties: Single-scattering Albedo and Asymmetry Parameter

•Dust property varies with wavelength, in particularly, in visible bands.•Dust particles are almost non-absorbing at the NIR and SWIR bands, while they are absorbing at visible bands. 0.6

0.7

0.8

0.9

1

1.1

400 800 1200 1600 2000

Single-Scat AlbedoAsymmetry Parameter

Wavelength (nm)

(b)

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Dust Aerosol Lookup Tables

Dust aerosol lookup tables (including atmospheric diffuse transmittance tables) were generated with the vector radiative transfer model for different aerosol vertical profiles located at (from bottom): 0-km, 1-km, 2-km, 4-km, 6-km, 8-km, 10-km, and 99-km.

4 dust aerosol size distributions corresponding to AOT at 1020 nm of 0.3, 0.6, 1.0, and 1.5.

14 dust AOT at 865 nm are: 0.02, 0.05, 0.1, 0.15, 0.2, 0.3, 0.4, 0.6, 0.8, 1.0, 1.5, 2.0, 2.5, 3.0.

Solar-zenith angles from 0 to 80 (Deg.) at every 2.5 (Deg.). Sensor-zenith angles from 1 to 75 (Deg.) at every ~2 (Deg.). Relative azimuth angle from 0 to 180 (Deg.) at every 10 (Deg.). MODIS 16 spectral bands at 412, 443, 469, 488, 531, 551, 555,

640, 667, 678, 748, 859, 869, 1240, 1640, and 2130 nm.

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TOA Reflectance

10-2

10-1

400 800 1200 1600 2000

τa(869) = 0.1

τa(869) = 0.3

τa(869) = 0.6

τa(869) = 1.0

( )Wavelength nm

, TOA Typical Radianceθ0 = 20o, θ = 45o, Δφ = 90o

, 4 , AERONET Dust Model km Layer Black Ocean(c)

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Effects of Dust Aerosol Vertical Distribution

0

0.005

0.01

0.015

400 500 600 700 800

1km vs. 3km bottom-layer1km vs. 6km bottom-layer1km vs. 9km bottom-layer

Wavelength (nm)

τa(869) = 0.6, θ

0 = 60o, θ = 45o, Δφ = 90o

, AERONET Dust Model Black Ocean

(d)

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Atmospheric Correction: Simulations

-0.002

-0.001

0

0.001

0.002

0 10 20 30 40 50 60 70 80

412 nm443 nm488 nm531 nm551 nm

Solar Zenith Angle (Deg.)

τa(865) = 0.1, θ = 20o, Δφ = 90o

(a)

The SWIR Algorithm: 1240 nm and 2130 nmAeronet Dust Model (dH) at 3km bottom layerAssuming: dust at 2km layer

-0.003

-0.002

-0.001

0

0.001

0 10 20 30 40 50 60 70 80

412 nm443 nm488 nm531 nm551 nm

Solar Zenith Angle (Deg.)

τa(865) = 0.3, θ = 20o, Δφ = 90o

(b)

The SWIR Algorithm: 1240 nm and 2130 nmAeronet Dust Model (dH) at 3km bottom layerAssuming: dust at 2km layer

Derived water-leaving reflectances are biased low due to a wrong assumption of dust aerosol layer (more so for larger aerosol optical thickness at shorter wavelengths).

Dust layer at 3-km, but assumed at 2-km.

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NASA Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO)

• Launched on April 28, 2006• Part of the Aqua satellite constellation (or A-Train)• CALIPSO lags MODIS-Aqua by 1 to 2 minutes.• Wavelengths: 532 nm & 1064 nm• Pulse energy: 110 mJoule/channel• Footprint/FOV: 100 m/ 130 µrad• Vertical resolution: 30-60 m• Horizontal resolution: 333 m

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CALIPSO L2 Aerosol & Cloud Products

An example of data collected by CALIPSO's lidar in June 2006 Aerosols

•Height, Thickness•Optical depth, τ•Backscatter, & betaa(z)•Extinction, σa

Clouds•Height•Thickness•Optical depth, τ•Backscatter, &betac(z)•Extinction, σc

•Ice/water phase•Ice cloud emissivity, ε•Ice particle size

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CASE ONE : Dust In Japan Sea on 5/26/2007

MODIS Granule (2007146)

Calip

so tr

ack

Dust height 0–2.5 km

MODIS True Color Image and CALIPSO Track532 nm total attenuated backscatter

0 0.01 sr-1km-1

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CASE ONE : Ocean Color Retrieval Comparison MODIS Granule (2007146)With A No Dust Case on 5/22/2007

nLw412-NIR-02dust nLw412-NIR nLw412-NIR 5/22/2007

nLw443-NIR-02dust nLw443-NIR nLw443-NIR 5/22/2007

Spectral comparison

0 3.0 mW/cm3 µm sr

No Dust

No Dust

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nLw667-NIR-02dust nLw667-NIR nLw667-NIR 5/22/2007

0 1.0 mW/cm3 µm sr

CASE ONE : Ocean Color Retrieval Comparison MODIS Granule (2007146)With a No Dust Case on 5/22/2007

No Dust

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Taua531 comparison along the track of CALIPSO

CASE ONE : Ocean Color Retrieval Comparison MODIS Granule(2007146)

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Spectral comparison at location of [38.42°N, 135.90°E] (marked in the Calipso Track marked in 2007146)

CASE ONE : Ocean Color Retrieval Comparison MODIS Granule (2007146)

Old

New

No Dust Case

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Total Attenuated Backscatter

CASE 2 : Dust Gulf of OMAN on 5/26/2007

0 0.01 sr-1km-1

MODIS Granule: 2006326

Dust Height 0 - 1.5 km

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CASE 2: Comparison of ocean color products from NIR-dust and NIRnL

w(4

12)

nLw

(443

)

Dust NIR-02km Corr. Standard NIR Corr.

MODIS Granule: 2006326

0 3.0 mW/cm3 µm sr

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nLw

(488

)nL

w(5

51)

Dust NIR-02km Corr. Standard NIR Corr.

CASE 2: Comparison of ocean color products from NIR-dust and NIR

MODIS Granule: 2006326

0 3.0 mW/cm3 µm sr

22

nLw

(667

)sc

ale:

0 - 1

Chla

Scal

e:0.

1 –

32 lo

g

Dust NIR-02km Corr. Standard NIR Corr.

CASE 2: Comparison of ocean color products from NIR-dust and NIR

MODIS Granule: 2006326

0 1.0 mW/cm3 µm sr

0.1 32 mg/m3

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AOT(

531)

scal

e:0

- 0.6

AOT(

869)

Scal

e:0.

- 0.6

Dust NIR-02km Corr. Standard NIR Corr.

Spectral Comparison

CASE 2: Comparison of ocean color products from NIR-dust and NIR

MODIS Granule: 2006326

0.60.0

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Taua531 Comparison along Calipso Track Spectral Comparison at [22.34°N, 61.97°E]

CASE 2: Comparison of ocean color products from NIR-dust and NIR

MODIS Granule: 2006326

Old

New

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Atmospheric Correction for Dust Contaminated Ocean Region

Menghua Wang and Wei Shi

CALIPSO Data Provide Dust Height

MODIS True Color Image (Gulf of Oman)

Nov. 22, 2006

Region is covered by dust

nLw(443) from the standard-NIR method: significantly biased low values over the region.

nLw(443) from a new approach, dust models & dust height, show increased / improved results.

Chlorophyll-a from a new approach, clearly show ocean features (e.g., eddies).

CALIPSO Track

Old Results

New Results

New Results

Improved ocean color products Use realistic dust aerosol models CALIPSO data--dust height information Promising from preliminary results

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Conclusions

For ocean color remote sensing over dust contaminated ocean regions, we need realistic dust aerosol models and dust vertical distribution (~0.5-1km) information. We demonstrate an approach to carry out atmospheric correction for satellite ocean color observations under dust conditions using AERONET dust models and dust height information from CALIPSO measurements. With this approach, ocean color results (nLws) are improved. Dust aerosol height along the CALIPSO tracking are assumed to be representative for the entire dust region. This might not be accurate and can lead to errors in nLw retrievals. Future research is still necessary on improving dust aerosol models, how to effectively/accurately obtain aerosol height information (e.g., its spatial distribution), algorithm implementation, etc., in atmospheric correction for satellite ocean color products.