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Atmospheric Correction for Dust Contaminated Ocean Regions PowerPoint Presentation
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Atmospheric Correction for Dust Contaminated Ocean Regions

Atmospheric Correction for Dust Contaminated Ocean Regions

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Atmospheric Correction for Dust Contaminated Ocean Regions

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  1. Atmospheric Correction for Dust Contaminated Ocean Regions Menghua Wang and Wei Shi NOAA/NESDIS/STAR E/RA3, Room 102, 5200 Auth Rd. Camp Springs, MD 20746, USA Report of FY11 NASA ACE Funded Project March 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.

  2. 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.

  3. Current Satellite Ocean Color Retrievals Under Dust Condition • World oceans are frequently covered with dust, especially in the West Africa coast, Arabian Sea and Persian Gulf, US west coast, etc. • Dust aerosols are strongly absorbing in the blue and deep blue band. • Current aerosol models for satellite ocean color processing are not working under dust condition (also need aerosol vertical distribution info). • 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.

  4. 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.

  5. 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.

  6. Dust Aerosol Scattering Phase Function

  7. 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.

  8. 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.

  9. TOA Reflectance

  10. Effects of Dust Aerosol Vertical Distribution

  11. Atmospheric Correction: Simulations Dust layer at 3-km, but assumed at 2-km. 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).

  12. 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

  13. 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

  14. CASE ONE : Dust In Japan Sea on 5/26/2007 MODIS Granule (2007146) MODIS True Color Image and CALIPSO Track 532 nm total attenuated backscatter Calipso track 0 0.01 sr-1km-1 Dust height 0–2.5 km

  15. CASE ONE : Ocean Color Retrieval Comparison MODIS Granule (2007146) With A No Dust Case on 5/22/2007 nLw412-NIR nLw412-NIR 5/22/2007 nLw412-NIR-02dust No Dust nLw443-NIR-02dust nLw443-NIR nLw443-NIR 5/22/2007 Spectral comparison No Dust 0 3.0 mW/cm3 µm sr

  16. CASE ONE : Ocean Color Retrieval Comparison MODIS Granule (2007146) With a No Dust Case on 5/22/2007 nLw667-NIR-02dust nLw667-NIR nLw667-NIR 5/22/2007 No Dust 1.0 mW/cm3 µm sr 0

  17. CASE ONE : Ocean Color Retrieval Comparison MODIS Granule(2007146) Taua531 comparison along the track of CALIPSO

  18. CASE ONE : Ocean Color Retrieval Comparison MODIS Granule (2007146) Spectral comparison at location of [38.42°N, 135.90°E] (marked in the Calipso Track marked in 2007146) No Dust Case New Old

  19. CASE 2 : Dust Gulf of OMAN on 5/26/2007 MODIS Granule: 2006326 Total Attenuated Backscatter 0 0.01 sr-1km-1 Dust Height 0 - 1.5 km

  20. CASE 2: Comparison of ocean color products from NIR-dust and NIR MODIS Granule: 2006326 Dust NIR-02km Corr. Standard NIR Corr. nLw(412) nLw(443) 3.0 mW/cm3 µm sr 0

  21. CASE 2: Comparison of ocean color products from NIR-dust and NIR MODIS Granule: 2006326 Standard NIR Corr. Dust NIR-02km Corr. nLw(488) nLw(551) 3.0 mW/cm3 µm sr 0

  22. CASE 2: Comparison of ocean color products from NIR-dust and NIR MODIS Granule: 2006326 Dust NIR-02km Corr. Standard NIR Corr. nLw(667) scale:0 - 1 Chla Scale:0.1 – 32 log 0.1 32 mg/m3 1.0 mW/cm3 µm sr 0

  23. CASE 2: Comparison of ocean color products from NIR-dust and NIR MODIS Granule: 2006326 Standard NIR Corr. Dust NIR-02km Corr. AOT(531) scale:0 - 0.6 AOT(869) Scale:0.- 0.6 Spectral Comparison 0.0 0.6

  24. CASE 2: Comparison of ocean color products from NIR-dust and NIR MODIS Granule: 2006326 Taua531 Comparison along Calipso Track Spectral Comparison at [22.34°N, 61.97°E] New Old

  25. Old Results MODIS True Color Image (Gulf of Oman) Region is covered by dust New Results Nov. 22, 2006 New Results CALIPSO Data Provide Dust Height Atmospheric Correction for Dust Contaminated Ocean Region Menghua Wang and Wei Shi nLw(443) from the standard-NIR method: significantly biased low values over the region. • Improved ocean color products • Use realistic dust aerosol models • CALIPSO data--dust height information • Promising from preliminary results nLw(443) from a new approach, dust models & dust height, show increased / improved results. CALIPSO Track Chlorophyll-a from a new approach, clearly show ocean features (e.g., eddies).

  26. 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.