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 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,

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, – 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, – 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, ,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: /2001GL – 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: /2002JD – 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:

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, – 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: /2001GL – 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: /12005JD

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 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.

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: 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, & beta a (z) Extinction, σ a Clouds Height Thickness Optical depth, τ Backscatter, &beta c (z) Extinction, σ c Ice/water phase Ice cloud emissivity, ε Ice particle size

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

15 CASE ONE : Ocean Color Retrieval Comparison MODIS Granule ( ) With A No Dust Case on 5/22/2007 nLw412-NIR-02dust nLw412-NIRnLw412-NIR 5/22/2007 nLw443-NIR-02dustnLw443-NIRnLw443-NIR 5/22/2007 Spectral comparison 03.0 mW/cm 3 µm sr No Dust

16 nLw667-NIR-02dustnLw667-NIRnLw667-NIR 5/22/ mW/cm 3 µm sr CASE ONE : Ocean Color Retrieval Comparison MODIS Granule ( ) With a No Dust Case on 5/22/2007 No Dust

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

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

19 Total Attenuated Backscatter CASE 2 : Dust Gulf of OMAN on 5/26/ sr -1 km -1 MODIS Granule: Dust Height km

20 CASE 2: Comparison of ocean color products from NIR-dust and NIR nLw(412) nLw(443) Dust NIR-02km Corr.Standard NIR Corr. MODIS Granule: mW/cm 3 µm sr

21 nLw(488) nLw(551) Dust NIR-02km Corr. Standard NIR Corr. CASE 2: Comparison of ocean color products from NIR-dust and NIR MODIS Granule: mW/cm 3 µm sr

22 nLw(667) scale:0 - 1 Chla Scale:0.1 – 32 log Dust NIR-02km Corr.Standard NIR Corr. CASE 2: Comparison of ocean color products from NIR-dust and NIR MODIS Granule: mW/cm 3 µm sr mg/m 3

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

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

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

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.