Development of Coastal Observation Platform in LIS - RAMMB by pptfiles


									    Ocean Color Radiometer Measurements of Long
Island Sound Coastal Observational platform (LISCO):
  Comparisons with Satellite Data & Assessments of

          Presenter: Soe Min Hlaing
  Mentor/ Co-Mentor: Dr. Samir Ahmed/ Dr. Alexander Gilerson
            NOAA - CREST, City College of New York
                            Ocean Color
 Constituents of the water such as phytoplankton biomass can be estimated
   through ocean color.
 Phytoplankton biomass is an important parameter in the studies of Global
   Warming to regional ecological systems.
 Amount of phytoplankton in the ocean can be traced by the concentration of
   the optically active pigment chlorophyll [Chl].

                      Global chlorophyll Concentration [Chl] Image
    Remote Sensing of the Ocean Color

    Absorption Spectrum of Water              Specific Absorption Spectrum of [Chl]

   Absorption of Water is weakest in the visible part of the spectrum, so light
    can penetrate down to 50 m in clear water.
   Chlorophyll has optically active features in the visible region of the
   Chlorophyll absorb strongly in the blue and violet/ ultra violet regions of the
                     Reflectance spectra of the open ocean
                             [Chl]=0.2 mg/m3

                               [Chl]=1.0 mg/m3

                                              [Chl]=10 mg/m3



                       400   500        600         700    800

                                   Wavelength, nm
                Remote Sensing Reflectance Spectra of            Chlorophyll Concentration [Chl] as function of
                Ocean Water with Different Level of [Chl]                     Blue – Green Ratio

               In the open ocean chlorophyll is the main constituent of the water.
               With increasing [Chl] water changes its color from blue to green.
               Therefore [Chl] can be well characterized by blue-green ratio.
               Blue-Green ratio algorithm does not work in coastal due to the
                     complication of color dissolved organic matters (CDOM)
                Ocean Color Satellite Sensors
 SeaWIFS (NASA) on GeoEye's satellite
        8 spectral bands (from 412 to 865 nm) with 1.1 km resolution

 MODIS (NASA) on Terra and Aqua satellite
    36 spectral bands (from 412 to 15 μm) with 250m - 1km resolutions

 MERIS (ESA) on ENVISAT satellite
      16 spectral bands (from 412nm to 14.4 um) with 250m - 1km resolutions

 OCM2 (India) on Oceansat-2 satellite
             8 spectral bands (400 to 900nm) with 1 – 4 km resolutions

 VIIRS (NASA) future replacement of MODIS, planned to launch in 2011
            22 Spectral bands (370nm to 12.5 um) with 650m resolution
    Contribution of atmospheric radiance to the
                     total signal
                                                     Radiances             Sensor
               Solar Flux

                               Surface Reflection

           Diffuse Sky Light
           Wavy Sea Surface

                                                                  Water Leaving Radiances

   Space-borne sensors view the sea through the atmosphere, thus atmospheric
    perturbing effects, surface reflections, etc. are to be removed from the measured
    total radiance.
   Water leaving radiance accounts for only 10% of the total radiance.
   Accurate retrieval of water leaving radiance depends on the atmospheric correction
Validation of the Ocean Color Satellite Sensors

   Effectiveness of the water leaving radiance retrieval needs to be
     accessed and validated.

   Special system for calibration and validation of the Ocean Color
     satellites should be established.

   Objective of this work is to assess the capability of validation using
     above water observations and evaluate the associated uncertainties
                          AERONET-Ocean Color
AERONET – Ocean Color:                     is a sub-network of the Aerosol Robotic Network
(AERONET), relying on modified sun-photometers to support ocean color validation activities
with highly consistent time-series of water leaving radiance and aerosol optical thickness

  •Autonomous radiometers operated on fixed platforms in coastal regions;
  •Identical measuring systems and protocols, calibrated using a single reference source and
  method, and processed with the same code;
  •Standardized products of normalized water-leaving radiance and aerosol optical thickness.

   G.Zibordi et al. A Network for Standardized Ocean Color Validation Measurements. Eos Transactions, 87: 293, 297, 2006.
    Long Island Sound Coastal
      Observatory (LISCO)
MODIS Top of Atmosphere True Color Composite Image of Long Island Sound
            LISCO Tower

                  Instrument Panel

                 Retractable Instrument Tower
12 meters

                          Solar panels
       SeaPRISM and HyperSAS instruments
              installed on the tower

          SeaPRISM Instrument                              HyperSAS Instrument
•Water Leaving Radiance                        •Water Leaving Radiance

•Direct Sun Irradiance and Sky Radiance        •Sky Radiance and Down Welling Irradiance

• at 413, 443, 490, 551, 668, 870 and 1018nm   • Hyper-Spectral 305 to 900 nm wavelength range.
         Validation Procedure
        Satellite Data                            In-Situ Data
MODIS     SeaWIFS        MERIS                    SeaPRISM

 Cloud Free Level 2 Images        ±40 minutes of Satellite Over Pass Time

           Normalized Water Leaving Radiance (nLw)
               412, 443, 488, 547 and 667nm

             •Time Series Match Up and Comparison
            •Relative and Absolute Percent Differences
           •Correlation of the data at each wavelengths
          Water Leaving Radiance Processing Procedure:
                   Removal of Sky Reflection
o Totalradiance, LT , measured by water
viewing sensor is the sum of water leaving
radiance, Lw , the reflected component of the                            θ
sky radiance, Li and sun glint.
o Sky reflection is proportional to Li with
reflectance factor, ρ.                                 LT = Lw+ρLi     π-θ

o For a flat water surface ρ is just a constant   Li
Fresnel reflectance factor.
o Sun glint can be also minimized by arranging
the relative azimuth between the sensor and

o   Lw(λ) = LT (λ) - ρLi (λ)
            Water Leaving Radiance Processing Procedure:
                     Removal of Sky Reflection
o However, sea surface usually is wavy.

o ρ is a function of wind speed obtained through                    Li
simulations assuming Gausian Wave Slope

o Glint components, L▼ becomes significant.                                 θ

                                                    LT = Lw+ρ(W)Li + L▼   π-θ


    Simulation for the variability of sky
radiance direction with different wind speed
              (Mobley, 1999)
Bidirectional Reflectance Distribution Function (BRDF)
                                        R0      f ( , a ,W , IOP)  f ( , 0 , a ,W , IOP) 
  BRDF( , 0 , ,  , a ,W , IOP)           0                    Q( , , ,  , ,W , IOP) 
                                                                                               
                                      R( ,W ) Q0 ( , a ,W , IOP)        0         a          

•Radiance emerging from the sea, in general, is not isotropic, it also depends on
the illumination and viewing conditions

•Viewing geometry dependency must be eliminated.

•Measurements are made at different times, so solar positions are not the same.

•Generalized process to transform the Lw measurements to the hypothetical
viewing geometry and solar position is called BRDF correction
Comparison of HyperSAS and SeaPRISM

  Scatter plot of the comparison between HYPERSAS
  and SeaPRISM datasets from October 2009 up to April 2010.
 Time Series Normalized
      Water Leaving
Radiance(nLw) Matchups
of SeaPRISM with satellite
Comparison of SeaPRISM and Satellite Data
•   Comparison between nLw data of SesPRISM and HyperSAS shows excellent

•   Co-located instruments give us the quality assurance data to compare with the
    satellite remote sensing data.

•   Comparison with the satellite data show excellent correlation at 488, 551 and 668 nm.

•   Initial assessments show relatively low Absolute Percent Difference through out the

•   Initial results proved the appropriateness of the LISCO site to achieve
    calibration/validation of the ocean color satellites in coastal water area as a key
    element of the AERONET-OC network
• This study was supported and monitored
  by National Oceanic and Atmospheric
  Administration (NOAA) under Grant -
  CREST Grant # NA06OAR4810162.
• The statements contained within the
  manuscript/research article are not the
  opinions of the funding agency or the U.S.
  government, but reflect the author’s

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