Ocean Color Radiometer Measurements of Long Island Sound Coastal Observational platform (LISCO):

Comparisons with Satellite Data & Assessments of Uncertainties

Presenter: Soe Min HlaingMentor/ 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

Specific Absorption Spectrum of [Chl]

Remote Sensing of the Ocean Color

Absorption Spectrum of Water

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

spectrum.

Chlorophyll absorb strongly in the blue and violet/ ultra violet regions of the

spectrum

Remote Sensing Reflectance Spectra of Ocean Water with Different Level of [Chl]

400 500 600 700 800

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[Chl]=10 mg/m3

[Chl]=1.0 mg/m3

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Wavelength, nm

[Chl]=0.2 mg/m3

Chlorophyll Concentration [Chl] as function of Blue – Green Ratio

Reflectance spectra of the open ocean

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

Solar Flux

Diffuse Sky Light

Wavy Sea Surface

Water Leaving Radiances

Surface Reflection

Atmospheric Radiances Sensor

Contribution of atmospheric radiance to the total signal

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

process.

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: 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 measurements.

G.Zibordi et al. A Network for Standardized Ocean Color Validation Measurements. Eos Transactions, 87: 293, 297, 2006.

AERONET-Ocean Color

•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.

Rationale:

Long Island Sound Coastal Observatory (LISCO)

MODIS Top of Atmosphere True Color Composite Image of Long Island Sound

12 m

eter

s

Retractable Instrument Tower

Instrument Panel

LISCO Tower

Solar panelsSolar panels

SeaPRISM and HyperSAS instruments installed on the tower

SeaPRISM Instrument•Water Leaving Radiance

•Direct Sun Irradiance and Sky Radiance

• at 413, 443, 490, 551, 668, 870 and 1018nm Wavelengths

HyperSAS Instrument•Water Leaving Radiance

•Sky Radiance and Down Welling Irradiance

• Hyper-Spectral 305 to 900 nm wavelength range.

In-Situ Data

Validation ProcedureSatellite Data

Cloud Free Level 2 Images

MODIS SeaWIFS MERIS

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

SeaPRISM

±40 minutes of Satellite Over Pass Time

•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 Total radiance, LT , measured by water viewing sensor is the sum of water leaving radiance, Lw , the reflected component of the sky radiance, Li and sun glint.

o Sky reflection is proportional to Li with reflectance factor, ρ.

o For a flat water surface ρ is just a constant Fresnel reflectance factor.

o Sun glint can be also minimized by arranging the relative azimuth between the sensor and sun.

o Lw(λ) = LT (λ) - ρLi (λ)

Li

θ

π-θLT = Lw+ρLi

Lw

Li

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 simulations assuming Gausian Wave Slope

o Glint components, L▼ becomes significant.

Li

θ

π-θLT = Lw+ρ(W)Li + L▼

Li

Simulation for the variability of sky radiance direction with different wind speed

(Mobley, 1999)

Bidirectional Reflectance Distribution Function (BRDF)

•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

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Comparison of HyperSAS and SeaPRISM measurements

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

data

Comparison of SeaPRISM and Satellite Data

Conclusions• Comparison between nLw data of SesPRISM and HyperSAS shows excellent

consistency.

• 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 spectrum.

• 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

Acknowledgement

• 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 opinions.

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