Transcript Slide 1

Ocean Color Observations and Their
Applications to Climate Studies
Alex Gilerson, Soe Hlaing, Ioannis Ioannou,
Sam Ahmed
Optical Remote Sensing Laboratory,
The City College of the City University of New York,
NOAA CREST
CREST Symposium, June 5, 2013
Melin, 2013
Water Composition for the Open Ocean
and Coastal Waters
In the open ocean
algae are the main
component
In coastal waters
algae are mixed with
CDOM and minerals
Algae CDOM* Minerals
*CDOM is the colored dissolved organic matter mostly of terrestrial origin
Reflectance of Various Surfaces
Signal from water is small in comparison with reflectance from other
surfaces and atmosphere
Total Radiance Signal at the Top of
Atmosphere
Lp
Ls
Lw
Lw -Total water-leaving radiance. Ls - Radiance above the sea surface due to
all surface reflection effects within the IFOV. Lp - Atmospheric path radiance.
Signal from the atmospheric scattering is about 10 times stronger than from water.
Atmospheric correction utilizes NIR bands (748, 865 nm)
Outline
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Introduction
System requirements
Vicarious calibration
Chl time series
Our applications to climate studies
Main Requirements for Sensors and
Observations
(IOCCG report 13)
• Easy intercomparison between sensors, and radiometric
intercalibration in well-defined conditions;
• A full compatibility of operational algorithms for atmospheric
correction and derivation of end products;
• A meaningful data merging, at the level of geophysical products
(pigment index, aerosol optical thickness) or at the level of the
initial quantities (e.g. spectral normalized radiances);
• A long-term continuity of ocean-colour observations, based on
stable, entirely comparable, parameters; and therefore
• The building up of a coherent data base for global
biogeochemical studies and related modelling activities
Main Requirements for Climatic Data Records
To gain insight into climate variability and change the
requirement is continuous time series of observations to
estimate ocean properties such as phytoplankton chlorophyll-a
with the radiometric accuracy of current sensors or better
(IOCCG report 13)
Length: relevant for climate time scales (referred to as “longterm”) need for multiple decades of data (>~50 years) - Melin,
2013
Two levels of products
- Water leaving radiance / Remote sensing reflectance (Rrs) –
highly accurate measurements by well calibrated sensors and
consistency through various missions
- Chlorophyll-a concentration (Chla) – main ocean color product
– continuous time series
Remote Sensing of the Ocean
RS of water areas provides an efficient way of monitoring
water quality, biomass in the ocean, sediment plumes,
spatial and temporal scales of the water structures, sea
surface temperature, etc.
Phytoplankton are very
important part of ocean life:
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Phytoplankton are the first link in the food chain.
Phytoplankton convert nutrients into plant
material by using sunlight through
photosynthesis and convert carbon dioxide from
sea water into organic carbon and oxygen as a
by-product and thus affect carbon balance.
Amount of phytoplankton in the
ocean can be traced by the
concentration of the optically
active pigment chlorophyll [Chl]
Reflectance spectra for the
open ocean
0.04
[Chl]=0.2 mg/m3
[Chl]=1.0 mg/m3
Reflectance
0.03
[Chl]=10 mg/m3
0.02
0.01
0.00
400
500
600
700
800
Wavelength, nm
[Chl] can be well characterized
by blue-green ratio
With increasing [Chl] water
changes its color from blue to
green
SeaWiFS Blue-Green
Ratio Algorithm
Carder, et al. ,2003
Chlorophyll Global and Regional Maps
SeaWiFS, July 2006
MODIS, NE and Florida
coasts
Ocean Color Satellite Sensors
NASA Coastal Zone Color Scanner (CZCS) – 1978 - 1986
Seaviewing Wide Field-of-view Sensor(SeaWiFS) – 1997 - 2011
NASA Moderate Resolution Imaging Spectroradiometer
(MODIS) on Terra satellite
-1999-present
NASA Moderate Resolution Imaging Spectroradiometer
(MODIS) on Aqua satellite
-2002-present
MEdium Resolution Imaging Spectrometer (MERIS),
European Space Agency (ESA) on ENVISAT satellite – 20022012
Suomi National Polar-orbiting Partnership - Visible Infrared
Imaging Radiometer Suite (VIIRS) NOAA- NASA -2011-present
MODIS Spectral Bands for Ocean Color and
Atmospheric Correction (Terra,1999; Aqua, 2002)
Vicarious calibration
System Vicarious Calibration (e.g., calibration relying on the use of
highly accurate in situ measurements of Lw and the application of the RT
code embedded in the atmospheric correction scheme, thus leading to
the calibration of the entire system, i.e., the sensor plus the algorithms
(Gordon 1998)) specifically applied to perform (absolute) radiometric
calibrations. Expected top-of-atmosphere calibration uncertainties are
0.3-0.5%, leading to uncertainties of 3-5% in Lw.
This suggests that in situ data sources for vicarious calibration of satellite
ocean color sensors need to be carefully evaluated accounting for the
actual application of satellite data products recognizing that the creation
of CDRs imposes the most stringent conditions.
Early indications on the appropriateness of in situ data/sites included
(Gordon 1998): 1. Cloud free, very clear, maritime atmosphere (τa<0.1 in
the visible); 2. Horizontally uniform Lw over spatial scales of a few kms;
3. Oligotrophic-mesotrophic waters (to minimize in situ measurement
errors of Lw in the blue); 4. Coincident aerosol measurements.
Zibordi, 2013
MOBY – Marine Optical Buoy
McClain, 2013
McClain, 2013
McClain, 2013
Regional trends
Decomposition of the signal into
seasonal, trend and irregular terms
Melin, 2010, 2013
Alternative Ocean Color Algorithms - NN
[Chl] Algorithms
1) OC3
2) Rrs NN (NN [Chl])
3) IOP+Rrs NN (IOP NN [Chl])
NN [Chl] and IOP NN [Chl] are trained based on the NOMAD
Ioannou et al, 2011, 2013
Alternative Ocean Color Algorithms - NN
Sample Seasonal [Chl], Spring 2003
Algorithm Implementation on Satellite Data- OC3-[Chl], mg m-3
Alternative Ocean Color Algorithms - NN
Sample Seasonal [Chl], Spring 2003
Algorithm Implementation on Satellite Data- NN-[Chl], mg m-3
Alternative Ocean Color Algorithms - NN
Global Distributions of [Chl], as derived from the
three algorithms for Spring 2003
Alternative Ocean Color Algorithms - NN
[Chl]mg/m3
Global seasonal variation of [Chl]mg/m3
Polarization measurements with the
hyperspectral multi-angular polarimeter + full
Stokes vector imaging camera
Addition of polarization sensitive channels to the
future satellite instruments
Polarization sensitive instruments are used to
measure aerosols. We show that they are useful
in the retrieval of additional water parameters:
attenuation coefficient, particle characteristics
Polarization
channels
3.5
665
440
[Chl] = 22.5 mg/m
2.5
680
-1
Lw, W m sr um
-1
3.0
-2
2.0
1.5
3
710
750
1.0
0.5
[Chl] = 5.9 mg/m
3
0.0
400
450
500
550
600
650
Wavelength, nm
700
750
800
865
In collaboration with NASA-GISS and Raytheon
we are working on a potential new sensor with
polarization sensitivity, 3 observational angles
for retrieval of aerosols and water parameters
Japan will launch an instrument with 665 and
865nm polarization channels, 3 viewing
angles, 250m resolution in 2016
Algal Blooms - Progression of K. Brevis
bloom using MODIS data and our algorithm
GloboLakes Project
Tyler, 2012
GloboLakes Project
Tyler, 2012
Conclusions
• Climate Ocean Color observations are challenging but possible
for observation of global and regional trends
• Require:
- highly precise sensors
- vicarious calibration;
- accurate atmospheric correction algorithms
- accurate and well established algorithms for ocean
operational products
- continuity between missions
This work is partially supported by grants from NOAA, NASA
and the Office of Naval Research