1. Jian Wang, Ph.D IMCS Rutgers University
Overview of Ocean Color: Theoretical background, sensors and application
Jian Wang, Ph.D
IMCS
Rutgers University

2. Introduction
Theoretical Background
Sensors and Platforms
Applications
Summary

3. Definition Ocean Color:
Refers to the characteristic hue of the ocean according to the presence and concentration of specific minerals or substances, such as chlorophyll.

4. Scope
Ocean color covers passive optical remote sensors (sun=light source)
Focus on digital image sensors, especially airborne/satellite radiometers

5. Theoretical Background
Radiative transfer theory
Atmospheric correction
IOPs and AOPs
Chlorophyll retrieval

6. Aerosols and molecules
Photon paths to sensor
SUN
SENSOR
Aerosols and molecules
Interface (with foam)
Water, phyto., NAP, CDOM
Single and double scattering (air/int./water) photon paths
Only photons from via water (1-35%: Sturm, 1981) are useful, the rest is noise

7. Atmospheric Correction
Solar radiation absorbed or scattered by the atmosphere before it reaches a sensor.
The ground surface receive not only the direct solar radiation but also sky light, or scattered radiation from the atmosphere.
A sensor will receive not only the direct reflected or emitted radiation from a target, but also the scattered radiation from a target and the scattered radiation from the atmosphere, which is called path radiance

8. Atmospheric Correction
The method using the radiative transfer equation
The method with ground truth data
Other method:
A special sensor to measure aerosol density or water vapor density

9. Remote sensing reflectance: AOP
f: empirical factor
Q: ratio of upwelling irradiance to radiance
t: transmittance of the air-sea interface
n: refraction index of seawater

10. Inherent optical properties (IOPs) Independent of light field
c = a + b
at = aw + ap + as
ap= aa + an
t: total
w: water
p: particulate
s: soluble
a: phytoplankton
n: nonpigmented particles

12. Backscattering

13. Chlorophyll Retrieval
To go back from the light detected at the sensor to deduce marine phytoplankton (e.g. represented by CHL)
Remove/correct for atmospheric and air-sea interface effects (atmospheric correction)
Deduce CHL from water-leaving reflectance spectrum (CHL retrieval)

14. Current SeaWiFS Chl algorithm:OC4V4 logChl=a+bR+cR2+dR3+eR4
R=log(Rrs443>490>510/Rrs555)

15. Current satellite sensors
SeaWiFS MODIS-T MODIS-A
Agency OSC/NASA NASA NASA
Launch
Sp.Res.(m)
Swath(km)
VIS/NIR/ 6/2/0 11/5/20 11/5/20
other bands
Tilt(less glint) Yes No No

16. Websites
SeaWiFS
MODIS

17. SeaWiFS data product
Level 1A: at-spacecraft raw radiance counts with calibration and navigation information available separately in the data file
Level 2: five normalized water-leaving radiance, and seven geophysical parameters derived from the radiance data.
Level 3: geophysical parameters binned to a 9x9 km (81 km2) global, equal-area grid at daily, 8-day, monthly, and annual intervals

18. Ocean color applications
Carbon cycle and climate change
Linking ocean ecosystem and the physical parameters
Coastal zone protection and marine resources management

19. Surface distribution of chlorophyll a using SeaWiFS data sets:
Note physical forcing effects: Coastal, Equator, North Atlantic
SeaWiFS Team/GSFC/NASA

21. New Jersey Coastal Upwelling
Temperature oC
July 6, ’98 - AVHRR
Field
Station
LEO
40N
74W
75W
39N
Field
Station
Chlor-a (mg/m3)
July 11, ‘98 - SeaWiFS
LEO
Historical
Hypoxia/Anoxia
Barnegat
Cape May

23. Note spatial scales of variability
Wind driven coastal upwelling
Note spatial scales of variability
CZCS
Images
Island-Induced
Upwelling
Coastal
Upwelling
Off Africa
Coastal
Upwelling
Off Peru SH NH
Wind
CZCS Team/GSFC/NASA

24. Summary Retrieve CHL from signal detected by sensors
- Atmospheric correction
- IOPs based algorithms
Broad applications