Optical remote sensing of waters with vertical structure

Area of Science:

• Oceanography
• Remote Sensing
• Phytoplankton Dynamics

Background:

• Ocean color remote sensing typically assumes a homogeneous upper ocean.
• Stable water column stratification in coastal areas and fjords significantly impacts phytoplankton blooms.
• Existing algorithms struggle to account for vertical variations in marine constituents.

Purpose of the Study:

• To develop and validate an optical remote-sensing algorithm capable of resolving vertical structures in oceanic waters.
• To determine chlorophyll-a concentrations in two distinct layers and the thickness of the upper layer.
• To improve the accuracy of marine constituent mapping in stratified water bodies.

Main Methods:

• An inverse-modeling technique using radiative-transfer computations for coupled atmosphere-ocean systems.
• Simultaneous retrieval of three parameters: chlorophyll-a in two layers and upper layer thickness.
• Minimization of differences between simulated and measured radiances using the simulated annealing optimization algorithm.

Main Results:

• The developed algorithm successfully retrieved vertical variations in chlorophyll-a concentration from synthetic data.
• The inverse-modeling approach demonstrated the feasibility of resolving two-layer oceanic structures.
• Results indicate potential for improved pigment concentration mapping in stratified waters.

Conclusions:

• The novel algorithm can resolve vertical structures in oceanic waters, providing insights into stratified environments.
• This advancement is crucial for understanding phytoplankton bloom dynamics in coastal and fjord regions.
• The method shows promise for application with satellite sensors like the Medium Resolution Imaging Spectrometer.