Prof. Dr. John Wilkin 

Successful weather forecasting depends, among other things, on the skillful merger of

observations with computer models of atmospheric physics. In coastal oceanography,

similar systems are emerging that combine data and models to enable predictions of

oceanic conditions in support of decision-making related to maritime safety, water quality,

ocean acidification, hypoxia, fisheries and the fate of pollutants and microplastics.

Ocean physical conditions such as sea level, temperate and currents are routinely observed

by satellites, radars and increasingly by novel platforms in the water such as profiling floats

and autonomous underwater vehicles. These data are incorporated into ocean forecast

models in much the same way as in weather prediction. But a voluminous data set that goes

largely unused in constraining coastal ocean forecasts are patterns in the ocean’s

ecosystem revealed by satellites that observe ocean color at numerous different

wavelengths of visible light.

Using established methods for calculating the apparent color of seawater due to the

absorption, scattering and reflection of visible light by plankton, organic matter and

sediments within the water column, this project will invert that relationship and use

satellite ocean color data to infer what those ecosystem characteristics must be, and what

underlying patterns of oceanic currents best explain the turbulent eddies and fronts that

are so readily apparent in ocean color imagery.