Extending the use and interpretation of ocean satellite data using Lagrangian modelling

Abstract

We propose a new methodology for synthesizing satellite or in situ observations with ocean circulation velocity fields from an operational model. This is done by attaching values taken from the satellite observations to virtual particles seeded at the surface in the domain of a circulation model and advecting them in a Lagrangian fashion. It is then possible to track the fate and change in composition of individual water parcels between two satellite images, and hence estimate the change in satellite‐derived properties along the trajectories of water parcels. The power of the method lies in deciphering the change in sea surface properties from satellite data in the Lagrangian (advective) frame. We use this to estimate rates of biological processes. Further, we generate a dynamically correct time‐interpolation of satellite fields by considering the temporal change in water properties as occurring along trajectories of moving water parcels, rather than in a static medium. We use the methodology to interpret and interpolate MODIS satellite fields in the Gulf of Maine, which has notoriously intermittent satellite coverage. The dynamic interpretation is made possible for this region by the availability of time‐specific velocity fields from an operational coastal circulation model.