LIFECO: Remote Sensing of Frontal Regimes

This work package is part of the LIFECO programme: LInking
Hydrographic Frontal activity to ECOsystem dynamics in the
North sea and Skagerrak - Importance to Fish Stock recruitment

The remote sensing component of the programme is designed
to, in conjunction with in situ validation data from the field
and the modelling work packages (WP 1,2 & 4: Advancement of
Hydrodynamic models, Coupled bio-physical modelling and
Distribution and abundance of plankton and fish relative
frontal processes): resolve the water mass distributions
specific to different assemblages of phytoplankton,
zooplankton and fish, supply synoptic, high spatial resolution
data suitable for validating the coupled physical-biochemical
numerical model of frontal conditions and application in
GIS (WP 1, 2 & 8 - Advancement of Hydrodynamic models,
Coupled bio-physical modelling, GIS and Spatial Data Analysis)
and assist in the planning and implementation of field programs
(WP4 - 6: Distribution and abundance of plankton and fish
relative frontal processes, Effects of frontal processes in
the plankton, Predatory interaction between fish species and
top-down control of zooplankton relative to frontal processes).

With the availability of sea surface temperature, ocean
colour,radar altimetry and synthetic aperture radar (SAR)
from a variety of sensors and platforms, it will be essential
to combine the various sources of information to produce the
best possible description of surface frontal features. This
combination of multiple-sensor, multiple-resolution data is
generally referred to as data fusion. It is planned to use
data fusion approaches to combine the multi-spectral,
multiple-resolution data to extract frontal feature
information.

One of the most important products to be delivered by the
remote sensing component of this project is the chlorophyll-a
concentration estimated from satellite ocean colour, since
chlorophyll-a is indicative of phytoplankton biomass in the
water column. However, it is well-known that obtaining
reliable chlorophyll estimates from ocean colour can be
problematic in coastal (Case 2) waters due to the effects of
dissolved organic material and turbidity from suspended
sediment. To minimise the error, the most up to date ocean
optics algorithms developed for chlorophyll estimation in
Danish waters will be used from the Danish Nationally funded
DECO program (Danish Institute of Fisheries Research
(Partner 1) is a participant in this program).

Within this work package it is planned to combine the
various sources of satellite data (data fusion) and relate
these data products to in situ data (WP4) and model results
(WP1 & 2). The goal is to extract the maximum possible
information on frontal physical and biochemical properties
from available satellite observations and to supply this
information as input to the GIS (WP8) and Synthesis tasks
(WP9).