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Remote sensing of mesoscale oceanic processes by acoustics and satellite sensors - a new approach to understanding of bio-physical coupling

Tildelt: kr 3,5 mill.





2009 - 2012

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Mesoscale eddies are important for the ocean circulation and are considered important for the open sea productivity. The basic processes behind are difficult to study and are vaguely understood mainly due to inadequate spatio-temporal coverage offered by traditional methodologies. Recent studies have demonstrated that surface observation of eddies as recorded by satellites can be combined with full depth coverage with vessel acoustic sensors. In concert the two methods create a new powerful tool to study biophysical interaction in eddies. Sea surface altimetry or ocean colour data combined with acoustics records of biomass may uncover biophysical interactions within eddies, and help understanding their importance for marine bioproduction. An integral part of the methodology is application of physical-biological models to study the bio-physical interactions. The models will help understanding how different types of eddies influence the primary and secondary production including passive as well as active p articles (representing zooplankton) and particles with simple foraging strategies (representing small fish), thus giving insight to how eddies contribute to the distribution and production of biomass in the open ocean. The successful initial observation s combining satellite/vessel data are promising for detection and mapping of eddies along the Norwegian continental shelf and slope. This is a groundbreaking methodology that may enhance understanding of productivity in the open sea and might become vita l in studies of fish recruitment and harvestable production at lower trophic level. The approach allow observations at scales of meter and second of biomass interaction with the environment. Advanced biological sampling can be designed to collect marine l ife thus giving precise information about spatio-temporal distribution adequate for modeling of biophysical coupling far beyond traditional sampling approaches.

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