Chapter 15
THE FORECASTING OCEAN ASSIMILATION
MODEL (FOAM) SYSTEM
Michael J. Bell, Rosa Barciela, Adrian Hines, Matt Martin, Alistair Sellar,
and David Storkey
Met Office, Exeter, UK
Abstract:
We present a detailed technical description of the present FOAM system and
discuss some representative examples of the scientific investigations we
undertake to track-down problems within the system and to understand the
importance (“impact”) of the various inputs to it. We also provide an historical
perspective on the development of the system and the changing demands for it,
and describe the way in which we are adapting to meet these demands.
Keywords: Operational ocean forecasting, data assimilation, assessments.
1.
Introduction
The Forecasting Ocean Assimilation Model (FOAM) is a system for
assimilating oceanographic measurements into a coupled dynamical model
of the deep ocean and sea-ice. It is used on a routine daily basis to make
forecasts out to five days ahead representing/resolving the ocean’s
mesoscale structure in selected regions. The system has been developed with
funding from the Royal Navy and is used to support their operations. It also
provides boundary conditions for a shelf-seas forecasting system operated by
the Met Office. We aim to demonstrate in the near future that its analyses
and forecasts of ocean currents are sufficiently skilful to be useful for search
and rescue, oil spill drift prediction, and the deep-ocean oil and gas industry.
We are also exploring the application of the system to monitoring of open
ocean ecosystems and air-sea CO 2 fluxes and management of fisheries and
are likely to explore its application to short-range, coupled, atmosphereocean forecasts.
The second section of this chapter provides an overview of the FOAM
system and a technical summary of its inputs, dynamical model and
assimilation methods as they stood in the operational suite in August 2004.
The third section attempts to give some insight into the intellectual
397
E. P. Chassignet and J. Verron (eds.), Ocean Weather Forecasting, 397-411.
© 2006 Springer. Printed in the Netherlands.
THE FORECASTING OCEAN ASSIMILATION
MODEL (FOAM) SYSTEM
Michael J. Bell, Rosa Barciela, Adrian Hines, Matt Martin, Alistair Sellar,
and David Storkey
Met Office, Exeter, UK
Abstract:
We present a detailed technical description of the present FOAM system and
discuss some representative examples of the scientific investigations we
undertake to track-down problems within the system and to understand the
importance (“impact”) of the various inputs to it. We also provide an historical
perspective on the development of the system and the changing demands for it,
and describe the way in which we are adapting to meet these demands.
Keywords: Operational ocean forecasting, data assimilation, assessments.
1.
Introduction
The Forecasting Ocean Assimilation Model (FOAM) is a system for
assimilating oceanographic measurements into a coupled dynamical model
of the deep ocean and sea-ice. It is used on a routine daily basis to make
forecasts out to five days ahead representing/resolving the ocean’s
mesoscale structure in selected regions. The system has been developed with
funding from the Royal Navy and is used to support their operations. It also
provides boundary conditions for a shelf-seas forecasting system operated by
the Met Office. We aim to demonstrate in the near future that its analyses
and forecasts of ocean currents are sufficiently skilful to be useful for search
and rescue, oil spill drift prediction, and the deep-ocean oil and gas industry.
We are also exploring the application of the system to monitoring of open
ocean ecosystems and air-sea CO 2 fluxes and management of fisheries and
are likely to explore its application to short-range, coupled, atmosphereocean forecasts.
The second section of this chapter provides an overview of the FOAM
system and a technical summary of its inputs, dynamical model and
assimilation methods as they stood in the operational suite in August 2004.
The third section attempts to give some insight into the intellectual
397
E. P. Chassignet and J. Verron (eds.), Ocean Weather Forecasting, 397-411.
© 2006 Springer. Printed in the Netherlands.