2.3.1 Why coupled models?
Numerical weather prediction is now a well-established process that provides us with information of
great practical value on a daily basis. But the limits
of deterministic predictability of the atmospheric
flow and weather are no more than a few days.
Ensemble integrations of atmospheric models are
now being used to try to extend this predictability,
at least in a statistical sense. However, to understand, or even forecast, processes with time scales
longer than a month or so we must incorporate
into prediction models components of the climate
system that adjust on these longer time scales. The
ocean provides such time scales, and coupled
ocean–atmosphere processes are likely to be
fundamental to climate variability and change on
all time scales from seasonal upwards. Coupled
ocean–atmosphere models have been developed to
address such issues.
Much of the early progress in coupled modelling
was motivated by the desire to understand, and
eventually forecast, the El Niño-Southern Oscillation phenomenon (ENSO), and great progress has
been made in this area under the Tropical Ocean
Global Atmosphere (TOGA) programme and its
successor, CLIVAR-GOALS (see Delecluse et al.,
1998, for a review). However, in this chapter we
focus on the decadal and longer time scales that are
the main interest of WOCE. Coupled modelling
work in this area has largely been motivated by the
need to project the effects on climate of man-made
emissions of greenhouse gases such as CO 2 , over
a time scale of 100–200 years, and one of the
primary goals of WOCE was ‘to develop ocean
models suitable for predicting climate change, and
to collect the data to test them’.
In this chapter we concentrate on global
General Circulation Models (GCMs), which are
the most comprehensive models used in modern
climate research. Four possible applications can
be identified:
1 estimation of the present climate state;
2 study of internal modes of variability of the
climate system (e.g. ENSO, North Atlantic
Oscillation);
3 forecasting or hindcasting such internal variability; and
4 longer-term, forced climate change (e.g. through
solar variability or anthropogenic forcing).
Work on 1 to date has largely been done with
models of individual subsystems (atmosphere or
ocean), and work on 3 is in its infancy. Coupled
models have been extensively used for 2 and 4.
Rather than attempt a comprehensive review of
this work, this chapter concentrates on the formulation and performance of modern coupled models, from an oceanographic perspective. References
into the coupled modelling literature are provided
to allow the reader to follow up particular topics
in more depth.
2.3.2 Formulation of coupled models
A model capable of simulating climate variations
on time scales of decades to centuries requires
several components. At the very least, the atmosphere, land surface, ocean and sea ice, and their
2.3
Coupled Ocean–Atmosphere Models
Richard A.Wood and Frank O. Bryan
79
OCEAN CIRCULATION AND CLIMATE
Copyright © 2001 Academic Press
ISBN 0-12-641351-7
All rights of reproduction in any form reserved
CHAPTER
Numerical weather prediction is now a well-established process that provides us with information of
great practical value on a daily basis. But the limits
of deterministic predictability of the atmospheric
flow and weather are no more than a few days.
Ensemble integrations of atmospheric models are
now being used to try to extend this predictability,
at least in a statistical sense. However, to understand, or even forecast, processes with time scales
longer than a month or so we must incorporate
into prediction models components of the climate
system that adjust on these longer time scales. The
ocean provides such time scales, and coupled
ocean–atmosphere processes are likely to be
fundamental to climate variability and change on
all time scales from seasonal upwards. Coupled
ocean–atmosphere models have been developed to
address such issues.
Much of the early progress in coupled modelling
was motivated by the desire to understand, and
eventually forecast, the El Niño-Southern Oscillation phenomenon (ENSO), and great progress has
been made in this area under the Tropical Ocean
Global Atmosphere (TOGA) programme and its
successor, CLIVAR-GOALS (see Delecluse et al.,
1998, for a review). However, in this chapter we
focus on the decadal and longer time scales that are
the main interest of WOCE. Coupled modelling
work in this area has largely been motivated by the
need to project the effects on climate of man-made
emissions of greenhouse gases such as CO 2 , over
a time scale of 100–200 years, and one of the
primary goals of WOCE was ‘to develop ocean
models suitable for predicting climate change, and
to collect the data to test them’.
In this chapter we concentrate on global
General Circulation Models (GCMs), which are
the most comprehensive models used in modern
climate research. Four possible applications can
be identified:
1 estimation of the present climate state;
2 study of internal modes of variability of the
climate system (e.g. ENSO, North Atlantic
Oscillation);
3 forecasting or hindcasting such internal variability; and
4 longer-term, forced climate change (e.g. through
solar variability or anthropogenic forcing).
Work on 1 to date has largely been done with
models of individual subsystems (atmosphere or
ocean), and work on 3 is in its infancy. Coupled
models have been extensively used for 2 and 4.
Rather than attempt a comprehensive review of
this work, this chapter concentrates on the formulation and performance of modern coupled models, from an oceanographic perspective. References
into the coupled modelling literature are provided
to allow the reader to follow up particular topics
in more depth.
2.3.2 Formulation of coupled models
A model capable of simulating climate variations
on time scales of decades to centuries requires
several components. At the very least, the atmosphere, land surface, ocean and sea ice, and their
2.3
Coupled Ocean–Atmosphere Models
Richard A.Wood and Frank O. Bryan
79
OCEAN CIRCULATION AND CLIMATE
Copyright © 2001 Academic Press
ISBN 0-12-641351-7
All rights of reproduction in any form reserved
CHAPTER