where the SST is restored to a prescribed temperature T* with a coupling strength , both of which
depend on atmospheric parameters. The coupling
strength mainly reflects the temperature dependence of latent heat flux, and would take typical
local values around 50 W m
92 K
91
. A consequence
of such a value is that the model’s sea surface temperature cannot be very different from the specified temperature T*. As was noted by Bretherton
(1982), the coupling with the atmosphere must
become weaker with increasing spatial scales. At
small scales, the atmospheric response to SST
anomalies can effectively be removed by horizontal transports, and hence a large flux can persist.
At the global scale, the only process that can
remove heat from the atmosphere is long-wave
radiation, which corresponds to a much weaker
coupling of 2–3 W m
92 K
91
.
As the strength of this ocean–atmosphere
coupling is crucial for the stability of the thermohaline circulation, this issue is important for ocean
climate studies. The most simple and frequent
recourse is to use an intermediate value of that
is representative of the scale of interest. Alternatively, the scale dependence of the coupling can
explicitly be included, based on approximations of
the atmospheric heat budget (Rahmstorf and
Willebrand, 1995). Similar approximations can be
made for the atmospheric water transport (Rahmstorf et al., 1996). Energy balance models (e.g.
Lohmann et al., 1995) constitute a further step in
this hierarchy, permitting a somewhat more accurate
description of the thermodynamic processes and of
the mean horizontal transports in the atmosphere.
Formulations such as those mentioned above
describe a dynamically somewhat passive atmosphere that reacts only by transporting anomalies in
the heat and freshwater budgets. While locally the
atmospheric momentum budget is indeed independent of SST, atmospheric circulation patterns on
larger scales may well be influenced by SST. This
is particularly the case for coupled oscillation
modes of the ocean–atmosphere system. Recently,
some attempts have been made to formulate the
dynamical atmospheric response to changes in SST
and also to the thermocline depth, in order to simulate El Niño (Eckert and Latif, 1997) or decadal
variability modes in the North Pacific (Münnich
et al., 1998). The extent to which such formulations can be used to investigate climate variability
has not yet been established.
7.2.4.3 Other coupled components
Coupled modelling of (e.g.) global biogeochemical
cycles further enhances the central importance of
spatial representation for two reasons. First, the
natural scales of variability for biogeochemical
interactions are often much finer than those characterizing the physical system itself; this necessitates finer resolution of these coupled fields
for comparable levels of accuracy. Second, the
regional distributions of biogeochemical interactions are highly heterogeneous and often highly
localized spatially – e.g. on the narrow continental
shelves of the worlds oceans.
In recent years, the increasing need for multidisciplinary research tools has led to the adaptation of
ocean circulation models for use in coupled physical–biogeochemical studies and in other multicomponent configurations. Several mutually related
areas of coupled modelling are currently being
actively developed within the scientific community,
including coupled modelling systems for the global
climate system (atmosphere, sea ice, ocean, land);
and the coupling of physical with biological, chemical and/or geological models to study certain
aspects of environmental cycles and dynamics – e.g.
the carbon cycle, plankton dynamics, and sediment
transport. While certain classes of problems (e.g.
coupled climate modelling) have a short history
and vigorous model development and comparison
continues, other classes of problems are relatively
unexplored. Trenberth (1992) and Hofmann and
Lascara (1998) offer recent overviews.
These coupled model studies will place more
demands on the physical completeness, numerical
integrity, and sub-grid-scale parameterizations of
ocean models. Generalized coupling strategies,
sophisticated parameterization schemes, and further attention to parallel computer performance
are all necessary ingredients for future progress in
these interdisciplinary areas. Finally, given the relative dearth of observational data (in particular,
for the bio–geochemical variables), advanced
forms of model/data fusion (data assimilation; see
Malanotte-Rizzoli, 1996) are essential for the
regional-to-global-scale simulation systems envisioned for the future.
7.2.5 Organization of model development
Numerical ocean models are highly specialized
tools that have the form of a computer program
SECTION 7 INSIGHTS FOR THE FUTURE
554
depend on atmospheric parameters. The coupling
strength mainly reflects the temperature dependence of latent heat flux, and would take typical
local values around 50 W m
92 K
91
. A consequence
of such a value is that the model’s sea surface temperature cannot be very different from the specified temperature T*. As was noted by Bretherton
(1982), the coupling with the atmosphere must
become weaker with increasing spatial scales. At
small scales, the atmospheric response to SST
anomalies can effectively be removed by horizontal transports, and hence a large flux can persist.
At the global scale, the only process that can
remove heat from the atmosphere is long-wave
radiation, which corresponds to a much weaker
coupling of 2–3 W m
92 K
91
.
As the strength of this ocean–atmosphere
coupling is crucial for the stability of the thermohaline circulation, this issue is important for ocean
climate studies. The most simple and frequent
recourse is to use an intermediate value of that
is representative of the scale of interest. Alternatively, the scale dependence of the coupling can
explicitly be included, based on approximations of
the atmospheric heat budget (Rahmstorf and
Willebrand, 1995). Similar approximations can be
made for the atmospheric water transport (Rahmstorf et al., 1996). Energy balance models (e.g.
Lohmann et al., 1995) constitute a further step in
this hierarchy, permitting a somewhat more accurate
description of the thermodynamic processes and of
the mean horizontal transports in the atmosphere.
Formulations such as those mentioned above
describe a dynamically somewhat passive atmosphere that reacts only by transporting anomalies in
the heat and freshwater budgets. While locally the
atmospheric momentum budget is indeed independent of SST, atmospheric circulation patterns on
larger scales may well be influenced by SST. This
is particularly the case for coupled oscillation
modes of the ocean–atmosphere system. Recently,
some attempts have been made to formulate the
dynamical atmospheric response to changes in SST
and also to the thermocline depth, in order to simulate El Niño (Eckert and Latif, 1997) or decadal
variability modes in the North Pacific (Münnich
et al., 1998). The extent to which such formulations can be used to investigate climate variability
has not yet been established.
7.2.4.3 Other coupled components
Coupled modelling of (e.g.) global biogeochemical
cycles further enhances the central importance of
spatial representation for two reasons. First, the
natural scales of variability for biogeochemical
interactions are often much finer than those characterizing the physical system itself; this necessitates finer resolution of these coupled fields
for comparable levels of accuracy. Second, the
regional distributions of biogeochemical interactions are highly heterogeneous and often highly
localized spatially – e.g. on the narrow continental
shelves of the worlds oceans.
In recent years, the increasing need for multidisciplinary research tools has led to the adaptation of
ocean circulation models for use in coupled physical–biogeochemical studies and in other multicomponent configurations. Several mutually related
areas of coupled modelling are currently being
actively developed within the scientific community,
including coupled modelling systems for the global
climate system (atmosphere, sea ice, ocean, land);
and the coupling of physical with biological, chemical and/or geological models to study certain
aspects of environmental cycles and dynamics – e.g.
the carbon cycle, plankton dynamics, and sediment
transport. While certain classes of problems (e.g.
coupled climate modelling) have a short history
and vigorous model development and comparison
continues, other classes of problems are relatively
unexplored. Trenberth (1992) and Hofmann and
Lascara (1998) offer recent overviews.
These coupled model studies will place more
demands on the physical completeness, numerical
integrity, and sub-grid-scale parameterizations of
ocean models. Generalized coupling strategies,
sophisticated parameterization schemes, and further attention to parallel computer performance
are all necessary ingredients for future progress in
these interdisciplinary areas. Finally, given the relative dearth of observational data (in particular,
for the bio–geochemical variables), advanced
forms of model/data fusion (data assimilation; see
Malanotte-Rizzoli, 1996) are essential for the
regional-to-global-scale simulation systems envisioned for the future.
7.2.5 Organization of model development
Numerical ocean models are highly specialized
tools that have the form of a computer program
SECTION 7 INSIGHTS FOR THE FUTURE
554