ocean models), and developments to sub-grid-scale
parameterizations, in both atmosphere and ocean.
For the ocean, sill overflows and their mixing in
bottom boundary layers, mesoscale eddy fluxes
and the spatially inhomogeneous nature of diapycnal mixing are areas where developments are likely
(through improved resolution, parameterization
or both). Many of these issues were discussed at
the WOCE/CLIVAR workshop on ocean climate
modelling held in Boulder in August 1998, and the
report of that workshop (WOCE International
Project Office, 1999) summarizes the state of the
art and research directions envisaged at that time.
Biogeochemical cycles, especially the carbon and
sulfur cycles, will probably be incorporated into
climate models over the next few years. While
there is clearly much still to be done, the ocean
components of climate models are reaching a state
of maturity where serious comparison with observations is now possible, and model projections of
climate variability and change can be used to help
in the design of the ocean observing and monitoring systems of the future.
Acknowledgements
We thank Claire Cooper, Scott Doney, Jonathan
Gregory and James Penman for help in producing
the figures, and Matthew Collins, Peter Cox, Chris
Gordon, Jonathan Gregory, Chris Hewitt, Colin
Johnson and Catherine Senior for valuable discussions. RAW is supported by the UK Department of
the Environment, Transport and the Regions. FOB
is supported by the US National Science Foundation, through its sponsorship of NCAR.
Appendix: Acronyms for models and
institutions
The following model names and other acronyms are
used within this chapter. Note that this is not a full
list of coupled models in use at the time of writing.
The interested reader is referred to the CMIP project (see below), and to the assessment reports of the
Intergovernmental Panel on Climate Change, e.g.
IPCC, 1995, for more complete listings.
CSM
Climate Sytem Model (coupled)
(NCAR; Boville and Gent, 1998)
CMIP
Coupled Model Intercomparison
Project. A systematic intercomparison
of a number of coupled models,
co-ordinated by the Program for
Climate Model Diagnosis and
Intercomparison, Lawrence
Livermore National Laboratory,
Livermore, California, USA. CMIP1
includes model ‘control’ runs only,
CMIP2 also includes model response
to an idealized scenario of
atmospheric carbon dioxide increase
(see http://www. pcmdi.llnl.gov)
DKRZ
Deutsche Klimarechnungszentrum,
Hamburg, Germany
GFDL
Geophysical Fluid Dynamics
Laboratory, Princeton, New Jersey,
USA
HadCM2/3 Coupled models of the Hadley
Centre for Climate Prediction and
Research, Meteorological Office,
Bracknell, UK
HOPE
Hamburg Ocean Primitive Equation
Model (DKRZ; Wolff et al., 1997)
LODYC
Laboratoire d’Oceanologie Dynamique et de Climatologie, Paris,
France
LSG
Large-Scale Geostrophic model
(MPI/DKRZ; Maier Reimer
et al., 1993)
MOM
Modular Ocean Model (GFDL),
developed originally from the model
of Bryan (1969)
MPI
Max Planck Institut für
Meteorologie, Hamburg, Germany
NCAR
National Center for Atmospheric
Research, Boulder, Colorado, USA
OPA
Ocean model of LODYC (Madec
et al., 1998)
OPA/
OPA coupled to the atmospheric
ARPEGE
model of Meteo France/European
Centre for Medium Range Weather
Forecasts (Madec and Delecluse,
1997)
OPA/LMD OPA coupled to the atmospheric
model of the Laboratoire de
Meteorologie Dynamique (Madec
and Delecluse, 1997)
OPYC
Ocean isopycnic model (MPI;
Oberhuber, 1993)
SECTION 2 OBSERVATIONS AND MODELS
96
parameterizations, in both atmosphere and ocean.
For the ocean, sill overflows and their mixing in
bottom boundary layers, mesoscale eddy fluxes
and the spatially inhomogeneous nature of diapycnal mixing are areas where developments are likely
(through improved resolution, parameterization
or both). Many of these issues were discussed at
the WOCE/CLIVAR workshop on ocean climate
modelling held in Boulder in August 1998, and the
report of that workshop (WOCE International
Project Office, 1999) summarizes the state of the
art and research directions envisaged at that time.
Biogeochemical cycles, especially the carbon and
sulfur cycles, will probably be incorporated into
climate models over the next few years. While
there is clearly much still to be done, the ocean
components of climate models are reaching a state
of maturity where serious comparison with observations is now possible, and model projections of
climate variability and change can be used to help
in the design of the ocean observing and monitoring systems of the future.
Acknowledgements
We thank Claire Cooper, Scott Doney, Jonathan
Gregory and James Penman for help in producing
the figures, and Matthew Collins, Peter Cox, Chris
Gordon, Jonathan Gregory, Chris Hewitt, Colin
Johnson and Catherine Senior for valuable discussions. RAW is supported by the UK Department of
the Environment, Transport and the Regions. FOB
is supported by the US National Science Foundation, through its sponsorship of NCAR.
Appendix: Acronyms for models and
institutions
The following model names and other acronyms are
used within this chapter. Note that this is not a full
list of coupled models in use at the time of writing.
The interested reader is referred to the CMIP project (see below), and to the assessment reports of the
Intergovernmental Panel on Climate Change, e.g.
IPCC, 1995, for more complete listings.
CSM
Climate Sytem Model (coupled)
(NCAR; Boville and Gent, 1998)
CMIP
Coupled Model Intercomparison
Project. A systematic intercomparison
of a number of coupled models,
co-ordinated by the Program for
Climate Model Diagnosis and
Intercomparison, Lawrence
Livermore National Laboratory,
Livermore, California, USA. CMIP1
includes model ‘control’ runs only,
CMIP2 also includes model response
to an idealized scenario of
atmospheric carbon dioxide increase
(see http://www. pcmdi.llnl.gov)
DKRZ
Deutsche Klimarechnungszentrum,
Hamburg, Germany
GFDL
Geophysical Fluid Dynamics
Laboratory, Princeton, New Jersey,
USA
HadCM2/3 Coupled models of the Hadley
Centre for Climate Prediction and
Research, Meteorological Office,
Bracknell, UK
HOPE
Hamburg Ocean Primitive Equation
Model (DKRZ; Wolff et al., 1997)
LODYC
Laboratoire d’Oceanologie Dynamique et de Climatologie, Paris,
France
LSG
Large-Scale Geostrophic model
(MPI/DKRZ; Maier Reimer
et al., 1993)
MOM
Modular Ocean Model (GFDL),
developed originally from the model
of Bryan (1969)
MPI
Max Planck Institut für
Meteorologie, Hamburg, Germany
NCAR
National Center for Atmospheric
Research, Boulder, Colorado, USA
OPA
Ocean model of LODYC (Madec
et al., 1998)
OPA/
OPA coupled to the atmospheric
ARPEGE
model of Meteo France/European
Centre for Medium Range Weather
Forecasts (Madec and Delecluse,
1997)
OPA/LMD OPA coupled to the atmospheric
model of the Laboratoire de
Meteorologie Dynamique (Madec
and Delecluse, 1997)
OPYC
Ocean isopycnic model (MPI;
Oberhuber, 1993)
SECTION 2 OBSERVATIONS AND MODELS
96