**Model Information of Potential Use to the IPCC Lead Authors and the
AR4.**

**CNRM-CM3 (version used for IPCC AR4)**

2 August 2005

# Model identity:

A.  Institution, sponsoring agency, country:\
    Centre National de Recherches Météorologiques, Météo France, France

B.  Model name (and names of component atmospheric, ocean, sea ice, etc.
    models):\
    CNRM-CM3\
    Atmosphere: ARPEGE-Climat version 3\
    Ocean: OPA 8.1\
    Sea-ice: GELATO 2

C.  Vintage (i.e., year that model version was first used in a published
    application): 2004

D.  General published references and web pages:\
    http://www.cnrm.meteo.fr/scenario2004/references_eng.html

E.  References that document changes over the last \~5 years (i.e.,
    since the IPCC TAR) in the coupled model or its components. We are
    specifically looking for references that document changes in some
    aspect(s) of model performance.\
    - descriptions of previous versions of the ARPEGE-Climat model can
    be found in the following publications:

    -   Déqué et al., 1994

    -   Déqué and Piedelièvre, 1995

    -   Royer et al. , 2002

F.  IPCC model version\'s global climate sensitivity (KW^-1^m^2^) to
    increase in CO~2~ and how it was determined (slab ocean expt.,
    transient expt\--Gregory method, ±2K Cess expt., etc.)

    -   not yet available

G.  Contacts (name and email addresses), as appropriate, for:

    1.  coupled model: David Salas y Melia, David.Salas@meteo.fr

    2.  atmosphere : Michel Déqué, Michel.Deque@meteo.fr

    3.  ocean : David Salas y Melia, David.Salas@meteo.fr

    4.  sea ice: David Salas y Melia, David.Salas@meteo.fr

    5.  land surface: Hervé Douville, Herve.Douville@meteo.fr

    6.  vegetation: Hervé Douville, Herve.Douville@meteo.fr

    7.  other?

# Besides atmosphere, ocean, sea ice, and prescription of land/vegetated surface, what can be included (interactively) and was it active in the model version that produced output stored in the PCMDI database?

A.  Atmospheric chemistry?\
    - Ozone transport with simplified chemistry as described in Cariolle
    and Déqué (1986) and Cariolle et al. (1990).

B.  Interactive biogeochemistry?

> \- no

C.  What aerosols and are indirect effects modeled?\
    - The distributions of marine, desertic, urban aerosols, sulfate
    aerosols are specified. Marine and desertic aerosols are constant in
    all experiments. Urban aerosols vary according to estimates between
    1860 and 2000. Sulfate aerosols are specified in all experiments
    according to Boucher and Pham (2002) data, see
    <http://www-loa.univ-lille1.fr/~boucher/sres/> for more details.
    Note that only the direct effect of anthropogenic sulfate aerosols
    was taken into account.

D.  Dynamic vegetation?

> \- no

E.  Ice-sheets?

> \- fixed

# List the community based projects (e.g., AMIP, C4MIP, PMIP, PILPS, etc.) that your modeling group has participated in and indicate if your model results from each project should carry over to the current (IPCC) version of your model in the PCMDI database.

AMIP with former versions and current version of ARPEGE-Climat\
PMIP 6k BP simulation with former version of ARPEGE-Climat (different
from the IPCC version)

PILPS with the ISBA land surface scheme (same as in the IPCC)

CMIP simulation was performed at CERFACS with a former coupled versions
of ARPEGE-Climat and OPA

# Component model characteristics (of current IPCC model version):

A.  Atmosphere

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1.  Resolution: triangular truncation T63 with "linear" reduced Gaussian
    grid equivalent to T42 quadratic grid (2.8 °)

2.  Numerical scheme/grid (advective and time-stepping schemes; model
    top; vertical coordinate and number of layers above 200 hPa and
    below 850 hPa):

\- semi-lagrangian semi-implicit time integration with 30 mn time-step,
3 hour time-step for radiative transfer;

> \- top layer 0.05 hPa, progressive hybrid sigma-pressure vertical
> coordinate with 45 layers, 23 layers above 200 hPa, usually 7 layers
> below 850 hPa (less in regions of high orography)

3.  List of prognostic variables (be sure to include, as appropriate,
    liquid water, chemical species, ice, etc.). Model output variable
    names are not needed, just a generic descriptive name (e.g.,
    temperature, northward and eastward wind components, etc.)

> \- temperature, northward and eastward wind components, specific
> humidity, ozone concentration, surface pressure

4.  Name, terse descriptions, and references (journal articles, web
    pages) for all major parameterizations. Include, as appropriate,
    descriptions of:

    a.  Clouds:\
        - statistical cloud scheme for stratiform clouds based on Ricard
        and Royer (1993). Convective cloud cover based on the mass-flux
        transport

    b.  Convection\
        - mass-flux convective scheme with Kuo-type closure based on
        Bougeault (1985) boundary layer based on Louis et al. (1982)
        with modifications by Mascart et al. (1995). SW, LW radiation
        based on Fouquart and Morcrette parameterizations implemented in
        a former version of the ECMWF model (Morcrette JJ, 1990;
        Morcrette JJ, 1991)

    c.  any special handling of wind and temperature at top of model:\
        - relaxation of temperature, linear (Rayleigh) friction for wind

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B.  Ocean: OPA 8.1 developped by LODYC (Madec et al. 1998)

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1.  Resolution: 182 x 152 grid (with resolution of about 2° in
    longitude, and resolution varying in latitude from near 0.5° at the
    equator to roughly 2° in polar regions).

2.  Numerical scheme/grid, including advection scheme, time-stepping
    scheme, vertical coordinate, free surface or rigid lid, virtual salt
    flux or freshwater flux

> \- Arakawa C grid, Advection scheme: upstream

\- time-stepping scheme: 15 time-steps per day. The non-diffusive part
of the scheme is treated in leapfrog, whereas the differencing scheme of
the diffusive part is implicit.

\- z-coordinate (31 vertical levels with 10 levels in the upper 100 m),
rigid lid, freshwater flux.

3.  List of prognostic variables and tracers:\
    - temperature, salinity, vertical eddy viscosity (TKE scheme),
    zonal, meridional and vertical velocity components.

4.  Name, terse descriptions, and references (journal articles, web
    pages) for all parameterizations

> \- The ocean model is extensively described in : Madec et al. (1997)

5.  Include, as appropriate, descriptions of:

    a.  Eddy parameterization:\
        - vertical : TKE

    b.  horizontal :

> \- isopycnal diffusion, with eddy viscosity of 40000 m2/s for momentum
> and eddy diffusivity equal to 2000 m2/s

c.  Bottom boundary layer treatment and/or sill overflow treatment\
    - zero fluxes of heat and salt, and linear friction on momentum

d.  Mixed-layer treatment:

> \- 1.5 turbulent closure scheme (Blanke and Delecluse, 1993). Sunlight
> penetration: downward irradiance formulated with two extinction
> coefficients (Paulson and Simpson, 1977) with values corresponding to
> a type I water in Jerlov's classification

e.  Tidal mixing:

> \- no

f.  River mouth mixing:

> \- distribution of freshwater fluxes from rivers over several ocean
> grid points

g.  Mixing isolated seas with the ocean:

> \- none

h.  Treatment of North Pole \"singularity\" (filtering, pole rotation,
    artificial island?)

> \- no pole singularity in the chosen OPA grid (Madec and Imbard, 1996)

C.  Sea ice\
    The GELATO, developed at CNRM by David Salas y Melia, is described
    in Salas-Mélia, D. (2002).

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1.  Horizontal resolution, number of layers, number of thickness
    categories

\- grid: same as OPA's. Number of layers: 4 in the ice part of the slab,
1 in the snow part of the slab. Number of thickness categories : 4,
0-0.3m, 0.3-0.8m, 0.8-3m, and 3m or more.

2.  Numerical scheme/grid, including advection scheme, time-stepping
    scheme,

\- time-stepping scheme: leap frog, except for heat diffusion in the
sea-ice/snow slab (implicit scheme).

\- advection scheme : semi-lagrangian (from CICE model), as described in
Hunke et al. (2002)

3.  list of prognostic variables

\- For this experiment, a reduced set of prognostic variables is
produced: sea ice zonal and meridional velocity components,
concentration, albedo, thickness, snow layer thickness, surface
temperature, ocean flux, net heat flux weighted on the marine surface,
net heat flux weighted on the different sea ice categories, virtual
fresh water flux at the base of sea ice, net sea ice production field.

4.  Completeness (dynamics? rheology ? leads? snow treatment on sea ice)

\- includes: elastic-viscous-plastic (EVP) rheology (Hunke and Dukowicz,
1997), leads and snow treatment on sea ice

5.  Treatment of salinity in ice

> \- sea ice salinity is constant in GELATO (6 psu)

6.  brine rejection treatment

\- sea ice melting and freezing gives birth to a salt flux which is
computed as a 'virtual freshwater flux'

7.  treatment of the North Pole 'singularity' (filtering, pole rotation,
    artificial island?)

\- no pole singularity as GELATO grid is the same as OPA's.

D.  Land / ice sheets (some of the following may be omitted if
    information is clearly included in cited references.\
    The land surface scheme ISBA (Interactions Soil Biosphere
    Atmosphere) developed initially by Noilhan and Planton (1989) has
    been updated and described by Mahfouf et al. (1995).

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1.  Resolution (tiling?), number of layers for heat and water

> \- 2.8°, 4 soil layers for heat and 2 for water

2.  Treatment of frozen soil and permafrost:

> \- yes

3.  Treatment of surface runoff and river routing scheme\
    - runoff is transported to the ocean with the river routing scheme
    TRIP developed by T. Oki (Oki, T. and Sud, Y.C., 1998; Oki, T.,
    Wishimyra, T., Dirmeyer, P., 1999; Chapelon et al. 2002)

4.  Treatment of snow cover on land:

    -   snow parameterization described in Douville et al. (1995a and
        1995b).

5.  Description of water storage model and drainage:

    -   Force-restore approach

    -   Deep drainage as a relaxation toward field capacity + a residual
        subgrid drainage below field capacity

    -   VIC-type subgrid runoff

6.  Surface albedo scheme

    -   snowfree albedo from ECOCLIMAP (Masson et al. 2003)

    -   prognostic snow albedo (Douville et al. 1995a)

    -   diagnostic snow fraction as a function of snow mass, vegetation
        roughness length and subgrid orography (Douville et al. 1995a
        and 1995b)

7.  Vegetation treatment

    -   prescribed vegetation map and prescribed phenology from
        ECOCLIMAP (Masson et al. 2003)

    -   no carbon cycle

8.  List of prognostic variables:

    -   4-layer soil temperatures

    -   2-layer soil hydrology (liquid and solid)

    -   1-layer snow hydrology (prognostic snow mass, snow albedo and
        snow density)

    -   1 interception reservoir (liquid water on the canopy)

9.  Ice sheet characteristics (How are snow cover, ice melting, ice
    accumulation, ice dynamics handled? How are the heat and water
    fluxes handled when the ice sheet is melting?)

    -   ice sheet are represented simply by prescribing initially a huge
        snow amount and applying to it the same snow parameterization as
        over the land surface.

    -   ice dynamics is not included

    -   Climatological calving of icebergs was taken into account around
        the Antarctic (not Greenland). During the summer season (october
        to march), a constant flux of ice (0.14 Sv) is calved at the
        coast. This climatological value was estimated from a
        preliminary coupled control run in which the average quantity of
        snow accumulated over the Antarctic was computed. The
        corresponding mass of snow was found to be close to current
        estimates of the total mass of ice calved in the Antarctic seas
        per year. This approximation is valid as long as ice sheets are
        in steady state, i.e. if they do not significantly shrink or
        spread, which we assume here.

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E.  coupling details\
    Coupling between atmosphere, ocean and sea ice models is done
    through the OASIS 2.2 coupler developed at CERFACS. Note that the
    sea ice model is included in the ocean model. For a reference of the
    coupling software, see Terray et al. (1998).

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1.  frequency of coupling:

> \- 24 hours

2.  Are heat and water conserved by coupling scheme?

> \- yes

3.  list of variables passed between components:

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a.  atmosphere -- ocean :\
    - temperature over sea, non solar heat flux, solar heat flux, water
    flux, zonal wind stress, meridional wind stress, evaporation flux,
    liquid precipitation, solid precipitation, non solar heat flux
    derivative

b.  atmosphere -- land :

> \- radiative and turbulent surface fluxes, temperature, albedo,
> surface roughness, soil moisture

c.  land -- ocean:

> \- runoff et river outlet

d.  sea ice -- ocean:

> \- sea surface temperature, salinity, currents, mixed layer depth,
> ice-\> ocean momentum, freshwater and heat fluxes

e.  sea ice -- atmosphere:

> \- temperature over sea-ice, sea-ice albedo, sea-ice concentration,
> non solar heat flux, solar heat flux, water flux, zonal wind stress,
> meridional wind stress, evaporation flux, liquid precipitation, solid
> precipitation, non solar heat flux derivative

f.  Flux adjustment? (heat?, water?, momentum?, annual?, monthly?)

> \- no flux adjustment

# Simulation Details (report separately for each IPCC simulation contributed to database at PCMDI)

**Picntrl/Run_1**

> This preindustrial control simulation was initialized from a coupled
> simulation of a previous version of CNRM coupled model initialized an
> ocean at rest with temperature and salinity profiles specified from
> Levitus (1982) climatology, integrated for 30 years with a relaxation
> of surface temperature to the monthly mean Reynolds climatology for
> 1950. The CNRM-CM3 version was then integrated for 70 year with
> preindustrial 1860 greenhouse gases concentrations as a spin-up. After
> this spin-up period results have been stored from nominal years 1930
> to 2429.

**20C3M/Run_1**

This simulation was initialized from January/2040 of the Picntrl/Run_1
simulation

> Solar forcing was set at 1370 W/m2 and no solar or volcanic
> variability were included. The greenhouse gases annual global
> concentrations were specified based on observations as specified in
> the ENSEMBLES project webpage
> (http://www.cnrm.meteo.fr/ensembles/public/results/results.html).
> Sulfate aerosols are specified according to Boucher and Pham (2002)
> data (<http://www-loa.univ-lille1.fr/~boucher/sres/>) interpolated at
> annual resolution. Results are given for the years 1860 to 2000.

**Commit/Run_1**

This simulation was initialized from January/2000 of the 20C3M/Run_1
simulation.

> The radiative forcing agents are fixed at their year 2000 value.
> Results are given for years 2000 to 2100.

**SRESA2/Run_1**

This simulation was initialized from January/2000 of the 20C3M/Run_1
simulation.

> The greenhouse gases annual global concentrations were specified based
> on scenario SRES A2 as specified in the ENSEMBLES project webpage
> (<http://www.cnrm.meteo.fr/ensembles/public/results/results.html>).
> Sulfate aerosols are specified according to Boucher and Pham (2002)
> data (<http://www-loa.univ-lille1.fr/~boucher/sres/>) interpolated at
> annual resolution. Results are given for years 2000 to 2100.

**SRESA1B/Run_1**

> This simulation was initialized from January/2000 of the 20C3M/Run_1
> simulation. The greenhouse gases annual global concentrations were
> specified based on scenario SRES A1B as specified in the ENSEMBLES
> project webpage
> (http://www.cnrm.meteo.fr/ensembles/public/results/results.html).
> Sulfate aerosols are specified according to Boucher and Pham (2002)
> data (<http://www-loa.univ-lille1.fr/~boucher/sres/>) interpolated at
> annual resolution. Results are given for years 2000 to 2300.

**SRESB1/Run_1**

This simulation was initialized from January/2000 of the 20C3M/Run_1
simulation. The greenhouse gases annual global concentrations were
specified based on scenario SRES B1 as specified in the ENSEMBLES
project webpage
(http://www.cnrm.meteo.fr/ensembles/public/results/results.html).
Sulfate aerosols are specified according to Boucher and Pham (2002) data
(<http://www-loa.univ-lille1.fr/~boucher/sres/>) interpolated at annual
resolution. Results are given for years 2000 to 2300.

**1%to2x/Run_1**

This simulation was initialized from January/2040 of the PIcntrl/Run_1
simulation. This initial state corresponds to nominal year 1860 of
1%to2x/Run1 experiment. The concentrations of greenhouse gases are held
constant at preindustrial levels, except for CO2, which increases from
its preindustrial level (286.2 ppm) at the rate of 1% per year, until
the initial concentration is doubled. From the time of doubling (nominal
year 1930 of the run), the concentrations of all radiative forcing are
held constant for 150 years. Results are given for nominal years 1860 to
2080.

**1%to4x/Run_1**

This simulation was initialized from January/2040 of the PIcntrl/Run 1
simulation. This initial state corresponds to nominal year 1860 of
1%to2x/Run1 experiment. The concentrations of greenhouse gases are held
constant at preindustrial levels, except for CO2, which increases from
its preindustrial level (286.2 ppm) at the rate of 1% per year, until
the initial concentration is quadrupled. From the time of quadrupling
(nominal year 2000 of the run), the concentrations of all radiative
forcing are held constant for 150 years. Results are given for nominal
years 1860 to 2150.

**AMIP/Run_1**

The initial condition for this simulation was the 1 Dec 1977 of the
20C3M/Run_1. The year 1978 was used as a spin-up period before storing
the results over 1979-2000

# References

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effects of cumulus convection, Mon. Wea. Rev. 113, 2108-2121

Blanke, B. and Delecluse, P. (1993): Variability of the tropical
Atlantic Ocean simulated with a general circulation model with two
different mixed layer physics. J. Phys. Oceanogr., 23, 1363-1388

Cariolle, D. and Déqué, M. (1986): Southern hemisphere medium-scale
waves and total ozone disturbances in a spectral general circulation
model. J Geophys. Res 91, 10825-10846\
Cariolle, D., Lasserre-Bigory, A., Royer, J.-F. and Geleyn, J.-F.
(1990): A general circulation model simulation of the springtime
Antarctic ozone decrease and its impact on mid-latitudes, J. Geophys.
Res. Atmos. 95, 1883-1898

Chapelon, N., Douville, H., Kosuth, P. and Oki, T. (2002): Off-line
simulation of the Amazon water balance: a sensitivity study with
implications for GSWP, Clim. Dyn., 19, 141-154

Déqué M., Dreveton, C., Braun, A., and Cariolle, D. (1994): The
ARPEGE/IFS atmosphere model : A contribution to the French community
climate modelling. Climate Dyn., 10, 249-266.

Déqué, M. and J.P. Piedelievre (1995): High resolution climate
simulation over Europe. Climate Dyn., 11, 321-339.

Douville, H., Royer, J.-F. and Mahfouf, J.-F. (1995a): A new snow
parametrization for the Météo-France climate model. Part I: Validation
in stand-alone experiments, Clim. Dyn. 12, 21-35

Douville, H., Royer, J.-F. and Mahfouf, J.-F. (1995b): A new snow
parametrization for the Météo-France climate model. Part II: Validation
in a 3-D GCM experiments, Clim. Dyn. 12, 37-52

Hunke, E. C. and Dukowicz, J. K. (1997): An elastic-viscous-plastic
model for sea ice dynamics. J. Phys. Oceanogr., 27, 1849-1867

Hunke, E. C. and Lipscomb, W. H. (2002): CICE: the Los Alamos sea ice
model, documentation and software User\'s Manual. T-3 Fluid Dynamics
Group, Los Alamos National Laboratory, Tech. Rep. LACC-98-16 v.3.

Madec, G. and Imbard, M. (1996): A global ocean mesh to overcome the
North Pole singularity, Clim. Dyn. 12, 381-388

Madec G., Delecluse P., Imbard M., Lévy C. (1998): OPA version 8.1 Ocean
General Circulation Model Reference Manual, Notes du Pôle de
Modélisation, Institut Pierre-Simon Laplace, n°11, 91 pp \[Available
from Laboratoire d\'Océanographie Dynamique et de Climatologie,
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Mahfouf, J.-F. et al. (1995): The land surface scheme ISBA within the
Météo-France climate model ARPEGE. Part I: Implementation and
preliminary results. J. Climate 8, 2039-2057

Mascart P., Noilhan, J. and Giordani, H. (1995): A modified
parameterization of flux profile relationships in the surface layer
using different roughness length values for heat and momentum. Bound.
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Masson, V. et al. (2003) : A global database of land surface parameters
at 1-km resolution in meteorological and climate models, J. Climate, 16,
1261-1282

Morcrette, J.-J. (1990): Impact of changes to the radiation transfer
parameterizations plus cloud optical properties in the ECMWF model. Mon.
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Morcrette, J.-J. (1991): Radiation and cloud radiative properties in the
European Centre for Medium Range Forecasts forecasting system, J.
Geophys. Res. 95, 9121-9132

Louis et al. (1982): A short history of the operational
PBL-parameterization at ECMWF. In: ECMWF Workshop on Planetary Boundary
Layer Parameterization, ECMWF, Reading, pp 59-80

Noilhan, J. and Planton, S. (1989): A simple parameterization of land
surface processes for meteorological models, Mon. Wea. Rev. 117, 536-549

Oki, T. and Sud, Y.C. (1998): Design of Total Runoff Integrating
Pathways (TRIP) A global river channel network. Earth Interactions,
vol.2, paper 1

Oki, T., Wishimyra, T., Dirmeyer, P. (1999): Assessment of annual runoff
from land surface models using Total Runoff Integrating Pathways (TRIP).
J. Meteorol. Soc. Japan 77, 235-255.

Paulson, C.A. and Simpson, J.J. (1977): Irradiance measurements in the
upper ocean. J. Phys. Oceanogr., 7, 952-956.

Ricard, J.-L. and Royer, J.-F. (1993): A statistical cloud scheme for
use in a AGCM, Ann. Geophysicae 11, 1095-1115.

Royer, J.-F., D. Cariolle, F. Chauvin, M. Déqué, H. Douville, R.M. Hu,
S. Planton, A. Rascol, J.-L. Ricard, D. Salas y Mélia, F. Sevault, P.
Simon, S. Somot, S. Tytéca, L. Terray, S. Valcke (2002): Simulation des
changements climatiques au cours du 21-ième siècle incluant l\'ozone
stratosphérique. C. R. Geophys., 334, 147-154.

Salas-Mélia, D. (2002): A global coupled sea ice-ocean model. Ocean
Modelling 4, 137-172

Terray, L., Valcke, S. and Piacentini, A. (1998): OASIS 2.2 User\'s
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