PMIP Documentation for CNRM-2
Centre National de Recherches Météorologiques: Model CNRM ARPEGE Cy14c (T31 L19) 1996
and
Mr. Jean-Francois Royer, CNRM METEO-FRANCE, 42 avenue coriolis, 31057 TOULOUSE cedex, FRANCE; Phone: 33 561 07 93 77; Fax:33 561 07 96 10; e-mail: jean-francois.royer@meteo.fr
World Wide Web URL: http://www.cnrm.meteo.fr
Number of days in each month: 31 28 31 30 31 30 31 31 30 31 30 31
but the 1rst, 5th and 9th year are leap years (29 days in february)
There is yet no paper based on the PMIP version or version 2 of ARPEGE Climat.
As a reference paper you can quote a published paper describing the results of version 0:
Deque,M; Dreveton,C; Braun,A; Cariolle,D (1994): The ARPEGE/IFS atmosphere model: A contribution to the French community climate modelling. Climate Dyn. 10(4/5, Sep), 249-266.
secondary reference(s):
If required for detailed description of the parameterizations of version 2 an unpublished technical document: "Community modelling, 1996: ARPEGE-CLIMAT - Version 2- I. Algorithmic documentation." is available from: Michel.Deque@meteo.fr
Dandin, Ph; J.J. Morcrette,(1996): The ECMWF FMR scheme in the Meteo-France Climate model Arpege-Climat. Note de travail du Groupe de meteorologie de grande Echelle et Climat (GMGEC), no 50.( Available from: CNRM, 42 Av G Coriolis, F-31057 Toulouse Cedex, France).
Deque,M; Piedelievre,JP (1995): High resolution climate simulation over Europe. Climate Dyn. 11(6, Aug), 321-339.
Douville, H.; J.F. Royer (1995): A new snow parameterization for the Meteo-France climate model. Part I: validation in stand-alone experiments. Climate Dynamics, 12, 21-35
Douville, H.; J.F. Royer (1995): A new snow parameterization for the Meteo-France climate model. Part II: validation in a 3-D GCM experiment. Climate Dynamics, 12, 37-52
Geleyn,JF; Bazile,E; Bougeault,P; Deque,M; Ivanovici,V; Joly,A; Labbe,L; Piedelievre,JP; Piriou,JM; Royer,JF (1995): Atmospheric parameterization schemes in Meteo-France's Arpege NWP model. ECMWF Seminar Proc. Parametrization of sub-grid scale physical processes(5-9 September 1994), 385-402.
Land surface processes are represented by the scheme of Noihlan and Planton (1989) which was implemented in the ARPEGE model by JF Mahfouf:
Mahfouf,JF; Manzi,AO; Noilhan,J; Giordani,H; Deque,M (1995): The land surface scheme ISBA within the Meteo-France climate model ARPEGE. Part I: Implementation and preliminary results. J. Climate 8(8, Aug), 2039-2057.
Manzi, AO and S Planton (1994): Implementation of the ISBA parameterization scheme for land surface processes in a GCM: an annual cycle experiment. J. Hydrology, 155, 355-389 Noilhan, J and JF Mahfouf (1996): The ISBA land surface parameterization scheme. Glob. Planet. Change, 13, 145-159
Sensitivity experiments are described in:
Douville H and JF Royer (1996): Sensitivity of the Asian summer monsoon to an anomalous Eurasian snow cover within the Meteo-France GCM. Climate Dynamics, 12, 449-466
Douville H and JF Royer (1997): Influence of the temperate and boreal
forests on the Northern hemisphere climate in the Meteo-france climate
model. Climate Dynamics, 13, 57-74
dim_longitude*dim_latitude: 96*48.
For a surface pressure of 1000 hPa, the bottom layer is from 990 to
1000 hPa with the midlevel at 995 hPa.
Relevant references.
Simmons A and D Burridge (1981): An energy and angular momentum conserving
vertical finite difference scheme and hybrid vertical coordinates. Mon.
Wea. Rev, 109, 758-766
For a surface pressure of 1000 hPa, there are 5 layers below 800 hPa 6 layers above 200 hPa
The 19 vertical levels in hybrid coordinate are defined by: Pressure p(L) at half levels L (i.e. at the interface between atmospheric layers) are computed from the surface pressure p_s from the formula:
p(L) = A(L)+B(L)* ps
where A(L) and B(L) are coefficients which in this T31-L19 simulation
have been given the values:
A:2000.000,4000.000,6491.873,10000.000,13466.847,15602.481,16578.893,16568.072,15742.010,14272.696,12332.122, 10092.277,7725.153,5402.739,3297.026,1580.005,423.666,0.000,0.000
B:0.000,0.000,0.000,0.000,0.014,0.052,0.112,0.188,0.277,0.375,0.478,0.581,0.681,0.773,0.855,0.920,0.967,0.990,1.000
Relevant references.
Asselin (1972): Frequency filter for time integrations. Mon. Weath.
Rev., 100, 487-490
The gravity-wave stress is assumed to be maximum at the surface, and in a direction that depends on the (2 x 2) covariance matrix of the unresolved oragraphy (a measure of the anisotropy of the mountains) as well as on the mean wind in the planetary boundary layer. The magnitude of the surface stress is proportional to the product of the air density, the Brunt-Vaisalla frequency at the surface, the wind speed at the lowest vertical level, and the root-mean square of the unresolved orography in the direction of this wind (calculated from the subgrid-scale orographic variance).
At levels above the surface, the gravity-wave stress is assumed to be in the same direction as the surface stress. The vertically propagating gravity waves do not interact with the mean flow below a critical level of resonance. Above this level, their resonant amplification follows the experimental results of Clark and Peltier (1984), while dissipation proportional to the square of the Froude number also operates. The gravity waves are trapped and reflected with dissipation at the vertical level where the Brunt-Vaisalla frequency becomes zero. Cf. Deque et al. (1994))for further details.
A modification of the parameterization of momentum deposition by gravity-waves
in order to increase momentum deposition in the lower atmospheric layers
has been introduced by Geleyn et al, 1995. (A parameterization of gravity-wave
source due to convection has been introduced in version 2, but is not used
in this PMIP simulation).
Seasonal and diurnal cycles are included
Update of the coefficients for the ozone parameterization by recomputing them from a more recent bidimensional photochemical model. Ozone is not treated as a prognostic variable. Enumeration of radiatively active gases and concentration for control, 6ka and 21ka (CO2, ozone, water vapor, other trace gases) and aerosols.
control:
CO2 : 353 ppmv
CH4: 1.72 ppmv
N2O: 310 ppbv
CFC-11: 280 pptv
CFC-12: 484 pptv
6ka
CO2 : 286 ppm
CH4: 1.72 ppmv
N2O: 310 ppbv
CFC-11: 280 pptv
CFC-12: 484 pptv
There are a globally uniform distribution for the trace gases (CO2,CH4,N2O,
CFC) and a globally uniform vertical profile for ozone imposed geographical
distribution for 5 types of aerosols water vapour is treated spectrally
by an Eulerian transport scheme.
6 spectral bands covering 0-282000 m-1:
0- 35000 m-1 + 145000-188000 m-1
50000- 80000 m-1
80000- 97000 m-1 + 111000-125000 m-1
97000-111000 m-1
35000- 50000 m-1
125000-145000 m-1 + 18800-282000 m-1
Droplet absorption and scattering are taken into account and are determined from Liquid and Ice water paths computed from a diagnostic liquid and ice concentration in clouds. A Delta-Eddington method is used for the shortwave and an emissivity formulation for the longwave. A maximum overlap between cloud layers has been assumed
Aerosol effects are taken into account for 5 types of aerosols (Tanré
et al, 1984) Four types (desertic, land sea and urban) have a specified
geographical distribution, while a well mixed distribution is assumed for
the background aerosol. In the shortwave, aerosol scattering and absorption
are computed from their Mie parameters. In the longwave, absorption effects
of aerosols are based on an emissivity formulation.
Shallow convection is parameterized as part of the stability dependent
computation of the turbulent exchange coefficients by a modification of
the Richardson number using the vertical gradients of specific humidity
(Geleyn, 1987)
The critical humidity profile Hc is specified as a function of the vertical hybrid sigma-pressure coordinate at full levels by the following formula: Hc = 1 - HUCOE * z * (1 - z) * (1 + sqrt(HUTIL) * (z - 0.5)).
The 2 empirical coefficients HUCOE and HUTIL of the critical profile
are tuned to accomplish several objectives: to produce generally larger
cloud fractions than in the baseline model; to yield a planetary albedo
of about 0.30; to result in approximate balance of global annual-mean radiation
at the top of the atmosphere. Cf. Deque and Piedelievre (1995)and Deque
et al. (1994) for further details. In the T31 version used for this PMIP
simulation we have taken HUCOE = 1.2 and HUTIL = 3. A convective cloud
cover is computed from the total convective precipitation and combined
with the stratiform cloud cover
potential instability on the vertical and positive water vapor convergence
over the depth of the convective cloud as computed by the Bougeault (1985)
parameterization. Large scale precipitation is evaporated and melted in
the underlying layers a subgridscale distribution is assumed only for the
interception of convective precipitation by the vegetation canopy
A fractional land cover for each grid point on the Gaussian grid was
computed from the U.S. Navy data set. Points with a fractional land cover
above 50 % were specified as land.
For 6 fix: SSTs and sea-ice prescribed at their present day value, as
in the control run.
The land surface scheme includes the evolution of a single snow layer represented by the snow mass Wn The prognostic equation for Wn takes into account snow precipitation Pn, snow sublimation En, and snowmelt Fn:
d(Wn)/dt = Pn - En - Fn.
Snowmelt occurs when the surface temperature is larger than 273.16 K. The snow density increases exponentially with an e-folding time of about 4 day since the last snowfall from a value of 100 kg/m3 for fresh snow up to a maximum value of 300 kg/m3 for old snow. Fractional snow cover for radiative computations Pnr is computed as a function of the snow mass Wn and a critical value Wnc by the following formula:
Pn = Wn / (Wn + Wnc * (z0 / z0cp))
This fractional snow cover is used for computing surface albedo and emissivity
surface roughness is modified by the presence of snow.
z0 = z0f * (1-Pnz) + zon * Pnz
where z0f is surface roughness in the absence of snow z0n is roughness length of snow (set to 0.001 m) Pnz is a fractional cover for roughness computed as
Pnz = Wn / (Wn + Wnc * (1+ z0f/z0cz) )
where z0cz is a characteristic roughness length (0.025 m), Wn a characteristic
snow mass ( 10 km/m2).
Primary and secondary vegetation cover and type specified in each grid box from 13 classes determined by the Manzi and Planton (1994) simplification of the Wilson and Henderson-Sellers (1985) dataset. Roughness length, leaf area index (LAI), and minimum stomatal resistance required by the land surface scheme are specified according to the vegetation class and soil characteristics of the grid box by blending values associated with the primary and secondary vegetation weighted in a 3 to 1 ratio, respectively. The coverage and roughness length of deciduous and cultivated vegetation also undergo a seasonal cycle. The roughness length includes a contribution from local subgrid-scale orography as well.
It does not really include different soil types but rather use a specification of soil properties such as albedo and percentage of silt, clay and sand from 3 categories of soil color, soil texture and drainage as explained in Mahfouf et al (1995). Soil color, column depth (derived from drainage data of Wilson and Henderson-Sellers (1985)), and texture (fraction of sand and clay required by the land land surface scheme obtained from Webb et al. (1991) data) also are specified for each grid box. The depth of the active soil layer required by the land surface scheme is assigned according to the larger of the vegetation root depth vs the bare-soil depth.
As in the baseline model, surface albedos are a function of solar zenith
angle, but their values are assigned differently. Albedos over land are
prescribed according to vegetation cover (blended as described above for
primary and secondary vegetation types) and soil color. Observed albedo
from Meteosat and NOAA satellites are used to correct the bareground albedo
when the vegetation cover is less than 50% Surface longwave emissivities
are prescribed in the same manner as in the baseline model.
Over land, the surface moisture flux is made up of evaporation from
bare ground, snow sublimation, and from moisture intercepted by the vegetation
canopy, as well as from transpiration by the foliage according to formulations
of the land surface scheme.
An improvement of the ISBA soil-vegetation scheme has been achieved by the introduction of a deep drainage term, interception of convective precipitation by the vegetation canopy, and use of a thermal roughness length smaller than the dynamic roughness length. A new climatology for surface albedo and thermo-hydric properties of bare ground has been used. (Mahfouf et al, 1995)
The recent version of the ISBA scheme is described in Noilhan and Mahfouf (1996). It includes 5 prognostic variables: surface temperature, mean surface temperature, surface volumetric water content, mean volumetric water content, and the water amount intercepted by the vegetation canopy. The time dependence of the prognostic variables are formulated as force-restore equations after Deardorff (1978).
ISBA also requires 7 parameters that are prescribed or derived from other surface characteristics: the vegetation cover, leaf area index (LAI), minimum stomatal resistance, surface shortwave albedo, longwave emissivity, active soil depth, and surface roughness length (see Surface Characteristics). In addition, climatoligical/equilibrium temperatures and volumetric water contents, the maximum moisture capacity of the vegetation canopy, as well as transfer coefficients and restoring time constants are specified in the prognostic equations.
8 land surface characteristics:
- soil depth including the root zone: d_veg
- albedo: \alpha
- roughness length: Z_ov
- minimal vegetation density: veg_min (minimum during the seasonal cycle)
- maximal vegetation density: veg_max (maximum "")
- minimal leaf aera index : LAI_min
- maximal Leaf Area Index : LAI_max
- minimum surface resitance to transpiration: Rs_min
The prescribed values for the 13 different vegetation types are given in table 2 of Mahfouf et al (1995)
Elimination of the relaxation of deep soil temperature toward climatological values, by using a 4-layer scheme for solving the heat layer equation in the ground. Introduction of a limitation on the maximum value of the Richardson number in order to maintain a minimum turbulent transfer between the atmosphere and the surface in very stable stratifications.