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The Canadian Regional Climate Model (CRCM)
We present here the Regional Climate Model (RCM) approach, a general description of the CRCM and information on the different CRCM versions used to produce the climate change simulations.
Specific information on the configuration of the CRCM to produce the different climate change simulations and monthly data from these runs are available from CCCma's data section.
More information about the Canadian Regional Climate Model (CRCM), its applications and validation is available from the Canadian Regional Climate Modelling and Diagnostics Network.
1. The RCM Approach
The one-way nesting of limited area models (LAMs), suitably designed as Regional Climate Models (RCMs), within General Circulation Models (GCMs) is becoming a valuable downscaling technique for simulating the climate of a limited domain. They allow physically based and computationally affordable long-term integrations at high spatial resolution. RCMs are now been used in many climate research centres around the world.
The Canadian RCM (CRCM), which can be set up to run on a domain covering any part of the globe, first emerged from combining the semi-Lagrangian semi-implicit MC2 (Compressible community mesoscale model) dynamical kernel with the CCCma atmospheric GCM physics parameterization package.
For regional climate modelling applications, MC2 (Laprise et al., 1997) was initially coupled with the physical parameterization package of the CCCma second generation atmospheric GCM (AGCM2; McFarlane et al., 1992) to generate the first version of the CRCM.
As the Canadian RCM is a limited area model, it is necessary to specify the lateral atmospheric and the lower boundary conditions: a procedure called "nesting". In the interior of the domain, the RCM is free to develop its "own" fine scale structures (in the "free zone").
2. Description of the CRCMThe numerical formulation of the Canadian RCM is based on the MC2 (Mesoscale Compressible Community) dynamical kernel developed by the late Andre Robert and his colleagues of the Cooperative Centre for Mesoscale Meteorology (CCRM). MC2 is based on the fully elastic, non-hydrostatic Euler field equations solved with a state-of-the-art semi-implicit and semi-Lagrangian (SISL) numerical integration scheme adequate for computing atmospheric flow at all spatial scales. CRCM atmospheric variables are discretized on an Arakawa C-type staggered grid on a polar-stereographic projection in the horizontal and on Gal-Chen (Gal-Chen and Somerville, 1975) terrain-following scaled height coordinate in the vertical. The efficiency of the SISL scheme allows the use of longer timesteps (at least by a factor of 3) when compared with other non SISL-RCMs at the same spatial resolution. A description of MC2 is found in Bergeron et al. (1994) and Laprise et al. (1997).
For regional climate modelling applications, the nesting data used can come from a GCM, for example the CGCM2. The first part of the nesting procedure consists of driving the CRCM with a time series of atmospheric fields from the driving model (e.g., CGCM2) (namely pressure, temperature, water vapor and horizontal wind components) at the external lateral boundaries exactly. The surface pressure is nested, as the other atmospheric variables, at the lateral boundary. Then, towards the interior of the domain, through an external sponge belt ("sponge zone"), the driving atmospheric fields (e.g., CGCM2) (generally only the winds) are gradually blended with corresponding CRCM fields. Throughout the rest of the regional domain (towards the interior), usually defined as the "free zone", the CRCM is not affected by the driving data (e.g., CGCM2). More recently, a spectral nudging technique has been developed and can be applied within the interior of the regional domain ("free zone") to keep CRCM's large-scale flow close to its driving data. This spectral nudging technique, developed by Riette and Caya (2002), uses the spectral decomposition from Denis et al. (2002) and is based on the approach from von Storch et al. (2000). In addition, to prevent any climatic drift of surface pressure, the domain averaged value of pressure at the lowest CRCM level is continually adjusted to remain consistent with the driving data (e.g., CGCM2). The pressure on model levels away from the surface are adjusted accordingly.
The second part of the nesting consists in specifying geophysical and other surface fields adapted to the CRCM grid. This set of parameters may include fixed quantities (i.e., geophysical soil and vegetation properties including orography) as well as time-dependent ones (i.e., sea-surface and sea-ice temperature). The overall nesting procedure is one-way, meaning that the CRCM does not feedback on the driving model (e.g., CGCM2).
It is also possible to use atmospheric reanalyses as nesting data for the CRCM which will be useful in hindcast mode.
Details on the numerical formulation of the CRCM can be found in Caya and Laprise (1999).
3. CRCM versions for climate change simulationsWe present here a description of the different CRCM versions used to produce the climate change simulations, starting with the most recent run.
Specific information on the configuration of the CRCM to produce these climate change simulations and monthly data from these runs are available from CCCma's data section.
A description of CRCM3.7 and CRCM3.6, their validation and response to increasing greenhouse-gas forcing can be found in Plummer et al. (2006). For CRCM3.5, this information is presented in Laprise et al. (2003).
Beginning with version 3.6, the CRCM can utilize spectral nudging of large-scale winds within the regional domain (Riette and Caya, 2002) and be coupled with a lake model for the Laurentian Great Lakes (Goyette et al., 2000).
Our latest version, CRCM4.2 is even more in-line than CRCM 3.7 with the CCCma GCM3 package (Scinocca and McFarlane, 2004). The most important change consisted in the implementation of GCM3's multi-layer surface scheme CLASS 2.7 (Canadian LAnd Surface Scheme; Verseghy, 1991; Verseghy et al., 1993) in the CRCM to provide a more realistic description of water and energy exchange between the land surface and atmosphere. Starting from the surface, CLASS uses three soil layers with thicknesses of 0.1 m, 0.25m and 3.75 m, corresponding approximately to the depth influenced by the diurnal cycle, the rooting zone and the annual variations of temperature, respectively. CLASS includes prognostic equations for energy and water conservation for the three soil layers and a thermally and hydrologically distinct snowpack where applicable (treated as a fourth variable-depth soil layer). Vegetation canopy in CLASS is treated explicitly. Also, a minor modification to CRCM4.2 consisted in introducing GCM3's turbulent transfer coefficients for surface exchanges of heat, moisture and momentum.
Many differences are found between CRCM versions 3.7 and 3.6, since CRCM 3.7 was created to bring the physical parameterizations of the CRCM more in-line with the CCCma GCM3 package (Scinocca and McFarlane, 2004). The calculation of short-wave radiation has changed considerably in CRCM 3.7; as a result, it has improved (i.e. increased) atmospheric absorption of solar radiation as compared with the earlier version. Radiative effects of greenhouse gases are now considered separately for CO2, CH4, N2O, CFC11 and CFC12 (replacing equivalent CO2). The formulation of cloud cover and vertical mixing in the boundary layer have also been modified to be more realistic. A constant soil water capacity has been introduced for the single-layer representation of the soil, giving more realistic (i.e. increased) Bowen ratios, thereby reducing the overestimated summer surface evaporation/precipitation ratios over land. The modified soil water capacity also shortened the freezing (and thawing) period, allowing an earlier onset of snow on the ground in the fall (Frigon et al., 2002). However, this had the adverse effect of producing excessive soil drying and especially hot summer temperatures in the southeastern USA. Snow masking depth has been changed from the spatially varying field (used previously in version 3.6) to a uniform value of 3.0 m over land surfaces; it remains variable over tundra, desert and swamp surfaces. The snow masking depth represents the specified depth of snow where surface elements are assumed to be covered by snow and the surface albedo changes from the albedo of land to that of snow. This change eliminated spurious gradients of spring snow cover found in some areas (e.g., Canadian Prairies). And lastly, the internal water budget is now conserved every timestep over the entire free domain.
The main difference between CRCM versions 3.5 and 3.6 is found in the deep and shallow convection schemes.
An analysis of CRCM's very first climate change simulation is
presented in Laprise et al. (1998). This first
experiment was driven by AGCM2
equilibrium simulations (with constant atmospheric CO2). The CRCM was run over a small domain covering Western
Canada (WCAN1 domain, totalling only 100x70 grid points), also with a
45-km horizontal grid-size mesh. It was integrated over two 5-year time slices
with current and with double CO A description of CRCM4 and its validation can be found in Music and Caya (2007).
However, no paper has yet appeared on CRCM4.2
and its response to increasing greenhouse-gas forcing.
Details on the numerical formulation of the CRCM can be found
in Caya and Laprise (1999).
Dynamical core (Laprise et al., 1997)
Nesting Strategy
Physical parameterization
Mostly based on CCCma GCM3
package (Scinocca and McFarlane, 2004)
CLASS includes prognostic equations for energy and water conservation for the three soil layers
and a thermally and hydrologically distinct snowpack where applicable
(treated as a fourth variable-depth soil layer).
In other words, liquid and frozen water contents and temperature fluxes
evolve at the top and bottom of each soil layer.
The thermal budget is performed over the three soil layers but the hydrological budget is done only
in layers contained above the bedrock.
Vegetation canopy in CLASS is treated explicitly with properties
based on four vegetation types: coniferous tree, deciduous trees, crops and grass.
Vegetation canopy can intercept rain and snow precipitation and has its own
energy and water treatment with prognostic variables for canopy temperature, water storage and mass.
In an attempt to crudely mimic sub-grid scale variability, CLASS adopts a "pseudo-mosaic" approach
and divides each grid cell into a maximum of four sub-areas:
bare soil, vegetation, snow over bare soil and snow with vegetation.
The energy and water budget equations are
first solved for each sub-area separately and then averaged over the grid cell.
Physics adapted to finer resolution
Lake model
Internal budgets
A description of CRCM3.7.1, its validation and its response to
increasing greenhouse-gas forcing can be found in Plummer et al. (2006).
Details on the numerical formulation of the CRCM can be found
in Caya and Laprise (1999).
Dynamical core (Laprise et al., 1997)
Nesting Strategy
Physical parameterization
Mostly based on CCCma GCM3
package (Scinocca and McFarlane, 2004)
Physics adapted to finer resolution
Lake model
Internal budgets
A description of CRCM3.6, its validation and its response to
increasing greenhouse-gas forcing can be found in Plummer et al. (2006).
Details on the numerical formulation of the CRCM can be found
in Caya and Laprise (1999).
Dynamical core (Laprise et al., 1997)
Nesting Strategy
Physical parameterization
Mostly based on CCCma AGCM2
package (Boer et al., 1992; McFarlane et al., 1992)
Physics adapted to finer resolution
Lake model
A description of CRCM3.5, its validation and its response to
increasing greenhouse-gas forcing can be found in Laprise et al. (2003).
Details on the numerical formulation of the CRCM can be found
in Caya and Laprise (1999).
Dynamical core (Laprise et al., 1997)
Physical parameterization
Mostly based on CCCma AGCM2
package (Boer et al., 1992; McFarlane et al.,
1992)
Physics adapted to finer resolution
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-Horizontal winds U & V, air temperature, water vapour and pressure from the nesting model
are imposed at the lateral boundary grid-points exactly, as interpolated onto the
CRCM's atmospheric levels.
-Atmospheric horizontal winds U & V relaxed toward values of the driving data
over the sponge zone (generally 9 grid points).
CRCM 3.7.1 Description
-Horizontal winds U & V, air temperature, water vapour and pressure from the nesting model
are imposed at the lateral boundary grid-points exactly, as interpolated onto the
CRCM's atmospheric levels.
-Atmospheric horizontal winds U & V relaxed toward values of the driving data
over the sponge zone (generally 9 grid points).
CRCM 3.6 Description
-Horizontal winds U & V, air temperature, water vapour and pressure from the nesting model
are imposed at the lateral boundary grid-points exactly, as interpolated onto the
CRCM's atmospheric levels.
-Atmospheric horizontal winds U & V relaxed toward values of the driving data
over the sponge zone (generally 9 grid points).
CRCM 3.5 Description
-Horizontal winds U & V, air temperature, water vapour and pressure from the nesting model
are imposed at the lateral boundary grid-points exactly, as interpolated onto the
CRCM's atmospheric levels.
-Atmospheric horizontal winds U & V relaxed toward values of the driving data
over the sponge zone (generally 9 grid points).
References:
Last modified: 2010-01-13
Important Notices