Regional Climate Models

(a) ARPEGE

ARPEGE-IFS is a global operational forecast model in use at ECMWF and at the French Meteorological Service with different physical parameterizations. A third version is used for climate simulations with another parameterization set. This version is run with variable horizontal resolution, from 50 km in the center of the Mediterranean sea to 450 km in the southern Pacific ocean. It has 31 vertical levels in hybrid coordinate. An earlier version has been described in Déqué et al. (1998). The new features are the radiation scheme (Morcrette, 1990) and the cloud-precipitation-turbulence scheme (Ricard and Royer, 1993). The convection scheme is a mass-flux scheme with moisture convergence closure (Bougeault, 1985).

(b) CHRM

The limited area model CHRM derives from the operational weather forecasting model HRM of the German and Swiss meteorological services (Majewski 1991), which has been adapted into a climate version by ETH Zürich (Lüthi et al. 1996, Vidale et al. 2002). The model's computational grid is a regular latitude/longitude grid (81x91 grid points) with a rotated pole, a resolution of 0.5° (about 55 km) and 20 vertical levels in hybrid coordinates. The model has a full package of physical parameterizations, including a mass-flux scheme for moist convection (Tiedtke 1989) and a Kessler-type microphysics (Kessler 1969, Lin et al. 1983). The lateral boundaries are updated every six hours (with linear interpolation in between), while the soil state is only initialized. A detailed description of the actual model version and further evaluations are given in Vidale et al. (2002). CHRM and REMO (see below) share the same dynamical core, but they differ in terms of physical parameterizations.

(c) HadRM

HadRM is the most recent Hadley Centre regional climate model HadRM3H (Jones and Taylor, 2002). It is a limited area higher resolution version of the AGCM HadAM3H which itself is an improved version of HadAM3, the atmospheric component of the latest Hadley Centre coupled AOGCM, HadCM3. HadAM3 is described in Pope et al. (2000) which contains all the usual representations of atmospheric and land surface physics. The modifications of relevance here (as they relate to precipitation and were instrumental in reducing a warm and dry summer bias) are as follows: (1) A scheme to treat the radiative effects of anvil cirrus in deep convective regimes is included (Gregory, 1999). (2) The threshold relative humidity for cloud formation within a gridbox has been parametrized as a function of horizontal variability resolved by the climate model (Cusack et al. 1999). (3) An empirically adjusted cloud fraction parametrization has been introduced which sets the cloud fraction to 0.6 rather than 0.5 when the gridbox specific humidity reaches saturation. The underlying representation of convection is via the mass-flux scheme of (Gregory and Rowntree 1990) modified to include an explicit downdraught (Gregory and Allen 1991). Convective precipitation is then a function of total cloud condensate. Large-scale precipitation is derived from an explicit cloud water variable of the (Smith 1990) cloud scheme (Jones et al., 1995).

(d) HIRHAM

The HIRHAM applied in this study is an updated version of HIRHAM4 (Christensen et al. 1996). The dynamical part of the model is based on the hydrostatic limited area model HIRLAM, documented by Machenhauer (1988) and Källén (1996). Prognostic equations exist for the horizontal wind components, temperature, specific humidity, liquid water content and surface pressure. HIRHAM4 uses the physical parameterisation package of the general circulation model ECHAM4, developed by Roeckner et al. (1996). These parameterisations include radiation, land surface processes, sea surface sea-ice processes, planetary boundary layer, gravity wave drag, cumulus convection and stratiform clouds. The treatment of precipitation processes includes a newly introduced low precipitation threshold that reduces so-called drizzling, and only when convection is absent. This modification has improved the annual cycle of the mean precipitation in general (see e.g. Hagemann et al. 2001), but also more specifically precipitation frequencies over Denmark (Christensen et al. 2001a). The present work is part of the further validation. Land surface parameterisations uses five prognostic temperature layers and one bucket moisture layer. Runoff is calculated within the Arno scheme (Dümenil and Todini, 1992). Moreover, the updated model utilises high resolution datasets of land surface characteristics (e.g. Hagemann et al. 1999; Christensen et al. 2001b). The standard procedure to initialise soil moisture in the model for climate simulations is a cyclic repetition of the first model year (e.g. 1979) basically following Christensen (1999). However, in contrast to Christensen (1999), the model starts from relatively moist initial conditions. It is assumed that the first cyclic year is sufficient to obtain a balanced initial state for January 1979. The adopted computational grid is a rotated regular latitude/longitude grid (110x104 grid points) with the rotated South Pole at (27 °E, 37 °S), a resolution of 0.44° (about 50 km) and 19 vertical levels in hybrid sigma-p coordinates. (WEST –32.65, EAST 15.31, NORTH 22.7, SOUTH –22.62)

(e) REMO

The regional climate model REMO (Jacob, 2001), as used for the present study, is a combination of the dynamical core of the Europamodell/Deutschlandmodell of the German Weather Service (Majewski and Schrodin, 1994) and the physical parametrisation schemes of the ECHAM4 global climate model (Roeckner et al., 1996) of the Max-Planck Insitute of Hamburg. REMO uses a sperical Arakawa-C grid on regular latitude-longitude coordinates with a rotated pole and a resolution of 0.5° (about 55 km). 19 vertical levels are used, similar to those in ECHAM4. The integration domain covers the whole of Europe and parts of the Atlantic Ocean. Lateral boundary forcing is applied over an eight point boundary zone following the formulation of Davies (1976). Vertical diffusion and turbulent surface fluxes are parametrised following Louis (1979) with a higher order closure for the transfer coefficients of momentum, heat, moisture and cloud water. The land surface parameterization (similar to ECHAM4) encompasses five thermal soil layers (with texture dependent conduction characteristics) and one moisture layer (bucket), taking account of sub-grid scale heterogeneity for runoff calculation (Dümenil and Todini 1992). Land surface parameters are based upon a 1 km global dataset of major ecosystem types (Hagemann et al. 1999). REMO has the same dynamical core like CHRM and shares the same physical parametrisation schemes like those in HIRHAM.

(f) ICTP-RegCM:

The regional climate model RegCM used in PRUDENCE was originally developed by Giorgi et al. (1993a,b) and then augmented as described by Giorgi et al. (1999) and Pal et al. (2000). The dynamical core of the RegCM is essentially equivalent to the hydrostatic version of the NCAR/Pennsylvania State University mesoscale model MM5. Surface processes are represented via the Biosphere-Atmosphere Transfer Scheme (BATS)and boundary layer physics is formulated following a non-local vertical diffusion scheme Giorgi et al. 1993a). Resolvable scale precipitation is represented via the scheme of Pal et al. (2000), which includes a prognostic equation for cloud water and allows for fractional grid box cloudiness, accretion and re-evaporation of falling precipitation. Convective precipitation is represented using a mass flux convective scheme (Giorgi et al. 1993b) while radiative transfer (Giorgi et al. 1999) is computed using the radiation package of the NCAR Community Climate Model, version CCM3. This scheme describes the effect of different GHG, cloud water, cloud ice and atmospheric aerosols. Cloud radiation is calculated in terms of cloud fractional cover and cloud water content, and a fraction of cloud ice is diagnosed by the scheme as a function of temperature.

(g) PROMES:

The regional climate model used in PRUDENCE is the climate version of PROMES model (Castro et al., 1993). It is a primitive equation model, hydrostatic and fully compressible. Vertical coordinates are pressure-based sigma, and a Lambert conformal projection is used in the horizontal, centered on 6 E- 45 N, using an Arakawa-C for grid variables staggering. Prognostic variables are potential temperature, surface pressure, horizontal wind components, specific humidity, cloud and rainwater. Vertical interpolation of driving forcing fields to model levels follows Gaertner and Castro (1996). PROMES model uses a split-explicit integration scheme, based on Gadd (1978). Radiation is considered from Anthes et al. (1987) for absortion and scattering of shortwave radiation by clouds, and longwave processes are parameterized according Stephens (1978) and Garand (1983). Explicit cloud formation and associated precipitation follow Hsie et al. (1984), and subgrid scale convective processes are parametrized using the method of Kain and Fritsch (1993). Turbulent vertical exchanges in the PBL are modelled as proposed by Zhang and Anthes (1982), using a non-local scheme in case of free convection, and local K-theory (Blackadar, 1976) in other cases. Soil-vegetation atmosphere exchanges are parameterized using the land-surface scheme SECHIBA (Ducoudre et al., 1993).

(h) CLM:

The Climate version of the Lokalmodell (CLM) has the same dynamic and physical core as the weather forecast model LM (Lokalmodell) of the German Weather Service (DWD) (Steppeler et al. 2003, and http://cosmo-model.cscs.ch/cosmoPublic/frame.htm).

The CLM is non-hydrostatic and fully elastic. Calculations are performed on a rotated spherical Arakawa C-grid in horizontal direction, and on hybrid terrain-following coordinates in the vertical. The integration in time follows a horizontally explicit and vertically implicit time-splitting scheme. Lateral boundary formulation in grid space is due to Davis (1976). Optionally a boundary formulation in spectral space (called spectral nudging) can be used (von Storch, 2000). A fourth-order linear horizontal diffusion and a Rayleigh-damping in upper layers is part of the model.

Grid scale precipitation is considered including parameterized cloud microphysics (water and ice). Moist convection is parameterized by the mass flux convection scheme after Tiedtke (1989) modified by using a CAPE-closure. A level 2.5 vertical diffusion scheme is implemented including a laminar boundary layer. The delta-two-stream radiation scheme is after Ritter and Geleyn (1992) for short- and longwave fluxes with full cloud-radiation feedback. Soil temperature and water/ice are calculated by a multi-layer soil model. The soil temperature is predicted by a direct solution of the heat conduction equation. A prognostic TKE (turbulent energy) 2.5 level closure scheme can optionally be switch on.

For the requested simulations within PRUDENCE the CLM is run on a rotated spherical grid with a grid mesh of 0.5 degrees (i.e. approx. 56 km) and a total of 101x107 grid points. In a boundary zone of about 8 grid points the influence of the driving model is significant. The vertical height coordinates are hybrid terrain-following height on 20 levels. The multi-layer soil model is run with 9 soil layers (deepest layer at approx. 15m). Deep soil temperature is set to annual mean temperature from the CRU data set. Prognostic cloud ice parameterization and prognostic TKE scheme are switched on for Simulations CTRL and SA2.

The data sets in the PRUDENCE archive with the acronyms CTRL and SA2 were performed with two optional parameterizations switched on: a prognostic ice cloud parameterization and a prognostic TKE scheme. As it turned out the prognostic ice scheme is very sensitive to the driving model. In contrary to experiences at the DWD (were the LM is driven by their own global model which contains basically the same physics as the LM) the CLM produced too high precipitation amount when driven by the Hadley Centre AGCM. For CTRL and SA2 spectral nudging is not applied.

(i) RACMO:

RACMO2 is based on the ECMWF physics cycle 23r4, which has been used for the ERA-40 re-analysis project (see http://www.ecmwf.int/research/ifsdocs/). This physics package consists of the mass flux scheme by Tiedtke (1989) (including many updates), a prognostic cloud scheme by Tiedtke (1993), and tiled land surface scheme TESSEL, including four soil layers (both for soil moisture and temperature) and a skin temperature. In order to reduce the temperature bias in summer the vegetation stress function has been modified and the thickness of the soil layers has been increased (to in total nearly 5 m) as described in Lenderink et al. (2003). RACMO2 uses the HIRLAM (5.0.6) Semi-Lagrangian dynamical core. RACMO2 runs at a resolution of 0.44 degrees. The domain has 114 points in longitudinal direction and 100 in latitudinal direction. The boundary relaxation scheme is 8 points wide, but for the horizontal wind components it is extended to 16 points in order to improve the reproduction of the mean pressure fields within the domain (Lenderink et al. 2003). The model uses 31 vertical levels, corresponding to the ECMWF 31-level resolution. The lowest model level is at 30 m. A time step of 12 min is taken. The boundary layer update interval is 6 h.

(j) RCAO:

RCAO is the SMHI Rossby Centre regional Atmosphere-Ocean model (Döscher et al. 2002), incorporating the Rossby Centre Regional Atmosphere Model, RCA (Rummukainen et al. 2001, Jones et al. 2004) and the Rossby Centre Regional Ocean Model, RCO (Meier et al. 2003), a river routing routine based on the HBV hydrological model (Bergström et al. 1973; Lindström et al. 1997) and lakes (Ljungemyr et al. 1996; Omstedt 1999). RCO and RCA exchange relevant fields of state variables and fluxes using OASIS (Valcke et al. 2000).

RCA traces back to the NWP limited area model HIRLAM (Källén 1996). It has a transformed rotated co-ordinate system, a staggered Arakawa-C grid and the Simmons and Burridge (1982) hybrid vertical co-ordinate. Version 2 of RCA (RCA2, Jones et al. 2004) is applied in the resolution range 10-70 km and with 24 to 60 vertical levels. Lateral boundary forcing is on an eight-point boundary zone (cf. Davies, 1976). Prognostic variables are temperature, horizontal wind components, specific humidity, cloud water, turbulent kinetic energy, surface pressure, soil temperature (predicted at two depths) and water (predicted in two soil layers). The land surface scheme in RCA2 is described by Bringfelt et al. (2001). RCA uses a semi-lagrangian, semi-implicit dynamical core with 6th order implicit horizontal diffusion (McDonald and Haugen 1992). Its convection scheme follows Kain and Fritsch (1990) with a Sundqvist/Kessler type large scale condensation/precipitation (Rasch and Kristjánsson 1998). Large scale clouds are diagnosed using relative humidity and convective clouds using saturation deficit, convective updraft mass flux and total water content. There is A 1.5-order prognostic turbulent kinetic energy scheme for subgrid vertical diffusion (Cuxart et al. 2000). The fast single band radiation scheme is updated from Savijärvi (1990) and Sass et al. (1992).

RCO has been developed from the OCCAM version (Ocean Circulation Climate Advanced Modelling Project in Southampton) of the Bryan-Cox-Semtner primitive equation ocean model with a free surface (Webb et al. 1997). RCO is used for regional applications with open boundary conditions (Stevens, 1990), a two-equation turbulence closure, the k-epsilon model (Rodi 1980), and a sea ice model (Hibler 1979) with elastic-viscous-plastic rheology (Hunke and Dukowicz, 1997).

The model runs used to produce the data sets available at the PRUDENCE data distribution centre are described in detail in Räisänen et al. 2003 and 2004, Döscher and Meier, 2004 and Meier et al., 2004.

(k) MRI-20km-AGCM

The MRI-20km-AGCM is a global atmospheric climate model jointly developed by Meteorological Research Institute (MRI), Advanced Earth Science and Technology Organization (AESTO) and Japan Meteorological Agency (JMA). The model is based on an operational numerical weather prediction model used at JMA with some modifications in radiation and land surface processes as a climate model at MRI (Mizuta et al. 2006). The time integration was accelerated by a semi-Lagrangian three-dimensional advection scheme with the time step of 6 minutes. The model has a horizontal spectral truncation of TL959 corresponding to about a 20-km horizontal grid spacing and has 60 levels with a 0.1 hPa (altitude of about 65 km) top. TL959 means that the model has a spectral triangle truncation of spherical function at wave number 959 with linear Gaussian grid for wave-to-grid transformation. The model has 1920 grids in longitude and 960 grids in latitude for the whole globe. Prognostic Arakawa-Schubert scheme (Randall and Pan 1993) is used for deep convection. The land surface flux is based on SiB (Sellers et al. 1986). In the soil model, the phase change of water is included. The number of snow layers depends on the snow water equivalent (SWE) with a maximum of three. Snow cover also depends on the SWE. The snow albedo depends on the temperature and the snow age. The integration of the 20-km model were performed on the Earth Simulator (Habata et al. 2003; Habata et al. 2004).

The time-slice experiment was conducted as follows. The atmosphere-ocean general circulation model (AOGCM) used in the first step of the time-slice experiment is an MRI-CGCM2.3 (Yukimoto et al. 2006). The atmospheric part of this model has a horizontal spectral truncation of T42 corresponding to about a 270-km horizontal grid spacing and has 30 levels with a 0.4 hPa top. The oceanic part of this model has the horizontal grid spacing of 2.5 degrees in longitude and 2 to 0.5 (equator) degrees in latitude. The present-day climate or control simulation of the MRI-20km-AGCM for the 20-year period 1979-1998 was forced with sea surface temperature (SST) taken from 20th-Century climate simulations (20C3M) of the MRI-CGCM2.3. The future climate simulation of the MRI-20km-AGCM for the 20-year period 2080-2099 was forced with SST taken from SRES A1B simulations (Yukimoto et al. 2005) of the MRI-CGCM2.3.

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Table 1: Summary of grid configurations and parametrisations of the regional climate models