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MPI ECHAM4 (T42 L19) 1996
Model MPI ECHAM4 (T42 L19) 1996 is the fourth in a series of models developed at MPI that originally derive from cycle 17 of the European Centre for Medium-Range Weather Forecasts (ECMWF) model. The ECHAM4 model's immediate predecessor is AMIP baseline model MPI ECHAM3 (T42 L19) 1992. The ECHAM4 model differs most sharply from its predecessor in its treatment of transport and diffusion, of chemistry and radiation, and of the planetary boundary layer (PBL). The parameterizatons of convection, cloud formation, and land surface characteristics also have been modified.
Much of the literature on the baseline model remains relevant. Overall documentation of the ECHAM4 model is provided by Roeckner et al. (1996)[52]. Details of the new semi-Lagrangian transport scheme are given by Williamson and Rasch (1994)[57] and Hack et al. (1993)[58]. The radiation scheme is documented by Fouquart and Bonnel (1980)[63], Morcrette (1991)[64], Giorgetta and Wild (1995)[68], and Rockel et al. (1991)[17]. The reformulation of the PBL is after Brinkop and Roeckner (1995)[59]. Modification of the convection scheme follows Nordeng (1996)[72], and changes in cloud formation are after Sundqvist et al. (1989)[73] and Slingo (1987)[74]. The new land surface characteristics are described by Claussen et al. (1994)[76], Patterson (1990)[79], and Zobler (1986)[80]. Validation of various aspects of the ECHAM4 model is provided by Chen and Roeckner (1996)[53], Chen et al. (1996)[54], Lohmann et al. (1995)[55], and Wild et al. (1996)[56].
The horizontal representation is as in the baseline model, except that horizontal advection of water vapor and cloud water are treated by the shape-preserving semi-Lagrangian transport (SLT) scheme of Williamson and Rasch (1994)[57], with further details supplied by Hack et al. (1993)[58]. Because the SLT scheme is not inherently conservative, mass conservation is enforced at every time step through a variational adjustment of the advected variable field which weights the amplitude of the adjustment in proportion to the advection tendencies and the field itself.
The vertical representation is as in the baseline model, except that vertical advection of positive definite quantities is treated by the SLT scheme.
The AMIP simulation was run on a Cray C90 computer using 4 processors in the UNICOS environment.
About 3.5 minutes of Cray C90 computation time per simulated day.
Smoothing and filling procedures are the same as for the baseline model, except that filling of spurious negative atmospheric moisture values is obviated by the use of the SLT scheme.
Trace constituents including methane, nitrous oxide, and 16 different CFC's are added to the chemistry of the baseline model.
The radiation scheme of the baseline model is replaced. Instead, shortwave radiation is treated by the two-stream method of Fouquart and Bonnell (1980)[63], and longwave radiation by the method of Morcrette (1991)[64]. In addition, further changes are made in the treatment of other gaseous absorbers, continuum absorption by water vapor, and cloud-radiative interactions.
The Tiedtke (1989)[22] convection scheme of the baseline model still is utilized, but with modifications introduced after Nordeng (1996)[72]. Organized entrainment depends on local buoyancy and organized detrainment is derived for a spectrum of clouds. The detrained cloud water, as well as that present in shallow non-precipitating cumulus clouds, is made a source term in the stratiform cloud water transport equation (see Cloud Formation), and buoyancy in updrafts is controlled by the water loading. The closure assumption of the baseline model also is modified: cloud-base mass flux is linked to convective instability instead of moisture convergence.
The prognostic cloud-formation scheme of the baseline model is modified. Fractional cloudiness is determined as a nonlinear function of relative humidity excess above a threshold value, following Sundqvist et al. (1989)[73]. Threshold values decrease exponentially with height (between 99% at the surface to 60% in the upper troposphere) after Xu and Krueger (1991)[28]. The formation of marine stratocumulus clouds is linked to the existence of a low-level inversion following Slingo (1987)[74]. Cloud water from convective detrainment as well as that contained in non-precipitating shallow cumulus clouds (see Convection) is a source term for prognostic stratiform cloud formation . The transport and turbulent diffusion of cloud water also are treated by the SLT and TKE schemes (see Horizontal Representation, Diffusion, and Planetary Boundary Layer). See also Radiation for treatment of cloud optical properties.
The baseline model's PBL representation is replaced by a higher-order closure scheme that computes the turbulent transfer of momentum, heat, moisture, and cloud water (cf. Brinkop and Roeckner (1995)[59]). The eddy diffusion coefficients are calculated as functions of the square root of the prognostic turbulence kinetic energy (TKE) and a mixing length which is a function of both stability and height. The TKE is calculated from rate equations for the respective variables which include buoyancy, dissipation, wind shear, and vertical diffusion terms, but which neglect TKE advection. The buoyancy flux is formulated in terms of cloud-conservative variables (see Cloud Formation in the baseline model). The boundary condition is expressed as a function of friction velocity and convective length scale. The asymptotic value of the mixing length (cf. Blackadar 1962[60]) is 300 m within the PBL, following Holtslag and Boville 1993[61]). See also Diffusion and Surface Fluxes.
Vegetation parameters, albedos, and roughness lengths differ from those of the baseline model:
As in the baseline model, the turbulent surface fluxes are formulated as functions of roughness length and moist bulk Richardson number, but with decreased ocean roughness lengths used for calculating the heat and moisture fluxes (see Surface Characteristics).
The treatment of land surface processes is the same as in the baseline model, except that the heat capacity, thermal conductivity, and field capacity for soil moisture are prescribed according to geographically varying values derived from Food and Agriculture Organization (FAO) soil type distributions (cf. Patterson (1990)[79], and Zobler (1986)[80]).
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