Model ECHAM1+LSG: Elaborations

Note: The ECHAM1 + LSG model was jointly sponsored by the Max Planck Institut für Meteorologie (MPI) and the Deutsches Klimarechenzentrum (DKRZ).
 

Participation

Spinup/Initialization

• The atmospheric model was integrated with prescribed climatological SSTs and sea ice extents derived from the AMIP data until quasi-equilibrium was achieved.

• The ocean model was integrated first with prescribed Hellerman and Rosenstein (1983) wind stresses, and was relaxed toward surface salinity data of Levitus (1982), together with a feedback to effective monthly mean surface air temperatures constructed from the COADS data set (cf. Woodruff et al. 1987). In a second stage, the diagnosed freshwater fluxes from this run, together with the same surface wind stresses and surface air temperatures then were used as external forcing (along with a mild relaxation to AMIP SSTs). In a third stage, the ocean model was integrated further with the forcings of the second stage, except for the additional application of monthly mean values of the daily forcing anomalies. The total length of the three stages was ~7,000 years.

• The atmospheric model then was integrated again to quasi-equilibrium (a 20-year run), with SSTs and sea ice extents derived from the third stage of the ocean-only run. Monthly mean flux corrections for heat, freshwater, momentum (surface wind stresses) were computed following the method of Sausen et al. 1988. The SSTs were also flux-corrected to adjust for the mean bias between the AMIP and COADS climatologies.
• The atmospheric and oceanic models then were coupled and integrated with the application of these fixed monthly mean flux corrections.

Land Surface Processes

• Soil temperature is determined after Warrilow et al. (1986) from the heat conduction in 5 layers (proceeding downward, layer thicknesses are 0.065, 0.254, 0.913, 2.902, and 5.70 m), with net surface heat fluxes as the upper boundary condition and zero heat flux as the lower boundary condition at 10 m depth.

• Snow pack temperature is also computed from the soil heat equation using heat diffusivity/capacity for ice in regions of permanent continental ice, and for bare soil where water-equivalent snow depth is <0.025 m. For snow of greater depth, the temperature of the middle of the snow pack is solved from an auxiliary heat conduction equation (cf. Bauer et al. 1985). The temperature at the upper surface is determined by extrapolation, but it is constrained not to exceed the snowmelt temperature of 0 degrees C.

• There are separate prognostic moisture budgets for snow, vegetation canopy, and soil reservoirs. Snow cover is augmented by snowfall and is depleted by sublimation and melting. Snow melts (augmenting soil moisture) if the temperatures of the snow pack and of the uppermost soil layer exceed 0 degrees C. The canopy intercepts precipitation and snow (proportional to the vegetated fraction of a grid box), which is then subject to immediate evaporation or melting.

• Soil moisture is represented as a single-layer "bucket" model (cf. Manabe 1969) with field capacity 0.20 m that is modified to account for vegetative and orographic effects. Direct evaporation of soil moisture from bare soil and from the wet vegetation canopy, as well as evapotranspiration via root uptake, are modeled. Surface runoff includes effects of subgrid-scale variations of field capacity related to the orographic variance; in addition, wherever the soil is frozen, moisture contributes to surface runoff instead of soil moisture. Deep runoff due to drainage processes also occurs independently of infiltration if the soil moisture is between 5 and 9 percent of field capacity (slow drainage), or is larger than 90 percent of field capacity (fast drainage). When the model atmosphere is coupled to a dynamical ocean, this source of freshwater is discharged at coastal points by means of a river transport model that uses local runoff as input. Cf. Dümenil and Todini (1992) and Sausen et al. (1994) for further details.

Sea Ice

• Only the thermodyamics of sea ice are represented. Ice forms when a net heat loss from the ocean would cause the SST to fall below the freezing point.  Existing ice thickens/melts in relation to the available heat of fusion when the net heat flux is upward/downward. The heat flux is calculated from a surface energy balance which includes a conductive heat flux between the ocean and sea ice, based on the assumption of a linear temperature profile.  The surface albedo of the ice is assumed to remain constant; solar penetration, brine pockets, or other internal heat capacities are not parameterized.

• Snow cover is not represented and a modification of the heat flux by leads or partial ice cover is not accounted for.  Salinity changes are associated with changes of the volume of the sea ice on the asumption of constant sea-ice salinity.

Chief Differences from Closest AMIP Model

Gravity-wave Drag

Gravity-wave drag does not include the Miller et al. (1989) modifications to the Palmer et al. (1986) parameterization, as in the AMIP model.

Convection

Instead of the Tiedtke (1989) mass-flux representation of deep convection in the AMIP model, a Kuo (1974) scheme is used. Penetrative convection is assumed to occur only in the presence of conditionally unstable layers in the vertical and large-scale net moisture convergence. In a vertical column, this total available moisture is divided between a fraction b that moistens the environment and the remainder (1-b) that contributes to the latent heating (rainfall) rate. Shallow convection is parameterized in the same way as in the AMIP model, however.

Cloud Formation

In contrast to the AMIP model, the Roeckner et al. (1991) modifications of the the prognostic cloud-formation scheme are not included.

Orography

Enhanced (envelope) orography is used instead of the mean orography of the AMIP model.

Surface Fluxes

A low-wind correction to the surface fluxes involves imposition of a minimum wind speed rather than the Miller et al. (1992) approach followed in the AMIP model. The bulk Richardson number also does not include the effects of clouds on buoyancy.

References

Cubasch, U., K. Hasselmann, H. Hock, E. Maier-Reimer, U. Mikolajewicz, B.D. Santer, and R. Sausen, 1992:  Time-dependent greenhouse warming computations with a coupled ocean-atmosphere model.  Climate Dynamics, 10, 55-69.

Dümenil, L., and E. Todini, 1992: A rainfall-runoff scheme for use in the Hamburg climate model. In Advances in Theoretical Hydrology: A Tribute to James Dooge, J.P. O'Kane (ed.), European Geophysical Society Series on Hydrological Sciences, Vol. 1, Elsevier Press, Amsterdam, 129-157.

Hellerman, S., and M. Rosenstein, 1983: Normal monthly wind stress over the world ocean with error estimates. J. Phys. Oceanogr., 13, 1093-1104.

Kuo, H.L., 1974: Further studies of the parameterization of the influence of cumulus convection on large-scale flow. J. Atmos. Sci., 31, 1232-1240.

Levitus, S., 1982: Climatological atlas of the world's oceans. NOAA Professional Paper 13, 173 pp.

Manabe, S., 1969: Climate and ocean circulation. 1. The atmospheric circulation and the hydrology of the Earth's surface. Mon. Wea. Rev., 97, 739-774.

Roeckner, E., K. Arpe, L. Bengtsson, S. Brinkop, L. Dümenil, M. Esch, E. Kirk, F. Lunkeit, M. Ponater, B. Rockel, R. Sausen, U. Schlese, S. Schubert, and M. Windelband, 1992: Simulation of present-day climate with the ECHAM model: Impact of model physics and resolution. MPI Report No. 93, ISSN 0937-1060, Max-Planck-Institut für Meteorologie, Hamburg, Germany, 171 pp.

Sausen, R., K. Barthels, and K. Hasselmann, 1988: Coupled ocean-atmosphere models with flux correction. Climate Dyn., 2, 154-163.

Sausen, R., S. Schubert, and L. Dümenil, 1994: A model of the river runoff for use in coupled atmosphere-ocean models. J. Hydrology, 155, 337-352.

von Storch, J-S., V.V. Kharin, U. Cubasch, G.C. Hegerl, D. Schriever, H. von Storch, and E. Zorita, 1997: A description of a 1260-year control integration with the coupled ECHAM1/LSG general circulation model. J. Climate, 10, 1525-1543.

Warrilow, D.A., A.B. Sangster, and A. Slingo, 1986: Modelling of land surface processes and their influence on European climate. DCTN 38, Dynamical Climatology Branch, United Kingdom Meteorological Office, Bracknell, Berkshire RG12 2SZ, UK.

Woodruff, S., R.J. Slutz, R.L. Jenne, and P. Steurer, 1987: A comprehensive ocean-atmosphere dataset. Bull. Amer. Meteor. Soc., 68, 1239-1250.
 
 

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Last update 15 May, 2002.  This page is maintained by Tom Phillips (phillips@pcmdi.llnl.gov).
 

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