Model ECHAM4+OPYC3: Elborations

Participation

Spinup/Initialization

• The atmospheric model was integrated for ~20 years with prescribed AMIP SSTs and sea ice extents until quasi-equilibrium was achieved.

• The uncoupled ocean model was first spun up for ~500 years while being forced by surface climatological fluxes. The climatological wind stress and friction velocity were obtained from the stand-alone atmospheric simulation; the fluxes of heat and freshwater were derived from an observed climatology (cf. Oberhuber 1988), a bulk flux parameterization (cf. Oberhuber 1993 a,b), and additional relaxation towards the observational climatologies of AMIP SSTs and Levitus (1982) SSS. The ocean model then was spun up for an additional 500 years while being forced by daily anomalies of heat and freshwater flux derived from the stand-alone atmospheric simulation.

• The atmospheric and oceanic models were coupled and integrated for 100 years, while restoring the SST and SSS toward climatological values. Over the 100-year coupled simulation, the impact of the associated Newtonian feedbacks on the SST and SSS were gradually decreased to zero, while these feedback terms were integrated at full weight in order to derive annual-mean flux adjustments for heat and freshwater. After 100 years of coupled integration, the annual-mean flux adjustments were frozen, and then were applied throughout the subsequent 240-year control run of the coupled model.

Land Surface Processes

• The treatment of land surface processes in the MPI ECHAM4 model is the same as that in the MPI ECHAM3 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, and Zobler 1986).

• 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), but with field capacity that varies according to soil type (Patterson 1990). 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

• The sea ice model, based on that of Hibler (1979), predicts ice thickness, concentration, and momentum, as well as the thickness of an accumulating snow pack. Ice concentration and ice/snow thickness  are computed from their respective continuity equations.  Further parameterizations relate heat fluxes to changes in ice and snow thickness, lead size, and salinity due to brine ejection. The conversion from snow to ice also is parameterized.

• The thermodynamic part of the ice model predicts the vertical temperature profile, taking into account the heat capacity and conductivity of the slab and the net surface heat flux.

• A viscous-plastic rheology is chosen to parameterize the stress tensor. The governing equations are solved on an Arakawa B-grid with no-slip horizontal boundary conditions. See Oberhuber (1993a) for further details.

 

References

Bauer, H., E. Heise, J. Pfaendtner, and V. Renner, 1985: Development of an economical soil model for climate simulation. In Current Issues in Climate Research (Proceedings of the EC Climatology Programme Symposium, held 2-5 Oct. 1984, in Sophia Antipolis, France), A. Ghazi and R. Fantechi (eds.), D. Reidel, Dordrecht, 219-226.

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.

Hibler, 1979: A dynamic-thermodynamic sea ice model. J. Phys. Oceanogr., 9: 817-846.

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.

Oberhuber, J.M., 1988: An atlas based on the 'COADS' data set: The budgets of heat, buoyancy and turbulent kinetic energy at the surface of the global ocean. Max-Planck-Institut für Meteorologie, Report 15, Hamburg, Germany.

Oberhuber, J. M., 1993a: Simulation of the Atlantic circulation with a coupled sea-ice-mixed layer-isopycnical general circulation model. Part I: model description. J. Phys. Oceanogr., 23, 808-829.

Oberhuber, J.M., 1993b: Simulation of the Atlantic circulation with a coupled sea-ice-mixed layer-isopycnical general circulation model. Part II: model experiment. J. Phys. Oceanogr., 23, 830-845.

Patterson, K.A., 1990: Global distributions of total and total-available soil water-holding capacities. M.S. thesis, Department of Geography, University of Deleware, Newark, DE, 119 pp.

Roeckner, E., J.M. Oberhuber, A Bacher, M. Christoph, and I. Kirchner, 1996: ENSO variability and atmospheric response in a global coupled atmosphere-ocean GCM. Climate Dyn., 12, 737-754.

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.

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.

Zobler, L., 1986: A world soil file for global climate modeling, NASA Technical Memorandum 87802, Washington, D.C., 32 pp.
 
 

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