Model ECHAM4+HOPE-G (ECHO-G): Elaborations

Participation

Greenhouse Gas Concentrations

• CO₂: 353 ppmv
• CH₄: 1.72 ppmv
• N₂O: 310ppbv
• CFC11: 280 pptv
• CFC12: 484 pptv
• HCFC113: 60 pptv
• CFC114: 15 pptv
• CFC115: 5 pptv
• HCFC22: 122 pptv
• CCL4: 146 pptv
  

Spinup/Initialization

• The atmospheric model was integrated for 18 years with prescribed climatological monthly mean AMIP SSTs and sea ice extents of the period 1979-1988 until quasi-equilibrium was achieved. The climatology of ECHAM4 obtained with a T42 resolution and AMIP SSTs is described in Roeckner et al. (1996). ECHO-G uses a T30 grid for the atmosphere. The climatology in this resolution is contrasted with that of the T42 resolution in Stendel and Roeckner (1998).

• The uncoupled ocean model was spun up for 2034 years while being forced by surface daily fields as obtained in the last 15 years of the above  described standalone ECHAM4/T42 integration with climatological AMIP SSTs. Freshwater, heat, and momentum fluxes were applied equatorwards of the climatological AMIP sea ice extents only. Poleward of the sea ice extents, near surface fields,  obtained in the same ECHAM4 integration were used. The near surface fields (surface wind, dew point temperature, 2m-temperature) were transformed into fluxes with bulk formulas as described in Parkinson and Washington (1979). The 15-year daily forcing data were cyclically repeated over the spin-up period. In addition to this forcing the ocean SSTs and SSSs were relaxed to the climatological monthly AMIP SSTs which were used during the calculation of the atmospheric forcing data, assuming a heat flux of 40 W/(m**2K).  SSSs were relaxed to the annual Levitus et al. (1994) climatology on the same time scale (30 days). More details are found in Legutke and Maier-Reimer (1999).

• The atmospheric and oceanic models were coupled and integrated for 155 years, while restoring SST and SSS toward climatological values. No relaxation fluxes were applied in the climatological sea ice regions. From the last 100 years of this coupled integration, annual mean freshwater and heat fluxes were diagnosed from the relaxation terms. The fluxes were then globally normalized to zero. These fields were applied in the coupled experiments as flux corrections (see also  Marsland et al. (2003) , Min et al. 2004, and Min et al. 2005a, b for further details).

Land Surface Processes

• The treatment of land surface processes in the ECHAM4 model is the same as that in the 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.

Since surface melt and accumulation of snow on continental ice sheets is not balanced, even for very long time scales, the ice sheets (of Greenland and Antarctica)  serve as sinks of snow in the coupled model. In order to keep the heat and salt balance closed, the mass of the ice sheets is kept constant by routing the surplus of the mass balance into the ocean grid cells aroubd the coast. In addition a corresponding flux of latent heat of fusion is transfered into the ocean as well. This serves to simulate the effects of melt of ice shelves by sea water and the discharge of ice streams into the ocean.

Sea Ice

• The dynamic part of the sea ice model is based on that of Hibler (1979), recoded on the ocean model grid (Arakawa-E). It predicts ice thickness and concentration, snow depth, ice/scnow cover momentum. The snow pack is accumulating on the ice according to the solid freshwater fluxes given to the ocean.  Surface melt of snow or ice and bottom melt or ablation of ice is calculated from the residual surface fluxes on the snow/ice layer and the conductive fluxes through the snow/ice cover, which are both calculated in the atmosphere.  Each ocean grid cell of the atmosphere grid can be partially covered by sea ice. All fluxes on these cells are calculated twice with the respective surface conditions of the sea ice and the open water (Groetzner et al. (1996)) .The conversion from snow to ice also is parameterized. See Wolff et al. (1997) for more 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.

Groetzner, A., R. Sausen, and M. Clausen 1996: The impact of sub-grid scale sea-ice imhomogenities on the perfomance of the atmospheric general circulation model ECHAM3,.Climate Dynamics, 12, 477-496.

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

Legutke, S. and E. Maier-Reimer, 1999: Climatology of the HOPE-G Global Ocean General Circulation Model. Technical report, No. 21, German Climate Computer Centre (DKRZ), Hamburg, 90 pp (http://www.mad.zmaw.de/Pingo/repdl.html).

Levitus, S., R. Burgett, and T. P. Boyer, 1994: World Ocean Atlas. 3, Salinity and Vol. 4, Temperature. NOAA Atlas NESDIS 3/4, U. S. Government Printing Office, Washington, DC.

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.

Marsland, S. J., M. Latif and S. Legutke, 2003: Variability of the Antarctic Circumpolar Wave in a coupled ocean-atmosphere model. Ocean Dynamics, 53(4), 323-331.

Min, S-K., S. Legutke, A. Hense, and W-T. Kwon, 2004: Climatology and internal variability in a 1000-year control simulation with the coupled climate model ECHO-G.  M&D Technical Report No. 2, Modelle & Daten, Hamburg, Germany, 67 pp.   Accessible online at http://mad.zmaw.de/Pingo/reports/TeReport_Web02.pdf. 

Min, S-K., S. Legutke, A. Hense, and W-T. Kwon, 2005a: Internal variability in a 1000-year control simulation with the coupled climate model ECHO-G.  Part I:  near surface temperature, precipitation, and mean sea level pressure.  Tellus (in press).

Parkinson, C. L. and W. M. Washington, 1979: A large-scale numerical model of sea ice. J. Geophys. Res., 84(C1), 311-337.

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., K. Arpe, L. Bengtsson, M. Christoph, M. Claussen, L. Duemenil, M. Esch, M. Giorgetta, U. Schlese, and U. Schulzweida, 1996: The atmospheric general circulation model ECHAM-4: Model description and simulation of present-day climate. Reports of the Max-Planck-Institute, Hamburg, No. 218, 90 pp.

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

Stendel, M. and E. Roeckner, 1998: Impacts of horizontal resolution on simulated climate statistics in ECHAM4. Reports of the Max-Planck-Institute, Hamburg, No. 253, 57 pp (http://www.mpimet.mpg.de/dynindex.php?s=http://mpi-web.dkrz.de/de/web/science/a_reports.php#).

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.

Wolff, J.-O., E. Maier-Reimer, and S. Legutke, 1997: The Hamburg Ocean Primitive Equation Model, Technical report, No. 13, German Climate Computer Center (DKRZ), Hamburg, 98 pp (http://www.mad.zmaw.de/Pingo/repdl.html).

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

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