Model ECHAM4+HOPE-G (ECHO-G): Elaborations
Note: The ECHAM4+HOPE-G (ECHO-G) model is sponsored by the Model and
Data Group (M&D)
at Max Planck Institut für Meteorologie (MPI).
Model ECHO-G is an entry in CMIP2+ intercomparisons.
In the model control run, greenhouse gas concentrations are as follows:
- 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
The procedure for spinup/initialization was as follows :
- The atmospheric model was integrated for 18 years with prescribed
monthly mean AMIP SSTs and sea ice extents of the period 1979-1988
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
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
by surface daily fields as obtained in the last 15 years of the
described standalone ECHAM4/T42 integration with climatological AMIP
Freshwater, heat, and momentum fluxes were applied equatorwards of the
climatological AMIP sea ice extents only. Poleward of the sea ice
near surface fields, obtained in the same ECHAM4 integration were
used. The near surface fields (surface wind, dew point temperature,
were transformed into fluxes with bulk formulas as described in Parkinson
and Washington (1979). The 15-year daily forcing data were
repeated over the spin-up period. In addition to this forcing the ocean
SSTs and SSSs were relaxed to the climatological monthly AMIP SSTs
were used during the calculation of the atmospheric forcing data,
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
are found in Legutke
- The atmospheric and oceanic models were coupled and integrated
years, while restoring SST and SSS toward climatological values. No
fluxes were applied in the climatological sea ice regions. From the
100 years of this coupled integration, annual mean freshwater and heat
fluxes were diagnosed from the relaxation terms. The fluxes were then
normalized to zero. These fields were applied in the coupled
as flux corrections (see also Marsland
et al. (2003) , Min et al. 2004,
and Min et al. 2005a, b for further
Land Surface Processes
- The treatment of land surface processes in the ECHAM4 model is
as that in the ECHAM3 model, except that the heat capacity, thermal
and field capacity for soil moisture are prescribed according to
varying values derived from Food and Agriculture Organization (FAO)
type distributions (cf. Patterson 1990,
- Soil temperature is determined after Warrilow
et al. (1986) from the heat conduction in 5 layers (proceeding
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
heat diffusivity/capacity for ice in regions of permanent continental
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
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
of 0 degrees C.
- There are separate prognostic moisture budgets for snow,
and soil reservoirs. Snow cover is augmented by snowfall and is
by sublimation and melting. Snow melts (augmenting soil moisture) if
temperatures of the snow pack and of the uppermost soil layer exceed 0
degrees C. The canopy intercepts precipitation and snow (proportional
the vegetated fraction of a grid box), which is then subject to
evaporation or melting.
- Soil moisture is represented as a single-layer
(cf. Manabe 1969), but with field
varies according to soil type (Patterson
1990). Direct evaporation of soil moisture from
soil and from the wet vegetation canopy, as well as evapotranspiration
via root uptake, are modeled. Surface runoff includes effects of
variations of field capacity related to the orographic variance; in
wherever the soil is frozen, moisture contributes to surface runoff
of soil moisture. Deep runoff due to drainage processes also occurs
of infiltration if the soil moisture is between 5 and 9 percent of
capacity (slow drainage), or is larger than 90 percent of field
(fast drainage). When the model atmosphere is coupled to a dynamical
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
ice sheets is not balanced, even for very long time scales, the ice
(of Greenland and Antarctica) serve as sinks of snow in the
model. In order to keep the heat and salt balance closed, the mass of
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.
serves to simulate the effects of melt of ice shelves by sea water and
the discharge of ice streams into the ocean.
- 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
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
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
of the sea ice and the open water (Groetzner
et al. (1996)) .The conversion from snow to ice also is
See Wolff et al. (1997)
for more details.
Bauer, H., E. Heise, J. Pfaendtner,
and V. Renner, 1985: Development of an economical soil model for
simulation. In Current Issues in Climate Research (Proceedings
the EC Climatology Programme Symposium, held 2-5 Oct. 1984, in Sophia
France), A. Ghazi and R. Fantechi (eds.), D. Reidel, Dordrecht,
Dümenil, L., and E.
1992: A rainfall-runoff scheme for use in the Hamburg climate model. In
in Theoretical Hydrology: A Tribute to James Dooge, J.P. O'Kane
European Geophysical Society Series on Hydrological Sciences, Vol. 1,
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
Dynamics, 12, 477-496.
Hibler, 1979: A dynamic-thermodynamic sea
ice model. J. Phys. Oceanogr., 9: 817-846.
Legutke, S. and E.
1999: Climatology of the HOPE-G Global Ocean General Circulation Model.
Technical report, No. 21, German Climate Computer Centre (DKRZ),
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,
Manabe, S., 1969: Climate and ocean
1. The atmospheric circulation and the hydrology of the Earth's surface.Mon.
Wea. Rev., 97, 739-774.
Marsland, S. J., M. Latif and
Legutke, 2003: Variability of the Antarctic Circumpolar Wave in a
ocean-atmosphere model. Ocean Dynamics, 53(4), 323-331.
S-K., S. Legutke, A. Hense, and
W-T. Kwon, 2004: Climatology and internal variability in a 1000-year
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.
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
S-K., S. Legutke, A. Hense, and
W-T. Kwon, 2005b: Internal variability in a 1000-year control
simulation with the coupled climate model ECHO-G. Part II:
ENSO and NAO. Tellus (in press).
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M. Washington, 1979: A large-scale numerical model of sea ice. J.
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Patterson, K.A., 1990: Global
of total and total-available soil water-holding capacities. M.S.
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Roeckner, E., K. Arpe, L.
M. Christoph, M. Claussen, L. Duemenil, M. Esch, M. Giorgetta, U.
and U. Schulzweida, 1996: The atmospheric general circulation model
Model description and simulation of present-day climate. Reports of the
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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,
Impacts of horizontal resolution on simulated climate statistics in
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A. Slingo, 1986: Modelling of land surface processes and their
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Zobler, L., 1986: A world soil file for
climate modeling, NASA Technical Memorandum 87802, Washington, D.C., 32
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