Earlier versions

ECBILT-FOM version 1
The ECBILT atmosphere model is a T21 global three-level quasi geostrophic model with simple parametrizations for the diabetic processes. The dynamical component of the atmosphere model was developed by Molteni (Marshall and Molteni, 1993). The phyiscal parametrizations are similar as in Held and Suarez (1978). As an extension to the quasi-geostrophic equations, an estimate of the neglected ageostrophic terms in the vorticity and thermodynamic equations in included as a time and space varying forcing. This forcing is computed from the diagnostically derived motion field.
The atmosphere model is coupled to a simple coarse resolution GFDL type ocean model and a thermodynamic sea-ice model. The resolution is about 5.6 times 5.6 degrees, it has 12 unevely spaced levels in the vertical and has a flat bottom. That's where the name comes from: Flat Ocean bottom Model. The timestep for the atmosheric part is and the sea-ice model is four hours, for the ocean it is one day. The models are synchronously coupled.

ECBILT-CLIO version 2
The ECBILT model used in this coupled model is slightly changes compared to the previous one; the radiative flux computations are substituted for a linearization of the ECHAM4 radiation code (van Dorland et al., 2000). The CLIO model comprises a primitive equation, free-surface ocean general circulation model coupled to a thermodynamic-dynamic sea ice model. The ocean component includes a relatively sophifiticated parametrization of vertical mixing in the ocean as well as a parametrization of dense water flow down topographic features. A three-layer model simulates the changes of snow and ice-thickness in response to surface and bottom heat fluxes, taking the sensible and latent heat storage in the snow-ice system into account. In the computation of ice-dynamics, sea-ice is considered to bahave as a viscous-plastic continuum. The resolution of CLIO is 3 degrees in latitude and longitude and there are 20 unevely spaced levels in the ocean.
The ocean and atmosphere models are coupled using the OASIS software. Although the two models have different grids, every atmospheric surface grid cell can contain an arbitrary fraction of open ocean (or leads), sea-ice and land surface. It is therefore possible to achieve an exact matching of the area occupied by these three types of surface in the two models in order to conserve heat and mass exchanged at the interface. There is no local flux correction in ECBILT-CLIO. However, the model systematically overestimates the precipitation over the Atlantic and Arctic oceans. In consequence, the precipitation over the Atlantic and Arctic basins are artificially reduced with 10% and 50% respectively and homogeneously redistributed over the North Pacific where precipitation was found to be too low.

Improvements of ECBILT/CLIO version 3

Sea-ice temperature
Pedro de Vries(KNMI) has looked into the stability problem of the ice model. Very large drops of ice temperature at the surface were possible because sensible heat fluxes could become very large. This is so, because the drag coefficient has a dynamic range of a factor 5 and sometimes strong winds are present giving another factor of 5 increase in dynamic range. In the old version, the ice temperature is computed implicitly with respect to conductive and radiative contributions, but not with respect to the sensible heat flux. The latter has been changed now. The parameter a of h_sensible=a*(T_ice-T_air) is now passed on to the subroutine that calculates the ice temperature. The possible changes in in the ice temperature are now especially reduced for those cases that a is a factor 5 to 25 larger than the mean value. Also the order of time stepping the ocean model and the atmospheric model was reversed. For a 500-year LGM run the ice temperature never(!) dropped below T=150 K.

Long Wave radiation
Michiel Schaeffer (RIVM) has compared the LWR-parameterization scheme in ECBILT with the one of the ECHAM4 model which is more comprehensive. The aim was to find out how the implemented LWR scheme performs under LGM forcing conditions.

Clear sky fluxes:
For present-day conditions the differences between the two models are very small (order of 1 percent) for outgoing LWR. Flux patterns and variability are very similar. For LGM conditions the larger differences (order of 4 percent, ECBILT-ECHAM4=+5 W/m^2) were present in the polar regions (abs(lat)>70). For incoming LWR at the surface larger differences were also found in the polar regions. Present-day: order of 1 to 2 percent. LGM conditions: 25 to 50 percent, ECBILT-ECHAM4=+20 to 40 W/m^2. The behavior in the polar regions is probably due to the fact that ECBILT can give zero moisture there under LGM conditions. In this case, the implemented LWR linearization may not be optimal.

Cloud forcing included:
The deviations for outgoing LWR are very similar for both present-day conditions as well as for LGM conditions: ECBILT-ECHAM4=-20 to -40 W/m^2 in tropical regions. This is due to ECBILT employing a single parameter for cloud coverage. Earlier studies have shown that using a scheme with three different cloud types significantly reduces the observed differences. However, no different climate response was observed, since errors in the LWR scheme and SWR scheme turned out to compensate one another. For efficiency, therefore, ECBILT makes use of one average cloud parameter. For incoming LWR at the surface differences of the same order were obtained for present-day conditions and LGM conditions.

Conclusion:
Under LGM conditions the LWR parameterization used in ECBILT behaves comparably well as under present-day conditions. The LWR scheme distinguishes 27 different geographical areas. The Greenland one (k=27) is defined for ice caps at high elevation (about 1700m). Optionally, the same k=27 parameterization can be used for the LGM icecaps in Northern America and Arctic regions.

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