Although simpler than a sophisticated three-dimensional GCM, the MIT model's climate input coupled to the snowpack model does a respectable job at capturing the known features of the melting and ablation which occur on the Greenland and Antarctic ice sheets. More measurements of the radiative fluxes, temperature and ablation would however be necessary to affirm this with certainty. The estimate of 162 . 1012 kg a-1 of runoff produced with the MIT / snowpack model combination for Greenland does underestimate the actual ablation because of the absence of runoff along the Northern coast of the ice sheet. A significant portion of the meltwater refreezes within the snow cover to form superimposed ice layers in both the MIT / snowpack and ECHAM / snowpack model combinations, yet the fraction of meltwater which ends up as runoff is significantly different in both cases. This highlights the advantage of an explicit calculation of the liquid water content of the snow cover and of changes of phase of water over a parameterization. The degree-day model in the formulation used for this study provides an adequate first approach to modeling the mass balance of the ice sheets. One must however be excessively careful in using temperature based parameterizations such as the degree-day or linear models in regions other than those for which they were calibrated and for climatic forcings different from the current state. This will become clear in climate change simulations (Bugnion (1999)). The linear model furthermore fails to recognize the non-linear dependence of melting and runoff on the surface albedo, and the role of refreezing.
The summer temperature pattern predicted by the ECHAM model for the Greenland ice sheet is not sufficiently accurate to give reasonable estimates of runoff. The failure of the ECHAM model to improve the estimates provided by the MIT model is particularly disappointing in view of the extremely high resolution of the simulation which served as input, a resolution which could not be sustained in a transient climate change integration. This does however confirm that regional predictions from GCMs cannot yet be fully trusted. The high resolution of the ECHAM model does however allow it to improve the accuracy of the pattern and amount of snow accumulation on both ice sheets, the excessive accumulation over Antarctica being the major shortcoming of the MIT model. Since that climate model is likely to continue overestimating precipitation in integrations carried out over the 21st century, this is a problem which could be particularly detrimental to the reliability of estimates of future changes in the mass balance of that ice sheet and their effect on the level of the oceans.
These calculations were designed to gain confidence in the ability of the coupled climate / snowpack model to capture the current state of the mass balance of the ice sheets before proceeding with the calculation of the changes which can be expected to occur in the coming century and their effect on the sea-level. The simple MIT climate model coupled to a sophisticated snowcover model seems to give an accurate prediction of the melting and runoff on the Greenland ice sheet, probably the variable which is the most difficult to estimate. A subsequent paper Bugnion (1999) looks into changes in mass balance of Greenland and Antarctica over the coming century for a range of climate change scenarios sufficiently broad to capture the major uncertainties in the rate of emissions of greenhouse gases and in key parameters in the climate model. This allows to calculate a set of projections of the changes in sea-level which follow from these modifications in the mass balance.
Acknowledgements
I am grateful to the ETH Zürich (Prof. A. Ohmura, Dr. H. Gilgen, Dr. M. Wild, ) for providing the ECHAM 4 and GEBA sdata. Insightful coments on earlier drafts were provided by G. Roe, P. Stone and M. Wild. This research was supported by the Alliance for Global Sustainability, the M.I.T. Joint Program on the the Science and Policy of Global Change and NASA Grant NAG 5-7204 as part of the NASA GISS Interdisciplinary EOS Investigation.