The Antarctic Surface Mass Balance (SMB, i.e. the snow accumulation from which we subtract ablation by sublimation, run-off or erosion) is a major yet badly known contribution to changes in the present-day sea level. Water storage by snow accumulation on the Antarctic continent is expected to increase in the 21st century, which would moderate the rise in sea level and impact the ice dynamic response of the ice sheet. Three-quarters of the Antarctic SMB are concentrated below 2000 m above sea level whereas this area represents only 40% of the grounded ice sheet area. Orographic precipitation is a major contributor to snow accumulation in this region, which is why a better estimation of this term is important. The representation of this process by models depends to a great extent on the resolution of the model, since precipitation amounts depend on the ice sheet slopes. Sublimation and snowmelt also depend on elevation, and although they are presently minor contributors to the Antarctic SMB, their role is expected to become more important in the coming centuries. Global and regional atmospheric climate models are unable to achieve a 40-km resolution over Antarctica at a century time scale, due to their computing cost. At this resolution, the Antarctic coastal area is still badly represented. This is why we developed the downscaling model SMHiL (Surface mass balance high-resolution downscaling) to estimate the Antarctic SMB components at a high resolution (~15 km) from large-scale atmospheric forcings. We computed the impact of the high-resolution topography on orographic precipitation amounts and the boundary layer processes that lead to sublimation, melting and refreezing. SMHiL has been validated for the present period with a dataset composed of more than 2700 quality-controlled observations. However, very few of these observations are representative of the Antarctic coastal area. In this context, we show that the GLACIOCLIM-SAMBA stake lines located on the ice sheet coast-to-plateau area is an appropriate reference to evaluate model performance. Finally, we used SMHiL to estimate the SMB changes during the 21st and 22nd centuries, by downscaling the atmospheric global climate model LMDZ4. The high-resolution SMB is significantly different from the SMB given by LMDZ4 and is closer to the observed one for the present period. Our results suggest that previous studies using the LMDZ4 models underestimated the future increase in SMB in Antarctica by about 30%. Future changes in the Antarctic SMB at low elevations will result from the conflict between higher snow accumulation and runoff. The downscaling model is a powerful tool that can be applied to climate models for a better assessment of a future rise in sea level.
