Modeling the Antarctic Surface Mass Balance with a coarse temporal resolution

Sublimation is the most important ablation term in the Antarctic Surface Mass Balance (SMB) (Agosta et al., 2019), while it is currently negligible for both Greenland and mountain glaciers (prevailing surface melt). Since simple parameterized SMB models are usually developed for Greenland and Alpine glaciers, they mostly misrepresent sublimation. To face this problem, we developed EBAL, a new parameterized Energy SMB model for Antarctica based on SEMIC (Krapp et al., 2017), which is an Energy SMB model developed for Greenland whose main innovations are a sinusoidal parameterization for the diurnal cycle to assess melt and refreezing and an albedo dependence on snow depth. EBAL was calibrated with both MAR (Kittel et al., 2022) and RACMO (Wessem et al., 2018) outputs for the period 1979-2000 and for the period 2075-2099 under the SSP5-8.5. EBAL can reproduce the statistical properties of MAR and RACMO sublimation time series and spatial distribution even if it uses a coarse time step (1 day). However, our final aim is to use EBAL for paleoclimate simulations, for which the temporal resolution of the inputs is even coarser, as often only monthly data is available. Thus, we have tested the idea of superimposing the present day-to-day variability on the MAR monthly atmospheric forcing of SSP5-8.5. Simulated SMB with EBAL forced with MAR original daily SSP5-8.5 inputs leads to a 210 Gt/yr sublimation, and to a 1425 Gt/yr melt. When forcing EBAL with monthly means only (linearly interpolated), we obtain a 113 Gt/yr sublimation and a 620 Gt/yr melt. When adding present-day variability to linearly interpolated monthly inputs, EBAL computes a 175 Gt/yr sublimation and a 1386 Gt/yr melt. Those latter numbers are very similar to those obtained when forcing with daily inputs. We propose to use this method to test EBAL for paleoclimate applications. References Agosta, C. et al., (2019). Estimation of the Antarctic surface mass balance using the regional climate model MAR (19792015) and identification of dominant processes. The Cryosphere. 13, pp. 281-296. 10.5194/tc-13-281-2019. Kittel, C. et al., (2022). Clouds drive differences in future surface melt over the Antarctic ice shelves. The Cryosphere. 16, pp. 2655-2669. 10.5194/tc-16-2655-2022. Krapp, M et al., (July 2017). SEMIC: an efficient surface energy and mass balance model applied to the Greenland ice sheet. The Cryosphere 11.4, pp. 15191535. 10.5194/tc-11-1519-2017 Wessem, J. M. et al., (Apr. 2018). Modelling the climate and surface mass balance of polar ice sheets using RACMO2 Part 2: Antarctica (19792016). The Cryosphere 12, pp. 14791498. 10.5194/tc-12-1479-2018