Surface Mass Balance, Sublimation and Snow Deposition in the Extreme Environments of the Three Poles

The polar ice caps experience significant melt and their future fate is highly uncertain yet very important to forecast sea level rise. Precipitation quantities are not well constrained over the ice sheets and the process such as sublimation of precipitation in katabatic winds or of drifting and blowing snow are not quantitatively understood. CRYOS has set-up a first set of all-year autonomous measurement stations at several locations on the East Antarctic ice sheet to measure meteorology, snow deposition and – for the first time – a snow transport rate using the Japanese SPC sensor. These local measurements serve as validation points for modelling sublimation and the complete surface mass balance using advanced model systems such as Alpine3D (Lehning, Volksch et al. 2006, Zwaaftink, Lowe et al. 2011), which have been co-developed between SLF Davos and CRYOS or community models such as the Weather and Forecasting Model (WRF). To this end, we are currently coupling the in-house snow model SNOWPACK (Lehning, Bartelt et al. 1999, Zwaaftink, Cagnati et al. 2013) to WRF and expect a massive improvement in surface mass balance estimates from this coupling.

Figure 1 – all-year autonomous measurement stations at several locations on the East Antarctic ice sheet to measure meteorology, snow deposition and snow transport rate

The grand question of snow and ice dynamics in the global climate system is complemented by basic research on flow – particle interactions, which CRYOS conducts in collaboration with SLF Davos e.g. in the cold wind tunnel (Walter, Horender et al. 2014) but also by developing a full physical understanding of snow transport (Comola and Lehning 2017), snow deposition mechanisms (Sommer, Wever et al. 2018) and snow sublimation (Sharma, Comola et al. 2018). The basic research on small-scale snow processes forms the basis for model development at the larger scale.

Figure 2 – Cellular automata based modelling of interaction between drifting snow and surface dynamics  (Sharma, Comola et al. 2018)


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