Version 1 of a sea ice module for the physics-based, detailed, multi-layer SNOWPACK model

• Published in: Geoscientific Model Development
• Main Authors: Wever, Nander, Rossmann, Leonard, Maaß, Nina, Leonard, Katherine C., Kaleschke, Lars, Nicolaus, Marcel, Lehning, Michael
• Format: Article in Journal/Newspaper
• Language: unknown
• Published: 2020
• Subjects: Antarc*; Antarctica; Sea ice; Weddell Sea
• Online Access: https://epic.awi.de/id/eprint/53633/; https://epic.awi.de/id/eprint/53633/1/gmd-13-99-2020.pdf; https://hdl.handle.net/10013/epic.f4b4ac83-7276-4111-be99-860172d5e195

Sea ice is an important component of the global climate system. The presence of a snowpack covering sea ice can strongly modify the thermodynamic behavior of the sea ice, due to the low thermal conductivity and high albedo of snow. The snowpack can be stratified and change properties (density, water content, grain size and shape) throughout the seasons. Melting snow provides freshwater which can form melt ponds or cause flushing of salt out of the underlying sea ice, while flooding of the snow layer by saline ocean water can strongly impact both the ice mass balance and the freezing point of the snow. To capture the complex dynamics from the snowpack, we introduce modifications to the physics-based, multi-layer SNOWPACK model to simulate the snow-sea-ice system. Adaptations to the model thermodynamics and a description of water and salt transport through the snow-sea-ice system by coupling the transport equation to the Richards equation were added. These modifications allow the snow microstructure descriptions developed in the SNOWPACK model to be applied to sea ice conditions as well. Here, we drive the model with data from snow and ice mass-balance buoys installed in the Weddell Sea in Antarctica. The model is able to simulate the temporal evolution of snow density, grain size and shape, and snow wetness. The model simulations show abundant depth hoar layers and melt layers, as well as superimposed ice formation due to flooding and percolation. Gravity drainage of dense brine is underestimated as convective processes are so far neglected. Furthermore, with increasing model complexity, detailed forcing data for the simulations are required, which are difficult to acquire due to limited observations in polar regions.