Snow in the Changing Sea-ice Systems
This paper describes fundamental characteristics of snow in the Earth system, including reasons for contrasts between the Arctic and Antarctic, and feedbacks with the changing sea ice systems. It elucidates key challenges for observations and modeling snow processes and provides recommendations for overcoming these challenges to better understand, observe and model the Earth system.
Process-oriented observations are critical to better understand snow on sea ice and its feedbacks in the climate system, expose inaccurate or missing mechanisms that drive the evolution of snow conditions in climate models, and inform model parameterization development, ultimately leading to more robust predictive capability. Improving the coverage and quality of large-scale snow observations will aid in designing standard error metrics to evaluate the key snow state variables (depth, albedo, density) for current climate conditions.
As Earth’s most reflective, insulative natural material, snow is critical to the sea-ice and climate systems. Snow modulates not only the critical role of sea ice in the global climate system but also the sensitivity and response of sea ice to anthropogenic warming. Over the last half century, a decrease in spring snow depth in the western Arctic has been observed and simulated in models. The delayed onset of sea-ice formation in autumn allows less snow to be captured on the ice, which then melts more quickly in the spring, exposing the ice to solar radiation and further ice loss. In the Antarctic, frequent storms and strong winds contribute to highly dynamic ice and snow packs. Observations have revealed key differences in processes and conditions that distinguish the Antarctic snow-sea ice system from that in the Arctic, including more snow-ice formation, a greater proportion of snow lost to leads, more thaw and more rain-on-snow events. For improving predictions of polar climate change and its effects, we recommend measuring and monitoring snow at the basin scale using autonomous aircraft and multi-sensor and/or merged satellite products, and taking advantage of targeted, coordinated observing opportunities, including non-scientific visits to high-latitude regions using standardized sampling protocols.