Sample collection and field studies of sea ice take place under harsh conditions which, combined with the logistical difficulties and high cost of voyages to the polar regions, limits the abilities of researchers to determine its properties. Observations of laboratory-grown sea ice can help quantify important sea-ice properties and incorporate them into numerical models. The growth of laboratory sea ice requires experimental set-ups that consider the complexity of sea-ice growth. Regulation and monitoring of environmental variables allow for growth and melt conditions to be controlled, manipulated and reproduced. Facilities thus vary widely because of differing research objectives. This paper presents a summary of some of the published sea-ice laboratories that study the physical properties of sea ice and an overview of their major design considerations, such as tank size, freezing method and instrumentation. It also discusses how these design considerations were implemented in the set-up of the new sea-ice growth laboratory at the Marine and Antarctic Research for Innovation and Sustainability. This paper should guide others in designing their facilities as well as in their understanding of other facilities for results comparison.

A volume-area scaling relation is commonly used to estimate glacier volume or its future changes on a global scale. The presence of an insulating supraglacial debris cover alters the mass-balance profile of a glacier, potentially modifying the scaling relation. Here, the nature of scaling relations for extensively debris-covered glaciers is investigated. Theoretical arguments suggest that the volume-area scaling exponent for these glaciers is ~7% smaller than that for clean glaciers. This is consistent with the results from flowline-model simulations of idealised glaciers, and the available data from the Himalaya. The best-fit scale factor for debris-covered Himalayan glaciers is ~60% larger compared to that for the clean ones, implying a significantly larger stored ice volume in a debris-covered glacier compared to a clean one having the same area. These results may help improve scaling-based estimates of glacier volume and future glacier changes in regions where debris-covered glaciers are abundant.

We explore spatial aliasing of non-Gaussian distributions of sea-ice thickness. Using a heuristic model and >1000 measurements, we show how different instrument footprint sizes and shapes can cluster thickness distributions into artificial modes, thereby distorting frequency distribution, making it difficult to compare and communicate information across spatial scales. This problem has not been dealt with systematically in sea ice until now, largely because it appears to incur no significant change in integrated thickness which often serves as a volume proxy. Concomitantly, demands are increasing for thickness distribution as a resource for modeling, monitoring and forecasting air–sea fluxes and growing human infrastructure needs in a changing polar environment. New demands include the characterization of uncertainties both regionally and seasonally for spaceborne, airborne, in situ and underwater measurements. To serve these growing needs, we quantify the impact of spatial aliasing by computing resolution error (Er) over a range of horizontal scales (x) from 5 to 500 m. Results are summarized through a power law (Er= bxm) with distinct exponents (m) from 0.3 to 0.5 using example mathematical functions including Gaussian, inverse linear and running mean filters. Recommendations and visualizations are provided to encourage discussion, new data acquisitions, analysis methods and metadata formats.