Basal melt of ice shelves is not only an important part of Antarctica's ice sheet mass budget, but it is also the origin of platelet ice, one of the most distinctive types of sea ice. In many coastal Antarctic regions, ice crystals form and grow in supercooled plumes of Ice Shelf Water. They usually rise towards the surface, becoming trapped under an ice shelf as marine ice or forming a semi-consolidated layer, known as the sub-ice platelet layer, below an overlying sea ice cover. In the latter, sea ice growth consolidates loose crystals to form incorporated platelet ice. These phenomena have numerous and profound impacts on the physical properties, biological processes and biogeochemical cycles associated with Antarctic fast ice: platelet ice contributes to sea ice mass balance and may indicate the extent of ice-shelf basal melting. It can also host a highly productive and uniquely adapted ecosystem. This paper clarifies the terminology and reviews platelet ice formation, observational methods as well as the geographical and seasonal occurrence of this ice type. The physical properties and ecological implications are presented in a way understandable for physicists and biologists alike, thereby providing the background for much needed interdisciplinary research on this topic.

Sea ice, which forms in polar and nonpolar areas, transmits light to ice-associated (sympagic) algal communities. To noninvasively study the distribution of sea-ice algae, empirical relations to estimate its biomass from under-ice hyperspectral irradiance have been developed in the Arctic and Antarctica but lack for nonpolar regions. This study examines relationships between normalised difference indices (NDI) calculated from hyperspectral transmittance and sympagic algal biomass in the nonpolar Saroma-ko Lagoon. We analysed physico-biogeochemical properties of snow and land-fast sea ice supporting 27 paired bio-optical measurements along three transects covering an area of over 250 m × 250 m in February 2019. Snow depth (0.08 ± 0.01 m) and ice-bottom brine volume fraction (0.21 ± 0.02) showed low (0.06) and high (0.58) correlations with sea-ice core bottom section chlorophyll a (Chl. a), respectively. Spatial analyses unveiled the patch size of sea-ice Chl. a to be ~65 m, which is in the same range reported from previous studies. A selected NDI (669, 596 nm) explained 63% of algal biomass variability. This reflects the bio-optical properties and environmental conditions of the lagoon that favour the wavelength pair in the orange/red part of the spectrum and suggests the necessity of a specific bio-optical relationship for Saroma-ko Lagoon.

Absorption and fluorescence of chromophoric dissolved organic matter (CDOM) in sea ice and surface waters in the southern Sea of Okhotsk was examined. Sea-water CDOM had featureless absorption increasing exponentially with shorter wavelengths. Sea ice showed distinct absorption peaks in the ultraviolet, especially in younger ice. Older first-year sea ice had relatively flat absorption spectra in the ultraviolet range. Parallel factor analysis (PARAFAC) identified five fluorescent CDOM components, two humic-like and three protein-like. Sea water was largely governed by humic-like fluorescence. In sea ice, protein-like fluorescence was found in considerable excess relative to sea water. The accumulation of protein-like CDOM fluorescence in sea ice is likely a result of biological activity within the ice. Nevertheless, sea ice does not contribute excess CDOM during melt, but the material released will be of different composition than that present in the underlying waters. Thus, at least transiently, the CDOM introduced during sea-ice melt might provide a more labile source of fresher protein-like DOM to surface waters in the southern Sea of Okhotsk.

The spectral dependence of natural light transmittance on ice algae concentration and snow depth in Arctic sea ice provides the potential to study the changing bottom-ice ecosystem using optical relationships. In this paper, we consider the use of functional data analysis techniques to describe such relationships. Specifically, we created a functional regression model describing spectral optical depth as a function of chlorophyll a concentration, snow depth and ice thickness. Measurements of the aforementioned covariates and surface and transmitted spectral irradiance were collected on landfast first-year sea ice in the High Arctic near Resolute Passage, Canada, during the spring of 2011 and used as model input. The derived model explains 75–84.5% of the variation in the observed spectral optical depth curves. No prior assumptions of snow/sea-ice optical properties are required in the application of this technique, as the model estimates the attenuation coefficients of each covariate using only the measurements mentioned above. The quality and simplicity of the model highlight the potential of functional data analysis to study the Arctic marine ecosystem.