The Arctic sea-ice-scape is rapidly transforming. Increasing light penetration will initiate earlier seasonal primary production. This earlier growing season may be accompanied by an increase in ice algae and phytoplankton biomass, augmenting the emission of dimethylsulfide and capture of carbon dioxide. Secondary production may also increase on the shelves, although the loss of sea ice exacerbates the demise of sea-ice fauna, endemic fish and megafauna. Sea-ice loss may also deliver more methane to the atmosphere, but warmer ice may release fewer halogens, resulting in fewer ozone depletion events. The net changes in carbon drawdown are still highly uncertain. Despite large uncertainties in these assessments, we expect disruptive changes that warrant intensified long-term observations and modelling efforts.

Fast ice is an important component of Antarctic coastal marine ecosystems, providing a prolific habitat for ice algal communities. This work examines the relationships between normalized difference indices (NDI) calculated from under‐ice radiance measurements and sea ice algal biomass and snow thickness for Antarctic fast ice. While this technique has been calibrated to assess biomass in Arctic fast ice and pack ice, as well as Antarctic pack ice, relationships are currently lacking for Antarctic fast ice characterized by bottom ice algae communities with high algal biomass. We analyze measurements along transects at two contrasting Antarctic fast ice sites in terms of platelet ice presence: near and distant from an ice shelf, i.e., in McMurdo Sound and off Davis Station, respectively. Snow and ice thickness, and ice salinity and temperature measurements support our paired in situ optical and biological measurements. Analyses show that NDI wavelength pairs near the first chlorophyll a (chl a) absorption peak (≈440 nm) explain up to 70% of the total variability in algal biomass. Eighty‐eight percent of snow thickness variability is explained using an NDI with a wavelength pair of 648 and 567 nm. Accounting for pigment packaging effects by including the ratio of chl a‐specific absorption coefficients improved the NDI‐based algal biomass estimation only slightly. Our new observation‐based algorithms can be used to estimate Antarctic fast ice algal biomass and snow thickness noninvasively, for example, by using moored sensors (time series) or mapping their spatial distributions using underwater vehicles.

Q1,Q2 We examine energetic charged particle diffusion perpendicular to a mean magnetic field B 0 due to turbulent fluctuations in a plasma, relaxing the common assumption of axisymmetry around B 0 and varying the ratio of two fluctuation components, a slab component with parallel wavenumbers and a two-dimensional (2D) component with perpendicular wavenumbers. We perform computer simulations mostly for 80% 2D and 20% slab energy and a fluctuation amplitude on the order of B 0. The nonlinear guiding center (NLGC) theory provides a reasonable description of asymptotic perpendicular diffusion as a function of the nonaxisymmetry and particle energy. These values are roughly proportional to the particle speed times the field line diffusion coefficient, with a prefactor that is much lower than in the classical field line random walk model of particle diffusion. NLGC predicts a prefactor in closer agreement with simulations. Next we consider extreme fluctuation anisotropy and the approach to reduced dimensionality. For 99% slab fluctuation energy, field line trajectories are diffusive, but the particle motion is subdiffusive. For 99% 2D fluctuation energy, both field lines and particle motions are initially subdiffusive and then diffusive, but NLGC gives unreliable results. The time dependence of the running particle diffusion coefficient shows that in all cases asymptotic diffusion is preceded by free streaming and subdiffusion, but the latter differs from standard compound subdiffusion. We can model the time profiles in terms of a decaying negative correlation of the perpendicular velocity due to the possibility of backtracking along magnetic field lines.

Antarctic coastal sea ice often grows in water that has been supercooled by interaction with an ice shelf. In these situations, ice crystals can form at depth, rise and deposit under the sea-ice cover to form a porous layer that eventually consolidates near the base of the existing sea ice. The least consolidated portion is called the sub-ice platelet layer. Congelation growth eventually causes the subice platelet layer to become frozen into the sea-ice cover as incorporated platelet ice. In this study, we simulate these processes in three dimensions using Voronoi dynamics to govern crystal growth kinetics. Platelet deposition, in situ growth and incorporation into the sea-ice cover are integrated into the model. Heat and mass transfer are controlled by diffusion. We extract and compare spatial-temporal distributions of porosity, salinity, temperature and crystallographic c-axes with observations from McMurdo Sound, Antarctica. The model captures the crystallographic structure of incorporated platelet ice as well as the topology of the sub-ice platelet layer. The solid fraction, which has previously been poorly constrained, is simulated to be �0.22, in good agreement with an earlier estimate of 0.25 � 0.06. This property of the sub-ice platelet layer is important for biological processes, and for the freeboard-thickness relationship around Antarctica.