Antarctic snow-covered sea ice topography derivation from TanDEM-X using polarimetric SAR interferometry

Single-pass interferometric synthetic aperture radar (InSAR) enables the possibility for sea ice topographic retrieval despite the inherent dynamics of sea ice. InSAR digital elevation models (DEMs) are measuring the radar scattering center height. The height bias induced by the penetration of electromagnetic waves into snow and ice leads to inaccuracies of the InSAR DEM, especially for thick and deformed sea ice with snow cover. In this study, an elevation difference between the satellite-measured InSAR DEM and the airborne-measured optical DEM is observed from a coordinated campaign over the western Weddell Sea in Antarctica. The objective is to correct the penetration bias and generate a precise sea ice topographic map from the single-pass InSAR data. With the potential of retrieving sea ice geophysical information by the polarimetric-interferometry (Pol-InSAR) technique, a two-layer-plus-volume model is proposed to represent the sea ice vertical structure and its scattering mechanisms. Furthermore, a simplified version of the model is derived, to allow its inversion with limited a priori knowledge, which is then applied to a topographic retrieval scheme. The experiments are performed across four polarizations: HH, VV, Pauli 1 (HH + VV), and Pauli 2 (HH − VV). The model-retrieved performance is validated with the optically derived DEM of the sea ice topography, showing an excellent performance with root-mean-square error as low as 0.26 m in Pauli-1 (HH + VV) polarization.

Application of a Convolutional Neural Network for the Detection of Sea Ice Leads

Despite accounting for a small fraction of the surface area in the Arctic, long and narrow sea ice fractures, known as “leads”, play a critical role in the energy flux between the ocean and atmosphere. As the volume of sea ice in the Arctic has declined over the past few decades, it is increasingly important to monitor the corresponding changes in sea ice leads. A novel approach has been developed using artificial intelligence (AI) to detect sea ice leads using satellite thermal infrared window data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Visible Infrared Imaging Radiometer Suite (VIIRS). In this new approach, a particular type of convolutional neural network, a U-Net, replaces a series of conventional image processing tests from our legacy algorithm. Results show the new approach has a high detection accuracy with F1 Scores on the order of 0.7. Compared to the legacy algorithm, the new algorithm shows improvement, with more true positives, fewer false positives, fewer false negatives, and better agreement between satellite instruments.

ICESat-2 shows sea ice leads decrease the Arctic cloudiness in cold months

The effect of leads in Arctic sea ice on clouds is a potentially important climate feedback. We use observations of clouds and leads from the Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) to study the effects of leads on clouds. Newly open leads increase cloudiness while newly frozen leads decrease cloudiness. The latter dominates but the magnitude of the net effect depends on the life cycle of leads. The cloud dissipating effect decrease the Arctic cloudiness by 4-6% in cold months. The cloud increasing effect of open leads is evident in areas with strong sea ice deformation and frequent lead formation. Lead effects can reach beyond the boundary layer to 6 km. The lack of proper representation of lead effect on clouds in current climate models and reanalyses contributes to the overestimation of cloudiness over Arctic sea ice in cold months.

A pulse of mercury and major ions in snowmelt runoff from a small Arctic Alaska watershed

Atmospheric mercury (Hg) is deposited to Polar Regions during springtime atmospheric mercury depletion events (AMDEs) that require halogens and snow or ice surfaces. The fate of this Hg during and following snowmelt is largely unknown. We measured Hg, major ions, and stable water isotopes from the snowpack through the entire spring melt runoff period for two years. Our small (2.5 ha) watershed is near Barrow (now Utqiaġvik), Alaska. We measured discharge, made 10 000 snow depths, and collected over 100 samples of snow and meltwater for chemical analysis in 2008 and 2009 from the watershed snowpack and ephemeral stream channel. Our results suggest AMDE Hg complexed with Cl⁻ or Br⁻ may be less likely to be photochemically reduced and re-emitted to the atmosphere prior to snowmelt, and we estimate that roughly 25% of the Hg in snowmelt is attributable to AMDEs. Projected Arctic warming, with more open sea ice leads providing halogen sources that promote AMDEs, may provide enhanced Hg deposition, reduced Hg emission and, ultimately, an increase in snowpack and snowmelt runoff Hg concentrations.

Dynamics of Eddies Generated by Sea Ice Leads

Interaction between the atmosphere and ocean in sea ice-covered regions is largely concentrated in leads, which are long, narrow openings between sea ice floes. Refreezing and brine rejection in these leads injects salt that plays a key role in maintaining the polar halocline. The injected salt forms dense plumes that subsequently become baroclinically unstable, producing submesoscale eddies that facilitate horizontal spreading of the salt anomalies. However, it remains unclear which properties of the stratification and leads most strongly influence the vertical and horizontal spreading of lead-input salt anomalies. In this study, the spread of lead-injected buoyancy anomalies by mixed layer and eddy processes are investigated using a suite of idealized numerical simulations. The simulations are complemented by dynamical theories that predict the plume convection depth, horizontal eddy transfer coefficient and eddy kinetic energy as functions of the ambient stratification and lead properties. It is shown that vertical penetration of buoyancy anomalies is accurately predicted by a mixed layer temperature and salinity budget until the onset of baroclinic instability (~3 days). Subsequently, these buoyancy anomalies are spread horizontally by eddies. The horizontal eddy diffusivity is accurately predicted by a mixing length scaling, with a velocity scale set by the potential energy released by the sinking salt plume and a length scale set by the deformation radius of the ambient stratification. These findings indicate that the intermittent opening of leads can efficiently populate the polar halocline with submesoscale coherent vortices with diameters of around 10 km, and provide a step toward parameterizing their effect on the horizontal redistribution of salinity anomalies.

Antarctic snow-covered sea ice topography derivation from TanDEM-X using polarimetric SAR interferometry

Single-pass interferometric synthetic aperture radar (InSAR) enables the possibility for sea ice topographic retrieval despite the inherent dynamics of sea ice. InSAR digital elevation models (DEM) are measuring the radar scattering centre height. The height bias induced by the penetration of electromagnetic waves into snow and ice leads to inaccuracies of the InSAR DEM, especially for multi-year sea ice with snow 5 cover. In this study, an elevation difference between the satellite-measured InSAR DEM and the airborne-measured optical DEM is observed from a coordinated campaign over the western Weddell Sea in Antarctica. The objective is to correct the penetration bias and generate a precise sea ice topographic map from the single-pass InSAR data. With the potential of retrieving sea ice geophysical information by the polarimetric-interferometry (Pol-InSAR) technique, a two-layer plus volume model is proposed to represent the sea ice vertical structure and its scattering mechanisms. Furthermore, a simplified version of the model is derived, to allow its inversion with limited a priori knowledge, which is then applied to a topographic retrieval scheme. The model-retrieved performance is validated with the optical DEM of the sea ice topography, showing an excellent performance with root-mean-square error as low as 0.22 m. The experiments are performed across four polarizations: HH, VV, Pauli-1 (HH+VV), and Pauli-2 (HH-VV), indicating the polarization-independent volume scattering property of the sea ice in the investigated co-polarized data.

Vertical Heat Fluxes beneath Idealized Sea Ice Leads in Large-Eddy Simulations: Comparison with Observations from the SHEBA Experiment

Large-eddy simulations (Δx = Δz = 1 m) are used to examine vertical ocean heat fluxes driven by mechanical and buoyancy forcing across idealized sea ice leads. Forcing parameters approximate conditions from a shear event during the Surface Heat Budget of the Arctic (SHEBA) experiment in March 1998. In situ measurements near the lead showed isopycnal displacements of 14 m and turbulent vertical heat fluxes up to 400 W m−2, both of which were attributed to a strong cyclonic stress curl localized along the lead axis. By contrast, the large-eddy simulations show cyclonic shear across the lead to produce no turbulence, with vertical heat transport instead related to an overturning cell that connects a broad upwelling near the lead to downwelling farther away. Anticyclonic forcing produces an opposite-signed overturning cell, but with an intense, narrow downwelling jet and strong turbulent heat fluxes (~100 W m−2) near the lead. For both signs of curl, domain-integrated heat transport due to the overturning cells is somewhat larger than the turbulent heat flux, the latter being confined to the vicinity of the lead. Buoyancy forcing related to sea ice formation in the lead was found to increase both the turbulent and the cell-related heat fluxes (by up to 50% and 10%, respectively). Vertical isopycnal displacements for the upwelling case were found to increase linearly with the strength of the forcing. Possible reasons for the discrepancies with the observations include finer scale variation in the surface ocean stress and turbulence associated with the formation of a ridge during the shear event.