In this paper, we present our inaugural remote sensing tests at the Churchill Marine Observatory, in which we obtained polarimetric backscattering measurements from freezing seawater in a mesocosm. This study used surface-based radars in Ku-band, C-band, and L-band frequencies to track sea-ice formation and observe the corresponding changes in the backscatter. Physical sampling and meteorological observations were performed to characterize the freeze-up. The results enhance understanding of sea-ice signatures for future monitoring and climate research by acquiring simultaneous characterization of the polarimetric backscatter at three distinctly separate frequency bands.

Terrestrial snow plays a crucial role in the Earth's system as it significantly governs the energy balance of the cryosphere. Among the diverse methods for measuring snow, remote sensing permits continuous surveillance across various space and time scales. The focus of our study is to evaluate the efficacy of co-located C-band and L-band microwave scatterometers for monitoring snowfall on the ground. In pursuit of this objective, co-polarized and cross-polarized signals were acquired both before and after the occurrence of a snowfall event. The Normalized Radar Cross Sections (NRCS) of C-band and L-band scatterometers were examined throughout the entire study duration. Our findings reveal that both L-band and C-band scatterometers promptly detected wet snow accumulation on the ground. Specifically, C-band at a lower elevation incidence angle (30°) and L-band at a higher incidence angle (55°) exhibited the greatest sensitivity to the accumulation of wet snow on the ground.

Oil thickness in oil spills involving sea ice is a key parameter required for an effective oil spill response; however, quantifying it from radar backscatter data remains a difficult task. We investigated a possible solution for estimating oil slick thickness by using electromagnetic forward and inverse scattering models of oil-covered newly formed sea ice (NI). Our forward model employs a first-order approximation of a multilayered small perturbation method to predict two copolarization C-band radar backscatters of NI covered by an oil slick with thicknesses ranging from 0–7 mm. The results showed that the backscatter decreases as slick thickness increases, which we attributed to signal attenuation within the saline-oil layer. Our inverse model relies on the particle swarm optimization algorithm to determine the slick thickness on NI using synthetic backscatter data, and it requires the input of several important ice and oil physical parameters (thickness, dielectrics, and roughness). Moreover, the estimated slick thickness was validated using scatterometer data from an oil-on-ice experiment at the University of Manitoba’s Sea-ice Environmental Research Facility. With synthetic data, the 5 mm oil slick thickness was overestimated by 25%, while with experimental data, it was overestimated by 8%. Overall, our findings have laid the groundwork for future inversion studies to identify the thickest oil spill zone from current and future C-band radar satellites for immediate response.

Climate-driven sea ice loss has exposed the Arctic to increased human activity, which comes along with a higher risk of oil spills. As a result, we investigated the ability of C-band polarimetric parameters in a controlled mesocosm to accurately identify and discriminate between oil-contaminated and uncontaminated newly formed sea ice (NI). Parameters, such as total power, copolarization ratio, copolarization correlation coefficient, and others, were derived from the normalized radar cross section and covariance matrix to characterize the temporal evolution of NI before and after oil spill events. For separation purposes, entropy ($H$) and mean-alpha ($\alpha$) were extracted from eigen decomposition of the coherency matrix. The$H$versus$\alpha $scatterplot revealed that a threshold classifier of 0.3-$H$and 18°-$\alpha $could distinguish oil-contaminated NI from its oil-free surroundings. From the temporal evolution of the polarimetric parameters, the results demonstrate that the copolarization correlation coefficient is the most reliable polarimetric parameter for oil spill detection, as it provides information on a variety of oil spill scenarios, including oil encapsulated within ice and oil spreading on top of ice. Overall, these findings will be used to support existing and future C-band polarimetric radar satellites for resolving ambiguities associated with Arctic oil spill events, particularly during freeze-up seasons.

Oil spills in the Arctic are becoming more likely as shipping traffic increases in response to climate-related sea ice loss. To improve oil spill detection capability, we used a controlled mesocosm to analyze the multipolarized C-band backscatter response of oil in newly formed sea ice (NI). Artificial sea ice was grown in two cylindrical tubs at the Sea-ice Environmental Research Facility, University of Manitoba. The sea ice physical characteristics, including surface roughness, thickness, temperature, and salinity, were measured before and after oil injection below the ice sheet. Time-series C-band radar backscatter measurements detected the differences in the sea ice evolution and oil migration to the sea ice surface in the oil-contaminated tub, which was compared to uncontaminated ice in a control tub. Immediately prior to the presence of oil on the ice surface, the copolarized backscatter is increased by 13-dB local maximum, while the cross-polarized backscatter is decreased by 9-dB. Ice physical properties suggest that the local backscatter maximum and minimum, which occurred immediately before oil migrated onto the surface, were related to a combination of brine and oil upward migration. The findings of this work provide a baseline data interpretation for oil detection in the Arctic Ocean using current and future C-band multipolarization radar satellites.

In this study, we performed a model-based analysis of scattering from oil-contaminated sea ice. Actual physical measurements of oil-contaminated sea ice were obtained from an experiment in 2017. We used a dielectric mixture model approach to create a multi-layered dielectric profile that represents the sea ice. For the first time, our multi-layered scattering model based on the small perturbation theory, was used to simulate scattering from oil-contaminated sea ice. Modeling results demonstrate that the method can be used for these conditions and show promise for further detailed model studies for detecting oil spills in a sea ice environment.

In this paper, we present model and measurement results for C-band HH and VV normalized radar cross-sections (NRCS) from winter snow-covered first-year sea ice with average snow thicknesses of 16, 4, and 3 cm. The brine content in snow pack was low in all three case studies, which is typical for cold winter conditions. We used the first-order approximation of the small perturbation theory accounting for surface scattering from the air-snow and snow-ice rough interfaces and continuously layered snow and sea ice. The experimental data were collected during the Circumpolar Flaw Lead system study in the winter of 2008 in the southern Beaufort Sea from the research icebreaker Amundsen. Good agreement between the model and experimental data were observed for all three case studies. The model results revealed that the scattering at the snow-ice rough interface is usually stronger than that at the air-snow interface. Furthermore, both model and experimental NRCS values (at VV and HH polarizations) were considerably higher for thin-snow cover compared with the thick-snow-cover case. We associate this effect with the lower attenuation of the propagated wave within the thin-snow pack in comparison to the thick-snow pack. We also demonstrated that different brine volume contents in snow with close thicknesses of 4 and 3 cm did not affect the backscattering coefficients at certain incidence angles and polarization. Our findings provide the physical basis for winter snow thickness retrieval and suggest that such retrievals may be possible from radar observations under particular scattering conditions.

Microwave scattering from sea ice is partially controlled by the ice surface roughness. In this paper, we propose a technique for calculating 2-D centimeter-scale surface roughness parameters, including the rms height, correlation length, and form of autocorrelation function, from 3-D terrestrial light detection and ranging data. We demonstrate that a single scale of roughness can be extracted from complex sea ice surfaces, incorporating multiple scales of topography, after sophisticated 2-D detrending, and calculate roughness parameters for a wide range of artificial and natural sea ice surface types. The 2-D technique is shown to be considerably more precise than standard 1-D profiling techniques and can therefore characterize surface roughness as a stationary single-scale process, which a 1-D technique typically cannot do. Sea ice surfaces are generally found to have strongly anisotropic correlation lengths, indicating that microwave scattering models for sea ice should include surface spectra that vary as a function of the azimuthal angle of incident radiation. However, our results demonstrate that there is no fundamental relationship between the rms height and correlation length for sea ice surfaces if the sampling area is above a threshold minimum size.

A focused study on the C-band polarimetric scattering and physical characteristics of frost-flower-covered sea ice was conducted at the Sea-Ice Environmental Research Facility over a three day period. Sea ice was grown in an outdoor pool outfitted with automated sensors to monitor environmental conditions. C-band polarimetric scattering measurements were conducted continuously at a range of incidence angles, and surface roughness statistics were obtained at discrete times using a laser scanner system LiDAR. Four stages of development were identified that exhibited notably different physical and scattering characteristics: 1) initial formation; 2) surface brine expulsion; 3) frost flower growth; and 4) decimation. An optimal polarization and incidence angle is not readily apparent for the purposes of identifying the frost flower development Stages I-III; however, the lower incidence angles (25° and 35°) appear to be most sensitive to the surface brine expulsion. Only the dual-polarization measurements at low incidence angles (e.g., 25°) could be used to identify the onset of the decimation stage. Backscatter increased rapidly during the initial formation, with a local maximum corresponding to ~ 80% areal coverage of frost flowers, followed by a local minimum when the surface was covered by a brine-rich surface layer, connoting that surface brine expulsion may be identified using polarimetric scatterometry.

A scattering model based on a Monte Carlo method and the finite-volume time-domain (FVTD) method has been created for sea ice scattering simulations. Statistical methods were used to generate a Gaussian-distributed randomly rough surface. The Polder-Van Santen-de Loor (PVD) model was used to estimate the sea ice dielectric values with inputs based upon actual measured physical variables obtained during field-based experiments and well-known parameterizations. Scattering simulations were performed through an application of the scattered-field (SF) formulation invoked in an FVTD computational engine. Simulated SFs were compared with C-band scatterometer measurements and showed good agreement for copolarized signals in a series of case studies. The developed simulation method has the potential to be used for a variety of sea ice types under different physical conditions.

A study of the polarimetric backscattering response of newly formed sea ice types under a large assortment of surface coverage was conducted using a ship-based C-band polarimetric radar system. Polarimetric backscattering results and physical data for 40 stations during the fall freeze-up of 2003, 2006, and 2007 are presented. Analysis of the copolarized correlation coefficient showed its sensitivity to both sea ice thickness and surface coverage and resulted in a statistically significant separation of ice thickness into two regimes: ice less than 6 cm thick and ice greater than 8 cm thick. A case study quantified the backscatter of a layer of snow infiltrated frost flowers on new sea ice, showing that the presence of the old frost flowers can enhance the backscatter by more than 6 dB. Finally, a statistical analysis of a series of temporal-spatial measurements over a visually homogeneous frost-flower-covered ice floe identified temperature as a significant, but not exclusive, factor in the backscattering measurements.

Polarimetric observations of sea ice from synthetic aperture radar can, in principle, assist in sea-ice classification and ice-water discrimination. In this paper, we use dual-polarization ground-based scatterometer observations of sea ice to assess the potential value of spaceborne dual-polarization observations of sea ice for operational ice analysis, focusing on C-band and, in particular, the contribution of the HV backscatter coefficient and HH/VV polarization ratios. Results show that signature variability resulting from frost flowers, ice deformation, and snow cover can overwhelm systematic differences between younger ice types, up to first-year thin. As a result of this and noise floor limitations of spaceborne sensors, the HV backscatter coefficient makes visual ice type and open water discrimination easier only below about 30° incidence angle. The HH/VV ratio is less impacted by the noise floor of spaceborne sensors but retains similar ambiguities for sea-ice classification.

Backscatter signatures of multiyear sea ice (MYI) during the late summer and early fall season before the fall freeze-up in the Canadian Arctic archipelago (CAA) have been obtained through the use of a ship-based polarimetric scatterometer. The device operates in C-band, and measurements were conducted in swaths from incidence angles of 20deg-60deg. Three characteristic sites on MYI floes were investigated in the high Arctic and the central Arctic regions.Insitusnow and sea-ice thermophysical data were collected at each site in conjunction with local scatterometer measurements. The thermophysical data were subsequently analyzed using dielectric modeling techniques and coupled with the backscattering measurements (sigmadeg). Observed backscatter values and ratios were found to be in agreement with literature data, with volumetric scattering as the dominant scattering mechanism.