Abstract: The coronavirus disease 2019 (COVID-19) pandemic is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This pathogen has spread rapidly across the world, causing high numbers of deaths and significant social and economic impacts. SARS-CoV-2 is a novel coronavirus with a suggested zoonotic origin with the potential for cross-species transmission among animals. Antarctica can be considered the only continent free of SARS-CoV-2. Therefore, concerns have been expressed regarding the potential human introduction of this virus to the continent through the activities of research or tourism to minimise the effects on human health, and the potential for virus transmission to Antarctic wildlife. We assess the reverse-zoonotic transmission risk to Antarctic wildlife by considering the available information on host susceptibility, dynamics of the infection in humans, and contact interactions between humans and Antarctic wildlife. The environmental conditions in Antarctica seem to be favourable for the virus stability. Indoor spaces such as those at research stations, research vessels or tourist cruise ships could allow for more transmission among humans and depending on their movements between different locations the virus could be spread across the continent. Among Antarctic wildlife previous in silico analyses suggested that cetaceans are at greater risk of infection whereas seals and birds appear to be at a low infection risk. However, caution needed until further research is carried out and consequently, the precautionary principle should be applied. Field researchers handling animals are identified as the human group posing the highest risk of transmission to animals while tourists and other personnel pose a significant risk only when in close proximity (< 5 m) to Antarctic fauna. We highlight measures to reduce the risk as well as identify of knowledge gaps related to this issue.

Abstract: Mercury (Hg) is a natural trace element found in high concentrations in top predators, including Arctic seabirds. Most current knowledge about Hg concentrations in Arctic seabirds relates to exposure during the summer breeding period when researchers can easily access seabirds at colonies. However, the few studies focused on winter have shown higher Hg concentrations during the non-breeding period than breeding period in several tissues. Hence, improving knowledge about Hg exposure during the non-breeding period is crucial to understanding the threats and risks encountered by these species year-round. We used feathers of nine migratory alcid species occurring at high latitudes to study bird Hg exposure during both the breeding and non-breeding periods. Overall, Hg concentrations during the non-breeding period were ~3 times higher than during the breeding period. In addition, spatial differences were apparent within and between the Atlantic and Pacific regions. While Hg concentrations during the non-breeding period were ~9 times and ~3 times higher than during the breeding period for the West and East Atlantic respectively, Hg concentrations in the Pacific during the non-breeding period were only ~1.7 times higher than during the breeding period. In addition, individual Hg concentrations during the non-breeding period for most of the seabird colonies were above 5 ?g g?1 dry weight (dw), which is considered to be the threshold at which deleterious effects are observed, suggesting that some breeding populations might be vulnerable to non-breeding Hg exposure. Since wintering area locations, and migration routes may influence seasonal Hg concentrations, it is crucial to improve our knowledge about spatial ecotoxicology to fully understand the risks associated with Hg contamination in Arctic seabirds.

Abstract: Radar altimeters are important tools to monitor the volume of the ice sheets. The penetration of radar waves in the snowpack is a major source of uncertainty to retrieve surface elevation. To correct this effect, a better understanding of the sensitivity of the radar waveforms to snow properties is needed. Here, we present an extension of the Snow Model Radiative Transfer (SMRT) to compute radar waveforms and conduct a series of simulations on the Antarctic ice sheet. SMRT is driven by snow and surface roughness properties measured over a large latitudinal range during two field campaigns on the Antarctic Plateau. These measurements show that the snowpack is rougher, denser, less stratified, warmer, and has smaller snow grains near the coast than on the central Plateau. These simulations are compared to satellite observations in the Ka, Ku, and S bands. SMRT reproduces the observed waveforms well. For all sites and all sensors, the main contribution comes from the surface echo. The echo from snow grains (volume scattering) represents up to 40% of the amplitude of the total waveform power in the Ka band, and less at the lower frequencies. The highest amplitude is observed on the central Plateau due to the combination of higher reflection from the surface, higher scattering by snow grains in the Ka and Ku bands, and higher inter-layer reflections in the S band. In the Ka band, the wave penetrates in the snowpack less deeply on the central Plateau than near the coast because of the strong scattering caused by the larger snow grains. The opposite is observed in the S band, the wave penetrates deeper on the central Plateau because of the lower absorption due to the lower snow temperatures. The elevation bias caused by wave penetration into the snowpack show a constant bias of 10 cm for all sites in the Ka band, and a bias of 11 cm, and 21 cm in the Ku band for sites close to the coast and the central Plateau, respectively. Now that SMRT is performing waveform simulations, further work will address how the snowpack properties affect the parameters retrieved by more advanced retracking algorithms such as ICE-2 for different snow cover surfaces.

Abstract: The high frequency radars in the Super Dual Auroral Radar Network (SuperDARN) estimate the elevation angles of returned backscatter using interferometric techniques. These elevation angles allow the ground range to the scattering point to be estimated, which is crucial for the accurate geolocation of ionospheric measurements. For elevation angles to be accurately estimated, it is important to calibrate the interferometer measurements by determining the difference in the signal time delays caused by the difference in the electrical path lengths from the main array and the interferometer array to the point at which the signals are correlated. This time delay is known as tdiff. Several methods have been proposed to estimate tdiff using historical observations; these methods are summarised in this paper. Comparisons of the tdiff estimates from the different calibration methods are presented and sources of uncertainty discussed. The effect of errors in the estimated tdiff value on the accuracy of geolocation is evaluated and discussed. The paper concludes with a series of recommendations for both scientific SuperDARN data users and SuperDARN radar operators.