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:

Due to recent climate change conditions, i.e. increasing temperatures and changing precipitation patterns, arctic snow cover dynamics exhibit strong changes in terms of extent and duration. Arctic amplification processes and impacts are well documented expected to strengthen in coming decades. In this context, innovative observation methods are helpful for a better comprehension of the spatial variability of snow properties relevant for climate research and hydrological applications.

Microwave remote sensing provides exceptional spatial and temporal performance in terms of all-weather application and target penetration. Time-series of Synthetic Active Radar images (SAR) are becoming more accessible at different frequencies and polarimetry has demonstrated a significant advantage for detecting changes in different media. Concerning arctic snow monitoring, SAR sensors can offer continuous time-series during the polar night and with cloud cover, providing a consequent advantage in regard of optical sensors.

The aim of this study is dedicated to the spatial/temporal variability of snow in the Ny-Ålesund area on the Br∅gger peninsula, Svalbard (N 78°55’ / E 11° 55’). The TerraSAR-X satellite (DLR, Germany) operated at X-band (3.1 cm, 9.6 GHz) with dual co-pol mode (HH/VV) at 5-m spatial resolution, and with high incidence angles (36° to 39°) poviding a better snow penetration and reducing topographic constraints. A dataset of 92 images (ascending and descending) is available since 2017, together with a high resolution DEM (NPI 5-m) and consistent in-situ measurements of meteorological data and snow profiles including glaciers sites.

Polarimetric processing is based on the Kennaugh matrix decomposition, copolar phase coherence (CCOH) and copolar phase difference (CPD). The Kennaugh matrix elements K₀, K₃, K_4, and K₇ are, respectively, the total intensity, phase ratio, intensity ratio, and shift between HH and VV phase center. Their interpretation allows analysing the structure of the snowpack linked to the near real time of in-situ measurements (snow profiles).

The X-band signal is strongly influenced by the snow stratigraphy: internal ice layers reduce or block the penetration of the signal into the snow pack. The best R² correlation performances between estimated and measured snow heights are ranging from 0.50 to 0.70 for dry snow conditions. Therefore, the use of the X-band for regular snow height estimations remains limited under these conditions.

Conversely, this study shows the benefit of TerraSAR-X thanks to the Kennaugh matrix elements analysis. A focus is set on the Copolar Phase Difference (CPD, Leinss 2016) between VV and HH polarization: Φ CPD = Φ _VV – Φ _HH. Our results indicate that the CPD values are related to the snow metamorphism: positive values correspond to dry snow (horizontal structures), negative values indicate recrystallization processes (vertical structures).

Backscattering evolution in time offer a good proxy for meteorological events detection, impacting on snow metamorphism. Fresh snowfalls or melting processes can then be retrieved at the regional scale and linked to air temperature or precipitation measurements at local scale. Polarimetric SAR time series is therefore of interest to complement satellite-based precipitation measurements in the Arctic.