Small-scale spatial-temporal variability in snow cover and relationships with vegetation and climate in maritime Antarctica

Snow cover changes can have important effects on ecosystems, especially where spatial variability in cover is high, influencing the biogeochemical conditions of the underlying soil as well as the vegetation. In this study, snow thickness and areal distribution were monitored using a time lapse camera over a grid of 15 x 20 m between 2009 and 2017 at Signy Island (60 degrees S, South Orkney Islands, maritime Antarctica). The data obtained confirmed high spatial and temporal variability in snow cover. Over the study period, the mean annual snow depth ranged between 5.6 cm (2017) and 11.1 cm (2012) while the maximum of the mean daily snow depth across the entire grid ranged between 17.1 cm (2017) and 50.1 cm (2015). No temporal trend was apparent but there was a strong correlation with mean annual air temperature, suggesting that possible future warming could decrease snow depth in the area. A negative correlation was identified between the winter Southern Oscillation Index (SOI) and mean annual snow depth, indicating an influence of El Nino-Southern Oscillation (ENSO) on snow cover in this part of Antarctica. There was considerable small-scale spatial variability in snow depth at each individual stake, with mean values between 3.9 and 25.3 cm and maximum values between 27 and 85 cm. Snow depth variability was influenced primarily by microtopography and wind direction, but also by the land cover type (vegetation). Our data highlight that spatial monitoring of snow accumulation is required at small physical scale to predict future effects of climatic changes on these sensitive maritime Antarctic terrestrial ecosystems.

Automated summary

Snow cover changes, monitored on Signy Island in maritime Antarctica between 2009 and 2017, showed high spatial and temporal variability, with mean annual snow depth influenced by air temperature and the Southern Oscillation Index. Small-scale spatial variability in snow accumulation was found to be influenced by microtopography, wind direction, and land cover type.