Owing to its huge volume, the Antarctic ice sheet has the potential to cause a global-scale sea level rise. Not only that, but it is also closely entwined with many important aspects of the earth-atmosphere system, such as the global water cycle, the atmospheric heat cycle, ocean temperature and salinity, and ocean circulation. Thus, Antarctic climate change and ice mass variability have emerged as key issues of concern in many recent studies.
However, the accuracy of ice sheet mass balance measurements is currently insufficient, not least because of the sparseness of in situ and satellite measurements over the Antarctic as a results of its harsh environs. Thus, the Antarctic Mesoscale Prediction System (AMPS) is a key tool--specifically, for studying precipitation over the region. Moreover, the products generated by AMPS will be used more widely if shown to hold up to careful scrutiny.
In this context, i.e., to evaluate the performance of AMPS in terms of precipitation, Yihui Liu--an MSc student at the College of Geography and Environment, Shandong Normal University, supervised by Prof. Yetang Wang--analyzed the snow accumulation changes at nine automatic weather stations (AWSs) on the Ross Ice Shelf, Antarctica, from 2008 to 2015. The finding are published in Advances in Atmospheric Sciences (Liu et al., 2017).
The study found that the number of snow accumulation events varied from one station to another during the study period, thus demonstrating geographic dependence. The interannual variability of snow accumulation was too high to determine its seasonality based on the AWS observations and limited time coverage.
Comparison between the AMPS and AWS snow height measurements showed that ~28% of the AWS events were reproduced by AMPS. Furthermore, significant correlation was found between AMPS and AWS coincident event sizes at five stations. The findings suggest that AMPS has a certain ability to represent actual precipitation events.