This thesis documents a series of studies performed on the lower atmosphere over the region of the Ross Ice Shelf, Antarctica, and its surroundings. In particular, much of the thesis focuses on the area in the vicinity of Ross Island, a mountainous protrusion in the far north-west of the permanent floating ice shelf. Weather in both the smaller and larger regions is naturally complex and generated by a range of localised and larger scale interactions.

In order to better understand the meteorology of the Ross Ice Shelf, including Ross Island, we produce a synoptic climatology of the region based on surface wind output provided by the ERA Interim reanalysis. Output is taken from 1979 to 2011 and thus represents a much longer time scale than covered by previous studies of Ross Ice Shelf winds. The climatology is generated through a clustering routine based on the widely-used k-means technique. The results of the routine are discussed and we find that the reanalysis is capable of representing the previously reported features of the region. Cluster composites are also shown to be coherent between reanalysis output and data collected by in situ monitoring devices. We confirm that the Ross Ice Shelf Air Stream (RAS), a jet of fast-moving air that propagates from the Siple Coast across the ice shelf, is a robust feature of the climatology of the region and we find that it has a large impact on the surface temperature. The analysis is continued with reference to two widely studied modes of internal variability, the Southern Annular Mode (SAM) and El Nino-Southern Oscillation (ENSO), which are known to affect local conditions in the Ross Sea region via modulation of the Amundsen-Bellingshausen Sea low. Reanalysis output and results from the clustering routine allow us to examine the impacts of these modes upon the Ross Ice Shelf and Ross Sea in unprecedented detail. Further, we are able to tie changes in the mean pattern to variability within and between particular clusters, allowing us to ascertain the dominant synoptic patterns in forcing the mean variability. The impact on surface temperatures for both modes is found to be high and significant, which we explain with reference to changes in circulation patterns.

We further use the results of the clustering algorithm to explore the climatology of the region surrounding Ross Island. By producing composites of local in situ records based on the clustering technique described previously, we are able to generate a climatology of the region that is not hampered by gaps in the observational record. We find that the climate of Ross Island is sensitive to RAS events, due to the ability of strong flows to dramatically increase the temperature. At Scott Base, on the southern tip of the Hut Point Peninsula, the temperature is found to be particularly sensitive to these events. McMurdo Station, which is located less than 3 km away, is observed to be much less sensitive, due to the modulation of synoptic flows by localised topographic influences. Particularly salient is the difference in temperature trends between these two locations, which we show to be statistically significant in the annual and seasonal means from 1979 onwards. By applying a novel temperature reconstruction technique based on the output of the clustering routine, we are able to assess the contribution of changes in circulation to temperature trends at these two locations. We conclude that a large amount of the change in temperature at Scott Base can be explained through circulatory variability over the Ross Ice Shelf. However, the trend at McMurdo Station can not be explained using this technique and may be the result of extremely localised forcing.

Data availability in Antarctica is widely known to be low, due to the relative sparsity of observations and ongoing problems with data collection due to extremely inhospitable conditions and challenging logistical considerations. The lack of data at the mesoscale has hampered the understanding of localised processes in the Antarctic atmosphere that may be important for forecasting. Through the development and deployment of a distributed system of atmospheric sensors called