No abstract

Basal melting of ice shelves is inherently difficult to quantify through direct observations, yet it is a critical factor controlling Antarctic mass balance and global sea-level rise. While much research attention is paid to larger ice shelves and those experiencing the most rapid change, many smaller, unstudied ice shelves offer valuable insights. Here, we investigate the oceanographic conditions and melting beneath the Sørsdal ice shelf, East Antarctica. We present results from the 2018/2019 Sørsdal deployment of the University of Tasmania's autonomous underwater vehicle nupiri muka. Oceanography adjacent to and beneath the ice shelf front shows a cold and relatively saline environment dominated by Winter Water and Dense Shelf Water, while bathymetry measurements show a deep (∼1,200 m) trough running into the ice shelf cavity. Two multiyear deployments of Autonomous Phase-sensitive Radar Echo Sounders on the surface of the ice shelf show weak melt rates (average of 1.6 and 2.3 m yr −1) with low temporal variability. These observations are supported by numerical ocean model and satellite estimates of melting. We speculate that the presence of a ∼825 m thick (350 m to at least 1,175 m) homogeneous layer of cold, dense water blocks access from warmer waters that intrude into Prydz Bay from offshore, resulting in weak melt rates. However, the newly identified trough means that the ice shelf is vulnerable to any decrease in polynya activity that allows warm water to enter the cavity. This could lead to increased basal melting and mass loss through this sector of Antarctica.

No abstract

This paper presents a teach-and-repeat path following method for an Autonomous Underwater Vehicle (AUV) navigating long distances in environments where external navigation aides are denied. This method utilizes sonar images to construct a series of reference views along a path, stored as a topological map. The AUV can then re-navigate along this path, either to return to the start location, or to repeat the route. Utilizing unique assumptions about the sonar image generation process, this system exhibits robust image matching capabilities, providing observations to a discrete Bayesian filter which maintains an estimate of progress along the path. Image matching also provides an estimate of offset from the path, allowing the AUV to correct its heading and effectively close the gap. Over a series of field trials, this system demonstrated online control of an AUV in the ocean environment of Holyrood Arm, Newfoundland and Labrador, Canada. The system was implemented on an International Submarine Engineering Ltd. Explorer AUV and performed multiple path completions over both a 1km and 5km track. These trials illustrated an AUV operating in a fully autonomous mode, in which navigation was driven solely by sensor feedback and adaptive control. Path following performance was as desired, with the AUV maintaining close offset to the path.