Observations of Continuous Instability for Scar Inlet Ice Shelf, Antarctic Peninsula

Abstract

Abstract. Observation of the evolving instability of ice shelves plays a very important role in global change research. Following the suddenly large-scale collapse of the Larsen B Ice Shelf in the Antarctic Peninsula in 2002, the evolving instability for its remnant, the Scar Inlet Ice Shelf, began to be increasingly studied to provide a deeper understanding of the disintegration of the Larsen B Ice Shelf in 2002 and also provide a chance for studying the response of ice shelves to the large-scale collapse events. In this study, based on sequential Landsat images spanning 2005–2020, we produced detailed maps of the ice velocity fields for the Scar Inlet Ice Shelf. The results indicate that the ice velocities for the Scar Inlet Ice Shelf region have substantially increased since 2005, the maximum ice velocity reached more than 900 m/y in the ice shelf front. Surface rifts have also substantially increased in both length and width and are moving seawards. The ice front position of the Scar Inlet Ice Shelf is relatively stable in 2008–2010 and then steadily advancing after 2010. The acceleration of ice velocities, the dynamic change of the ice front, the increase of major surface rifts and the newly added rifts in the central part of the ice shelf, and the heavily enhanced surface crevasses are all revealing the evolving instability of the Scar Inlet Ice Shelf.

Ice Flow Velocity Mapping for Long-Time Motion Analysis of Typical Glaciers in Northwestern Greenland

“…The data used in this paper to map the historical ice flow velocity maps of four typical glaciers in northwestern Greenland were DISP Mosaics from 1962 and 1963 developed by Zhou et al [8] and Landsat MSS images from 1970 to 1985. DISP Mosaics and Landsat MSS/TM/ETM+ images from 1973 to 2019 were used to track the ice fronts of four glaciers [12]. DISP Mosaics use the WGS84 reference coordinate system, with a resolution of 100 m and an average accuracy of less than 200 m. We selected images with lower snow cover, visible texture features, and reduced cloud cover to ensure better data quality for later analysis.…”