ALBERT

Beschreibung: Surface meltwater generated on ice shelves fringing the Antarctic Ice Sheet can drive ice-shelf collapse, leading to ice sheet mass loss and contributing to global sea level rise. A quantitative assessment of supraglacial lake evolution is required to understand the influence of Antarctic surface meltwater on ice-sheet and ice-shelf stability. Cloud computing platforms have made the required remote sensing analysis computationally trivial, yet a careful evaluation of image processing techniques for pan-Antarctic lake mapping has yet to be performed. This work paves the way for automating lake identification at a continental scale throughout the satellite observational record via a thorough methodological analysis. We deploy a suite of different trained supervised classifiers to map and quantify supraglacial lake areas from multispectral Landsat-8 scenes, using training data generated via manual interpretation of the results from k-means clustering. Best results are obtained using training datasets that comprise spectrally diverse unsupervised clusters from multiple regions and that include rock and cloud shadow classes. We successfully apply our trained supervised classifiers across two ice shelves with different supraglacial lake characteristics above a threshold sun elevation of 20°, achieving classification accuracies of over 90% when compared to manually generated validation datasets. The application of our trained classifiers produces a seasonal pattern of lake evolution. Cloud shadowed areas hinder large-scale application of our classifiers, as in previous work. Our results show that caution is required before deploying ‘off the shelf’ algorithms for lake mapping in Antarctica, and suggest that careful scrutiny of training data and desired output classes is essential for accurate results. Our supervised classification technique provides an alternative and independent method of lake identification to inform the development of a continent-wide supraglacial lake mapping product.

Beschreibung: A 1138-meter sediment core (AND-2A) recovered from the Southern McMurdo Sound sector of the Ross Sea comprises a near-continuous record of Antarctic climate and ice sheet variability through the Early to early Middle Miocene (20.2 to 14.5 million years ago), including an interval of inferred sustained global warmth known as the Miocene Climatic Optimum (MCO). The record preserves 55 sedimentary sequences that reflect cycles of glacial advance and retreat. A new analysis of proxy environmental data from the AND-2A core, and synthesis with regional geological information, show that the early to middle Miocene Antarctic climate ranged from cold polar conditions, similar to Antarctica during the Holocene, to those that characterise modern sub-polar environments. Four disconformities that punctuate the sedimentary sequence coincide with regionally mapped seismic discontinuities and reflect transient expansion of marine-based ice across the Ross Sea. The timing of these major marine-based ice sheet advances correlates with shifts in highly-resolved deep sea isotope records and major drops in eustatic sea-level indicating the global nature of these events. In contrast, three distinct intervals in the core indicate that this high latitude site was periodically influenced by an ice sheet margin that had retreated beyond the coastline. These relatively large-scale changes in climate and ice sheet extent occurred under atmospheric carbon dioxide concentrations that generally varied between 300 to 500 ppm. Therefore, our reconstructions suggest that Antarctica’s climate and ice sheets were sensitive to modest changes in greenhouse gas forcing and support previous studies, which indicate that marine-based portions of theWAIS and EAIS can retreat under climatic conditions that were similar to those projected for our future under current levels of atmospheric CO2.