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1. Lateral meltwater transfer across an Antarctic ice shelf

   https://doi.org/10.5194/tc-14-2313-2020  

   Dell, Rebecca ; Arnold, Neil ; Willis, Ian ; Banwell, Alison ; Williamson, Andrew ; Pritchard, Hamish ; Orr, Andrew ( January 2020 , The Cryosphere)

   null (Ed.)

   Abstract. Surface meltwater on ice shelves can exist as slush, it can pond in lakes orcrevasses, or it can flow in surface streams and rivers. The collapse of theLarsen B Ice Shelf in 2002 has been attributed to the sudden drainage of∼3000 surface lakes and has highlighted the potential forsurface water to cause ice-shelf instability. Surface meltwater systems havebeen identified across numerous Antarctic ice shelves, although the extentto which these systems impact ice-shelf instability is poorly constrained.To better understand the role of surface meltwater systems on ice shelves,it is important to track their seasonal development, monitoring thefluctuations in surface water volume and the transfer of water acrossice-shelf surfaces. Here, we use Landsat 8 and Sentinel-2 imagery to tracksurface meltwater across the Nivlisen Ice Shelf in the 2016–2017 meltseason. We develop the Fully Automated Supraglacial-Water Tracking algorithmfor Ice Shelves (FASTISh) and use it to identify and track the developmentof 1598 water bodies, which we classify as either circular or linear. Thetotal volume of surface meltwater peaks on 26 January 2017 at 5.5×107 m3. At this time, 63 % of the total volume is held withintwo linear surface meltwater systems, which are up to 27 km long, areorientated along the ice shelf's north–south axis, and follow the surfaceslope. Over the course of the melt season, they appear to migrate away fromthe grounding line, while growing in size and enveloping smaller waterbodies. This suggests there is large-scale lateral water transfer throughthe surface meltwater system and the firn pack towards the ice-shelf frontduring the summer. 

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2. Antarctic Supraglacial Lake Identification Using Landsat-8 Image Classification

   https://doi.org/10.3390/rs12081327  

   Halberstadt, Anna Ruth ; Gleason, Colin J. ; Moussavi, Mahsa S. ; Pope, Allen ; Trusel, Luke D. ; DeConto, Robert M. ( April 2020 , Remote Sensing)

   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. 

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3. Antarctic-wide ice-shelf firn emulation reveals robust future firn air depletion signal for the Antarctic Peninsula

   https://doi.org/10.1038/s43247-024-01255-4  

   Dunmire, Devon ; Wever, Nander ; Banwell, Alison F. ; Lenaerts, Jan T. M. ( February 2024 , Communications Earth & Environment)

   Antarctic firn is critical for ice-shelf stability because it stores meltwater that would otherwise pond on the surface. Ponded meltwater increases the risk of hydrofracture and subsequent potential ice-shelf collapse. Here, we use output from a firn model to build a computationally simpler emulator that uses a random forest to predict ice-shelf effective firn air content, which considers impermeable ice layers that make deeper parts of the firn inaccessible to meltwater, based on climate conditions. We find that summer air temperature and precipitation are the most important climatic features for predicting firn air content. Based on the climatology from an ensemble of Earth System Models, we find that the Larsen C Ice Shelf is most at risk of firn air depletion during the 21st century, while the larger Ross and Ronne-Filchner ice shelves are unlikely to experience substantial firn air content change. This work demonstrates the utility of emulation for computationally efficient estimations of complicated ice sheet processes.

    

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4. Antarctic Supraglacial Lake Detection Using Landsat 8 and Sentinel-2 Imagery: Towards Continental Generation of Lake Volumes

   https://doi.org/10.3390/rs12010134  

   Moussavi, Mahsa ; Pope, Allen ; Halberstadt, Anna ; Trusel, Luke ; Cioffi, Leanne ; Abdalati, Waleed ( January 2020 , Remote Sensing)

   Melt and supraglacial lakes are precursors to ice shelf collapse and subsequent accelerated ice sheet mass loss. We used data from the Landsat 8 and Sentinel-2 satellites to develop a threshold-based method for detection of lakes found on the Antarctic ice shelves, calculate their depths and thus their volumes. To achieve this, we focus on four key areas: the Amery, Roi Baudouin, Nivlisen, and Riiser-Larsen ice shelves, which are all characterized by extensive surface meltwater features. To validate our products, we compare our results against those obtained by an independent method based on a supervised classification scheme (e.g., Random Forest algorithm). Additional verification is provided by manual inspection of results for nearly 1000 Landsat 8 and Sentinel-2 images. Our dual-sensor approach will enable constructing high-resolution time series of lake volumes. Therefore, to ensure interoperability between the two datasets, we evaluate depths from contemporaneous Landsat 8 and Sentinel-2 image pairs. Our assessments point to a high degree of correspondence, producing an average R2 value of 0.85, no bias, and an average RMSE of 0.2 m. We demonstrate our method’s ability to characterize lake evolution by presenting first evidence of drainage events outside of the Antarctic Peninsula on the Amery Ice shelf. The methods presented here pave the way to upscaling throughout the Landsat 8 and Sentinel-2 observational record across Antarctica to produce a first-ever continental dataset of supraglacial lake volumes. Such a dataset will improve our understanding of the influence of surface hydrology on ice shelf stability, and thus, future projections of Antarctica’s contribution to sea level rise. 

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5. Surface meltwater drainage and ponding on Amery Ice Shelf, East Antarctica, 1973–2019

   https://doi.org/10.1017/jog.2021.46  

   Spergel, Julian J. ; Kingslake, Jonathan ; Creyts, Timothy ; van Wessem, Melchior ; Fricker, Helen A. ( January 2021 , Journal of Glaciology)

   null (Ed.)

   Abstract Surface melting on Amery Ice Shelf (AIS), East Antarctica, produces an extensive supraglacial drainage system consisting of hundreds of lakes connected by surface channels. This drainage system forms most summers on the southern portion of AIS, transporting meltwater large distances northward, toward the ice front and terminating in lakes. Here we use satellite imagery, Landsat (1, 4 and 8), MODIS multispectral and Sentinel-1 synthetic aperture radar to examine the seasonal and interannual evolution of the drainage system over nearly five decades (1972–2019). We estimate seasonal meltwater input to one lake by integrating output from the regional climate model [Regional Atmospheric Climate Model (RACMO 2.3p2)] over its catchment defined using the Reference Elevation Model of Antarctica. We find only weak positive relationships between modeled seasonal meltwater input and lake area and between meltwater input and lake volume. Consecutive years of extensive melting lead to year-on-year expansion of the drainage system, potentially through a link between melt production, refreezing in firn and the maximum extent of the lakes at the downstream termini of drainage. These mechanisms are important when evaluating the potential of drainage systems to grow in response to increased melting, delivering meltwater to areas of ice shelves vulnerable to hydrofracture. 

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