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Abstract. Earth system models are essential tools for understandingthe impacts of a warming world, particularly on the contribution of polarice sheets to sea level change. However, current models lack full couplingof the ice sheets to the ocean and are typically run at a coarse resolution(1∘ grid spacing or coarser). Coarse spatial resolution isparticularly a problem over Antarctica, where sub-grid-scale orography iswell-known to influence precipitation fields, and glacier models requirehigh-resolution atmospheric inputs. This resolution limitation has beenpartially addressed by regional climate models (RCMs), which must be forcedat their lateral and ocean surface boundaries by (usually coarser) globalatmospheric datasets, However, RCMs fail to capture the two-way couplingbetween the regional domain and the global climate system. Conversely,running high-spatial-resolution models globally is computationallyexpensive and can produce vast amounts of data. Alternatively, variable-resolution grids can retain the benefits of highresolution over a specified domain without the computational costs ofrunning at a high resolution globally. Here we evaluate a historicalsimulation of the Community Earth System Model version 2 (CESM2)implementing the spectral element (SE) numerical dynamical core (VR-CESM2)with an enhanced-horizontal-resolution (0.25∘) grid over theAntarctic Ice Sheet and the surrounding Southern Ocean; the rest of theglobal domain is on the standard 1∘ grid. We compare it to1∘ model runs of CESM2 using both the SE dynamical core and thestandard finite-volume (FV) dynamical core, both with identical physics andforcing, including prescribed sea surface temperatures (SSTs) and sea ice concentrations fromobservations. Our evaluation reveals both improvements and degradations inVR-CESM2 performance relative to the 1∘ CESM2. Surface massbalance estimates are slightly higher but within 1 standard deviation ofthe ensemble mean, except for over the Antarctic Peninsula, which isimpacted by better-resolved surface topography. Temperature and windestimates are improved over both the near surface and aloft, although theoverall correction of a cold bias (within the 1∘ CESM2 runs) hasresulted in temperatures which are too high over the interior of the icesheet. The major degradations include the enhancement of surface melt aswell as excessive cloud liquid water over the ocean, with resultant impactson the surface radiation budget. Despite these changes, VR-CESM2 is avaluable tool for the analysis of precipitation and surface mass balanceand thus constraining estimates of sea level rise associated with theAntarctic Ice Sheet. 

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. 

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. 

Abstract Surface melting and lakes are common to Antarctic ice shelves, and their existence and drainages have been invoked as a precursor for ice shelf collapse. Here, we present satellite observations over 2014–2020 of repeated, rapid drainages of a supraglacial lake at the grounding zone of Amery Ice Shelf, East Antarctica. Post‐drainage imagery in 2018 reveals lake bottom features characteristic of rapid, vertical lake drainage. Observed lake volumes indicate drainages are not associated with a threshold meltwater volume. Instead, drainages typically coincide with periods of high daily tidal amplitude, suggesting hydrofracture is assisted by tidally forced ice flexure inherent to the ice shelf grounding zone. Combined with observations of widespread grounding zone lake drainages on Amery, these findings indicate ice shelf meltwater accumulation may be inhibited by grounding zone drainage events, thus representing a potential stabilizing mechanism despite enhanced melting common to these regions. 

Abstract. Projection of the contribution of ice sheets to sea level change as part ofthe Coupled Model Intercomparison Project Phase 6 (CMIP6) takes the formof simulations from coupled ice sheet–climate models and stand-alone icesheet models, overseen by the Ice Sheet Model Intercomparison Project forCMIP6 (ISMIP6). This paper describes the experimental setup forprocess-based sea level change projections to be performed with stand-aloneGreenland and Antarctic ice sheet models in the context of ISMIP6. TheISMIP6 protocol relies on a suite of polar atmospheric and oceanicCMIP-based forcing for ice sheet models, in order to explore the uncertaintyin projected sea level change due to future emissions scenarios, CMIPmodels, ice sheet models, and parameterizations for ice–ocean interactions.We describe here the approach taken for defining the suite of ISMIP6stand-alone ice sheet simulations, document the experimental framework andimplementation, and present an overview of the ISMIP6 forcing to beused by participating ice sheet modeling groups.