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Adélie‐George V Land in East Antarctica, encompassing the vast Wilkes Subglacial Basin, has a configuration that could be prone to ice sheet instability: the basin's retrograde bed slope could make its marine terminating glaciers vulnerable to warm seawater intrusion and irreversible retreat under predicted climate forcing. However, future projections are uncertain, due in part to limited subglacial observations near the grounding zone. Here, we develop a novel statistical approach to characterize subglacial conditions from radar sounding observations. Our method reveals intermixed frozen and thawed bed within 100 km of the grounding‐zone near the Wilkes Subglacial Basin outflow, and enables comparisons to ice sheet model‐inferred thermal states. The signs of intermixed or near thawed conditions raises the possibility that changes in basal thermal state could impact the stability of Adélie‐George V Land, adding to the region's potentially vulnerable topographic configuration and sensitivity to ocean forcing driven grounding line retreat.

 

Variability in oceanic conditions directly impacts ice loss from marine outlet glaciers in Greenland, influencing the ice sheet mass balance. Oceanic conditions are available from Atmosphere‐Ocean Global Climate Model (AOGCM) output, but these models require extensive computational resources and lack the fine resolution needed to simulate ocean dynamics on the Greenland continental shelf and close to glacier marine termini. Here, we develop a statistical approach to generate ocean forcing for ice sheet model simulations, which incorporates natural spatiotemporal variability and anthropogenic changes. Starting from raw AOGCM ocean heat content, we apply: (a) a bias‐correction using ocean reanalysis, (b) an extrapolation accounting for on‐shelf ocean dynamics, and (c) stochastic time series models to generate realizations of natural variability. The bias‐correction reduces model errors by ∼25% when compared to independent in‐situ measurements. The bias‐corrected time series are subsequently extrapolated to fjord mouth locations using relations constrained from available high‐resolution regional ocean model results. The stochastic time series models reproduce the spatial correlation, characteristic timescales, and the amplitude of natural variability of bias‐corrected AOGCMs, but at negligible computational expense. We demonstrate the efficiency of this method by generating >6,000 time series of ocean forcing for >200 Greenland marine‐terminating glacier locations until 2100. As our method is computationally efficient and adaptable to any ocean model output and reanalysis product, it provides flexibility in exploring sensitivity to ocean conditions in Greenland ice sheet model simulations. We provide the output and workflow in an open‐source repository, and discuss advantages and future developments for our method.

 

Greenland’s coastal margins are influenced by the confluence of Arctic and Atlantic waters, sea ice, icebergs, and meltwater from the ice sheet. Hundreds of spectacular glacial fjords cut through the coastline and support thriving marine ecosystems and, in some places, adjacent Greenlandic communities. Rising air and ocean temperatures, as well as glacier and sea-ice retreat, are impacting the conditions that support these systems. Projecting how these regions and their communities will evolve requires understanding both the large-scale climate variability and the regional-scale web of physical, biological, and social interactions. Here, we describe pan-Greenland physical, biological, and social settings and show how they are shaped by the ocean, the atmosphere, and the ice sheet. Next, we focus on two communities, Qaanaaq in Northwest Greenland, exposed to Arctic variability, and Ammassalik in Southeast Greenland, exposed to Atlantic variability. We show that while their climates today are similar to those of the warm 1930s­–1940s, temperatures are projected to soon exceed those of the last 100 years at both locations. Existing biological records, including fisheries, provide some insight on ecosystem variability, but they are too short to discern robust patterns. To determine how these systems will evolve in the future requires an improved understanding of the linkages and external factors shaping the ecosystem and community response. This interdisciplinary study exemplifies a first step in a systems approach to investigating the evolution of Greenland’s coastal margins. 

Abstract. The ice sheet model intercomparison project for CMIP6 (ISMIP6) effort brings together the ice sheet and climate modeling communities to gain understanding of the ice sheet contribution to sea level rise. ISMIP6 conducts stand-alone ice sheet experiments that use space- and time-varying forcing derived from atmosphere–ocean coupled global climate models (AOGCMs) to reflect plausible trajectories for climate projections. The goal of this study is to recommend a subset of CMIP5 AOGCMs (three core and three targeted) to produce forcing for ISMIP6 stand-alone ice sheet simulations, based on (i) their representation of current climate near Antarctica and Greenland relative to observations and (ii) their ability to sample a diversity of projected atmosphere and ocean changes over the 21st century. The selection is performed separately for Greenland and Antarctica. Model evaluation over the historical period focuses on variables used to generate ice sheet forcing. For stage (i), we combine metrics of atmosphere and surface ocean state (annual- and seasonal-mean variables over large spatial domains) with metrics of time-mean subsurface ocean temperature biases averaged over sectors of the continental shelf. For stage (ii), we maximize the diversity of climate projections among the best-performing models. Model selection is also constrained by technical limitations, such as availability of required data from RCP2.6 and RCP8.5 projections. The selected top three CMIP5 climate models are CCSM4, MIROC-ESM-CHEM, and NorESM1-M for Antarctica and HadGEM2-ES, MIROC5, and NorESM1-M for Greenland. This model selection was designed specifically for ISMIP6 but can be adapted for other applications. 

The Amundsen Sea Embayment of the West Antarctic Ice Sheet contains Thwaites and Pine Island Glaciers, two of the most rapidly changing glaciers in Antarctica. To date, Pine Island and Thwaites Glaciers have only been observed by independent airborne radar sounding surveys, but a combined cross‐basin analysis that investigates the basal conditions across the Pine Island‐Thwaites Glaciers boundary has not been performed. Here, we combine two radar surveys and correct for their differences in system parameters to produce unified englacial attenuation and basal relative reflectivity maps spanning both Pine Island and Thwaites Glaciers. Relative reflectivities range from −24.8 to +37.4 dB with the highest values beneath fast‐flowing ice at the ice sheet margin. By comparing our reflectivity results with previously derived radar specularity and trailing bed echoes at Thwaites Glacier, we find a highly diverse subglacial landscape and hydrologic conditions that evolve along‐flow. Together, these findings highlight the potential for joint airborne radar analysis with ground‐based seismic and geomorphological observations to understand variations in the bed properties and cross‐catchment interactions of ice streams and outlet glaciers.