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Abstract West Antarctic Ice Sheet mass loss is a major source of uncertainty in sea level projections. The primary driver of this melting is oceanic heat from Circumpolar Deep Water originating offshore in the Antarctic Circumpolar Current. Yet, in assessing melt variability, open ocean processes have received considerably less attention than those governing cross-shelf exchange. Here, we use Lagrangian particle release experiments in an ocean model to investigate the pathways by which Circumpolar Deep Water moves toward the continental shelf across the Pacific sector of the Southern Ocean. We show that Ross Gyre expansion, linked to wind and sea ice variability, increases poleward heat transport along the gyre’s eastern limb and the relative fraction of transport toward the Amundsen Sea. Ross Gyre variability, therefore, influences oceanic heat supply toward the West Antarctic continental slope. Understanding remote controls on basal melt is necessary to predict the ice sheet response to anthropogenic forcing. 

Abstract Oceanic macroturbulence is efficient at stirring and transporting tracers. The dynamical properties of this stirring can be characterized by statistically quantifying tracer structures. Here, we characterize the macroscale (1–100 km) tracer structures observed by two Seagliders downstream of the Southwest Indian Ridge in the Antarctic Circumpolar Current (ACC). These are some of the first glider observations in an energetic standing meander of the ACC, a region associated with enhanced ventilation. The small‐scale density variance in the mixed layer (ML) was relatively enhanced near the surface and base of the ML, while being muted at mid‐depth in the ML, suggesting the formation mechanism to be associated with ML instabilities and eddies. In addition, ML density fronts were formed by comparable contributions from temperature and salinity gradients. In the interior, along‐isopycnal spectra and structure functions of spice indicated that there is relatively lower variance at smaller scales than would be expected based on non‐local stirring, suggesting that flows smaller than the deformation radius play a role in the cascade of tracers to small scales. These interior spice anomalies spanned across isopycnals, and were found to be about 3–5 times flatter than the aspect ratio that would be expected for O(1) Burger number flows like interior QG dynamics, suggesting the ratio of vertical shear to horizontal strain is greater thanN/f. This further supports that small‐scale flows, with high‐mode vertical structures, impact tracer distributions. 

Abstract. Antarctic sea ice has exhibited significant variability over the satellite record, including a period of prolonged and gradual expansion, as well as a period of sudden decline. A number of mechanisms have been proposed to explain this variability, but how each mechanism manifests spatially and temporally remains poorly understood. Here, we use a statistical method called low-frequency component analysis to analyze the spatiotemporal structure of observed Antarctic sea ice concentration variability. The identified patterns reveal distinct modes of low-frequency sea ice variability. The leading mode, which accounts for the large-scale, gradual expansion of sea ice, is associated with the Interdecadal Pacific Oscillation and resembles the observed sea surface temperature trend pattern that climate models have trouble reproducing. The second mode is associated with the central Pacific El Niño–Southern Oscillation (ENSO) and the Southern Annular Mode and accounts for most of the sea ice variability in the Ross Sea. The third mode is associated with the eastern Pacific ENSO and Amundsen Sea Low and accounts for most of the pan-Antarctic sea ice variability and almost all of the sea ice variability in the Weddell Sea. The third mode is also related to periods of abrupt Antarctic sea ice decline that are associated with a weakening of the circumpolar westerlies, which favors surface warming through a shoaling of the ocean mixed layer and decreased northward Ekman heat transport. Broadly, these results suggest that climate model biases in long-term Antarctic sea ice and large-scale sea surface temperature trends are related to each other and that eastern Pacific ENSO variability is a key ingredient for abrupt Antarctic sea ice changes. 

Abstract During the early stages of limb and fin regeneration in aquatic vertebrates (i.e., fishes and amphibians), blastema undergo transcriptional rewiring of innate immune signaling pathways to promote immune cell recruitment. In mammals, a fundamental component of innate immune signaling is the cytosolic DNA sensing pathway, cGAS‐STING. However, to what extent the cGAS‐STING pathway influences regeneration in aquatic anamniotes is unknown. In jawed vertebrates, negative regulation of cGAS‐STING activity is accomplished by suppressors of cytosolic DNA such as Trex1, Pml, and PML‐like exon 9 (Plex9) exonucleases. Here, we examine the expression of these suppressors of cGAS‐STING, as well as inflammatory genes and cGAS activity during caudal fin and limb regeneration using the spotted gar (Lepisosteus oculatus) and axolotl (Ambystoma mexicanum) model species, and during age‐related senescence in zebrafish (Danio rerio). In the regenerative blastema of wounded gar and axolotl, we observe increased inflammatory gene expression, including interferon genes and interleukins 6 and 8. We also observed a decrease in axolotlTrex1and garpmlexpression during the early phases of wound healing which correlates with a dramatic increase in cGAS activity. In contrast, theplex9.1gene does not change in expression during wound healing in gar. However, we observed decreased expression ofplex9.1in the senescing cardiac tissue of aged zebrafish, where 2′3′‐cGAMP levels are elevated. Finally, we demonstrate a similar pattern ofTrex1,pml, andplex9.1gene regulation across species in response to exogenous 2′3′‐cGAMP. Thus, during the early stages of limb‐fin regeneration, Pml, Trex1, and Plex9.1 exonucleases are downregulated, presumably to allow an evolutionarily ancient cGAS‐STING activity to promote inflammation and the recruitment of immune cells. 

Abstract 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. 

Abstract. Antarctic sea ice gradually increased from the late 1970s until 2016, when it experienced an abrupt decline. A number of mechanisms have been proposed for both the gradual increase and abrupt decline of Antarctic sea ice, but how each mechanism manifests spatially and temporally remains poorly understood. Here, we use a statistical method called low-frequency component analysis to analyze the spatial-temporal structure of observed Antarctic sea-ice concentration variability. The identified patterns reveal distinct modes of low-frequency sea ice variability. The leading mode, which accounts for the large-scale, gradual expansion of sea ice, is associated with the Interdecadal Pacific Oscillation and resembles the observed sea-surface temperature trend pattern that climate models have trouble reproducing. The second mode is associated with the central Pacific El Niño–Southern Oscillation (ENSO) and the Southern Annular Mode, and accounts for most of the sea ice variability in the Ross Sea. The third mode is associated with the eastern Pacific ENSO and Amundsen Sea Low, and accounts for most of the pan-Antarctic sea-ice variability and almost all of the sea ice variability in the Weddell Sea. This mode is associated with periods of abrupt Antarctic sea-ice decline and is related to a weakening of the circumpolar westerlies, which favors surface warming through a shoaling of the ocean mixed layer and decreased northward Ekman heat convergence. Broadly, these results suggest that climate model biases in long-term Antarctic sea-ice and global sea-surface temperature trends are related to each other and that eastern Pacific ENSO variability causes abrupt sea ice changes.