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Through their role in buttressing upstream ice flow, Antarctic ice shelves play an important part in regulating future sea-level change. Reduction in ice-shelf buttressing caused by increased ocean-induced melt along their undersides is now understood to be one of the key drivers of ice loss from the Antarctic ice sheet. However, despite the importance of this forcing mechanism, most ice-sheet simulations currently rely on simple melt parameterisations of this ocean-driven process since a fully coupled ice–ocean modelling framework is prohibitively computationally expensive. Here, we provide an alternative approach that is able to capture the greatly improved physical description of this process provided by large-scale ocean-circulation models over currently employed melt parameterisations but with trivial computational expense. This new method brings together deep learning and physical modelling to develop a deep neural network framework, MELTNET, that can emulate ocean model predictions of sub-ice-shelf melt rates. We train MELTNET on synthetic geometries, using the NEMO ocean model as a ground truth in lieu of observations to provide melt rates both for training and for evaluation of the performance of the trained network. We show that MELTNET can accurately predict melt rates for a wide range of complex synthetic geometries, with a normalised root mean squared error of 0.11 m yr−1 compared to the ocean model. MELTNET calculates melt rates several orders of magnitude faster than the ocean model and outperforms more traditional parameterisations for > 96 % of geometries tested. Furthermore, we find MELTNET's melt rate estimates show sensitivity to established physical relationships such as changes in thermal forcing and ice-shelf slope. This study demonstrates the potential for a deep learning framework to calculate melt rates with almost no computational expense, which could in the future be used in conjunction with an ice sheet model to provide predictions for large-scale ice sheet models.

Through their role in buttressing upstream ice flow, Antarctic ice shelves play an important part in regulating future sea level change. Reduction in ice-shelf buttressing caused by increased ocean-induced melt along their undersides is now understood to be one of the key drivers of ice loss from the Antarctic Ice Sheet. However, despite the importance of this forcing mechanism most ice-sheet simulations currently rely on simple melt-parametrisations of this ocean-driven process, since a fully coupled ice-ocean modelling framework is prohibitively computationally expensive. Here, we provide an alternative approach that is able to capture the greatly improved physical description of this process provided by large-scale ocean-circulation models over currently employed melt-parameterisations but with trivial computational expense. We introduce a new approach that brings together deep learning and physical modelling to develop a deep neural network framework, MELTNET, that can emulate ocean model predictions of sub-ice shelf melt rates. We train MELTNET on synthetic geometries, using the NEMO ocean model as a ground-truth in lieu of observations to provide melt rates both for training and to evaluate the performance of the trained network. We show that MELTNET can accurately predict melt rates for a wide range of complex synthetic geometries and outperforms more traditional parameterisations for > 95 % of geometries tested. Furthermore, we find MELTNET's melt rate estimates show sensitivity to established physical relationships such as a changes in thermal forcing and ice shelf slope. This study demonstrates the potential for a deep learning framework to calculate melt rates with almost no computational expense, that could in the future be used in conjunction with an ice sheet model to provide predictions for large-scale ice sheet models.

The importance of resolving mesoscale air-sea interactions to represent cyclones impacting the East Coast of Australia, the so-called East Coast Lows (ECLs), is investigated using the Australian Regional Coupled Model based on NEMO-OASIS-WRF (NOW) at urn:x-wiley:2169897X:media:jgrd57355:jgrd57355-math-0001 resolution. The fully coupled model is shown to be capable of reproducing correctly relevant features such as the seasonality, spatial distribution and intensity of ECLs while it partially resolves mesoscale processes, such as air-sea feedbacks over ocean eddies and fronts. The mesoscale thermal feedback (TFB) and the current feedback (CFB) are shown to influence the intensity of northern ECLs (north of urn:x-wiley:2169897X:media:jgrd57355:jgrd57355-math-0002), with the TFB modulating the pre-storm sea surface temperature by shifting ECL locations eastwards and the CFB modulating the wind stress. By fully uncoupling the atmospheric model of NOW, the intensity of northern ECLs is increased due to the absence of the cold wake that provides a negative feedback to the cyclone. The number of ECLs might also be affected by the air-sea feedbacks but large interannual variability hampers significant results with short term simulations. The TFB and CFB modify the climatology of sea surface temperature (mean and variability) but no direct link is found between these changes and those noticed in ECL properties. These results show that the representation of ECLs, mainly north of urn:x-wiley:2169897X:media:jgrd57355:jgrd57355-math-0003, depend on how air-sea feedbacks are simulated. This is particularly important for atmospheric downscaling of climate projections as small-scale sea surface temperature interactions and the effects of ocean currents are not accounted for.

Large uncertainties in Antarctic sea level projections are related to ocean-driven melting (Seroussi et al., 2020; Jourdain et al., 2020; Reese et al., 2020; Edwards et al., in press) and the marine ice sheet instability (Robel et al., 2019). ‘Hindcasting’ simulations that follow the trajectory of the Antarctic Ice Sheet from pre-industrial conditions to present-day, are a useful tool to better constrain such uncertainties. We here perform historic simulations with the Parallel Ice Sheet Model. The simulations are forced by changes in the ocean and atmosphere from GCM output of CMIP5 as selected for ISMIP6 (Barthel et al., 2020). Sub-shelf melting is modeled using PICO (Olbers & Hellmer, 2010; Reese et al., 2018), with careful consideration of PICO’s parameters: the parameters for heat exchange across the ice ocean interface as well as the overturning strength are fitted with estimates of the melt sensitivity based on observations (Jenkins et al., 2018). Present-day observation of sub-shelf melting and mass loss inform parameter selection using an ensemble approach (Albrecht et al., 2020; Reese et al., 2020). The historic simulations provide an important basis to assess the future evolution and stability of Antarctic grounding lines. This work is done in the framework of the H2020 TiPACCs project.

The Marine Ice Sheet-Ocean Model Intercomparison Project (MISOMIP) is a community effort sponsored by the Climate and Cryosphere (CliC) project. MISOMIP aims to design and coordinate a series of MIPs—some idealized and realistic—for model evaluation, verification with observations, and future projections for key regions of the West Antarctic Ice Sheet (WAIS). The first phase of the project, MISOMIP1, was an idealized, coupled set of experiments that combined elements from the MISMIP+ and ISOMIP+ standalone experiments for ice-sheet and ocean models, respectively. These MIPs had 3 main goals: 1) to provide simplified experiments that allow model developers to compare their results with those from other models; 2) to suggest a path for testing components in the process of developing a coupled ice sheet-ocean model; and 3) to enable a large variety of parameter and process studies that branch off from these basic experiments.Here, we describe preliminary analysis of the MISOMIP1 results. Eight models in 14 configurations participated in the MIP. In keeping with analysis of the MISMIP+ experiment, we find that the choice of basal friction parameterizations in the ice-sheet component (Weertman vs. Coulomb limited) has a particularly significant impact on the rate of ice-sheet retreat but the choice of stress approximation (SSA, SSA* or L1Lx) seems to have little impact. Models with Coulomb-limited basal friction also tend to be those with the highest melt rates, confirming a positive feedback between melt and retreat in the MISOMIP1 configuration seen in previous work. The ocean component’s treatment of the boundary layer below the ice shelf also has a significant impact on melt rates and resulting retreat, consistent with findings based on ISOMIP+. Feedbacks between the components lead to localized features in the melt rates and the ice geometry not seen in standalone simulations, though the ~2-km horizontal and ~20-m vertical resolution of these simulations appears to be too coarse to produce long-lived, sub-ice-shelf channels seen at higher resolution.

International audience; Like many western boundary currents, the East Australian Current (EAC) extension is projected to get stronger and warmer in the future. The CMIP5 multimodel mean (MMM) projection suggests up to 5°C of warming under an RCP85 scenario by 2100. Previous studies employed Sverdrup balance to associate a trend in basin wide zonally integrated wind stress curl (resulting from the multidecadal poleward intensification in the westerly winds over the Southern Ocean) with enhanced transport in the EAC extension. Possible regional drivers are yet to be considered. Here we introduce the NEMO-OASIS-WRF coupled regional climate model as a framework to improve our understanding of CMIP5 projections. We analyze a hierarchy of simulations in which the regional atmosphere and ocean circulations are allowed to freely evolve subject to boundary conditions that represent present-day and CMIP5 RCP8.5 climate change anomalies. Evaluation of the historical simulation shows an EAC extension that is stronger than similar ocean-only models and observations. This bias is not explained by a linear response to differences in wind stress. The climate change simulations show that regional atmospheric CMIP5 MMM anomalies drive 73% of the projected 12 Sv increase in EAC extension transport whereas the remote ocean boundary conditions and regional radiative forcing (greenhouse gases within the domain) play a smaller role. The importance of regional changes in wind stress curl in driving the enhanced EAC extension is consistent with linear theory where the NEMO-OASIS-WRF response is closer to linear transport estimates compared to the CMIP5 MMM. Plain Language Summary In recent decades, enhanced warming, severe marine heatwaves, and increased transport by the East Australian Current have led to the invasion of nonnative species and the destruction of kelp forests east of Tasmania. The East Australian Current extension is projected to get stronger and warmer in the future. We seek to better understand coupled climate model projections for the Tasman Sea. This is difficult because there is large model diversity and considerable uncertainty as to how and where future changes will occur. In addition, little is known about the possible importance of regional versus large-scale changes in surface time-mean winds in driving future circulation changes. Here we use a single limited-domain ocean-atmosphere coupled model that takes the average model projections as its inputs and finds that changes in the regional wind stress are most important for the enhanced projected East Australian Current extension. We also find that these projected changes are consistent with simple linear theory and the simulated regional changes in wind stress.

The East Australian Current (EAC) plays a major role in regional climate, circulation, and ecosystems, but predicting future changes is hampered by limited understanding of the factors controlling EAC separation. While there has been speculation that the presence of New Zealand may be important for the EAC separation, the prevailing view is that the time‐mean partial separation is set by the ocean's response to gradients in the wind stress curl. This study focuses on the role of New Zealand, and the associated adjacent bathymetry, in the partial separation of the EAC and ocean circulation in the Tasman Sea. Here utilizing an eddy‐permitting ocean model (NEMO), we find that the complete removal of the New Zealand plateau leads to a smaller fraction of EAC transport heading east and more heading south, with the mean separation latitude shifting >100 km southward. To examine the underlying dynamics, we remove New Zealand with two linear models: the Sverdrup/Godfrey Island Rule and NEMO in linear mode. We find that linear processes and deep bathymetry play a major role in the mean Tasman Front position, whereas nonlinear processes are crucial for the extent of the EAC retroflection. Contrary to past work, we find that meridional gradients in the basin‐wide wind stress curl are not the sole factor determining the latitude of EAC separation. We suggest that the Tasman Front location is set by either the maximum meridional gradient in the wind stress curl or the northern tip of New Zealand, whichever is furthest north.

International audience; The East Australian Current (EAC), like many other subtropical western boundary currents, is believed to be penetrating further poleward in recent decades. Previous observational and model studies have used steady state dynamics to relate changes in the westerly winds to changes in the separation behavior of the EAC. As yet, little work has been undertaken on the impact of forcing variability on the EAC and Tasman Sea circulation. Here using an eddy-permitting regional ocean model, we present a suite of simulations forced by the same time-mean fields, but with different atmospheric and remote ocean variability. These eddy-permitting results demonstrate the nonlinear response of the EAC to variable, nonstationary inhomogeneous forcing. These simulations show an EAC with high intrinsic variability and stochastic eddy shedding. We show that wind stress variability on time scales shorter than 56 days leads to increases in eddy shedding rates and southward eddy propagation, producing an increased transport and southward reach of the mean EAC extension. We adopt an energetics framework that shows the EAC extension changes to be coincident with an increase in offshore, upstream eddy variance (via increased barotropic instability) and increase in subsurface mean kinetic energy along the length of the EAC. The response of EAC separation to regional variable wind stress has important implications for both past and future climate change studies.

Administration of activated protein C (APC) protects from renal dysfunction, but the underlying mechanism is unknown. APC exerts both antithrombotic and cytoprotective properties, the latter via modulation of protease-activated receptor-1 (PAR-1) signaling. We generated APC variants to study the relative importance of the two functions of APC in a model of LPS-induced renal microvascular dysfunction. Compared with wild-type APC, the K193E variant exhibited impaired anticoagulant activity but retained the ability to mediate PAR-1-dependent signaling. In contrast, the L8W variant retained anticoagulant activity but lost its ability to modulate PAR-1. By administering wild-type APC or these mutants in a rat model of LPS-induced injury, we found that the PAR-1 agonism, but not the anticoagulant function of APC, reversed LPS-induced systemic hypotension. In contrast, both functions of APC played a role in reversing LPS-induced decreases in renal blood flow and volume, although the effects on PAR-1-dependent signaling were more potent. Regarding potential mechanisms for these findings, APC-mediated PAR-1 agonism suppressed LPS-induced increases in the vasoactive peptide adrenomedullin and infiltration of iNOS-positive leukocytes into renal tissue. However, the anticoagulant function of APC was responsible for suppressing LPS-induced stimulation of the proinflammatory mediators ACE-1, IL-6, and IL-18, perhaps accounting for its ability to modulate renal hemodynamics. Both variants reduced active caspase-3 and abrogated LPS-induced renal dysfunction and pathology. We conclude that although PAR-1 agonism is solely responsible for APC-mediated improvement in systemic hemodynamics, both functions of APC play distinct roles in attenuating the response to injury in the kidney.