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Measurements of stable water isotopes in the atmospheric water vapour can be used to better understand the physical processes of the atmospheric water cycle. In polar regions, the atmospheric water vapour isotopic composition is a key parameter to understand the link between the precipitation and snow isotopic compositions and interpret isotope climate records from ice cores. In this study we present a novel 2.5-month accurate record of the atmospheric water vapour isotopic composition during the austral summer 2023–2024 (6 December 2023 to 14 February 2024) at Concordia Station (East Antarctica), from two laser spectrometers based on different measurement techniques, which are independently calibrated and both optimised to measure in low humidity environments. We show that both instruments accurately measure the summertime diurnal variability in the water vapour δ18O, δD, and d-excess, when the water vapour mixing ratio is consistently higher than 200 ppmv. We compare these measurements to outputs of the isotope-enabled atmospheric general circulation model LMDZ6-iso and show that the model exhibits biases in both the mean water vapour isotopic composition and the amplitude of the diurnal cycle, consistent with previous studies. Hence, this study provides a novel dataset of the atmospheric water vapour isotopic composition on the Antarctic Plateau, which can be used to evaluate isotope-enabled atmospheric general circulation models. The dataset is available on the public repository PANGAEA (https://doi.org/10.1594/PANGAEA.974597, Landais et al., 2024b).

In recent years, the Antarctic sea ice has experienced major changes, which are neither well understood nor adequately reproduced by Earth system models. To support model development with an aim to improve Antarctic sea ice and upper-ocean predictions, the impacts of updating the sea ice model and the atmospheric forcing are investigated. In the new MetROMS-UHel-v1.0 (henceforth MetROMS-UHel) ocean–sea ice model, the sea ice component has been updated from CICE5 to CICE6, and the forcing has been updated from ERA-Interim (ERAI) to ERA5 reanalyses. The two versions of MetROMS evaluated in this study use a version of the regional ROMS ocean model including ice shelf cavities. We find that the update of CICE (Community Ice CodE) and ERA reduced the negative bias of the sea ice area in summer. However, the sea ice volume decreases after the CICE update but increases when the atmospheric forcing is updated. As a net result after both updates, the modelled sea ice becomes thinner and more deformed, particularly near the coast. The ROMS ocean model usually yielded a deeper ocean mixed layer compared to observations. Using ERA5, the situation was slightly improved. The update from CICE5 to CICE6 resulted in a fresher coastal ocean due to a smaller salt flux from sea ice to the ocean. In the ice shelf cavities, the modelled melt rates are generally underestimated compared with observations, with the largest underestimation coming from the ice shelves in the too cold Amundsen and Bellingshausen seas as well as from the Australian sector in East Antarctica. These identified sea ice and oceanic changes vary seasonally and regionally. By determining sea ice and oceanic changes after the model and forcing updates and evaluating them against observations, this study informs modellers on improvements and aspects requiring attention with potential model adjustments.

Observations of water stable isotopes in Antarctic surface snow, precipitation and water vapor are key for improving our understanding of the atmospheric water cycle and past climate reconstructions from ice cores. In this study, we use isotopic observations in Antarctica to assess the skill of the isotope-enabled atmospheric general circulation model LMDZ6, nudged to ERA5 above the boundary layer (1980?2023 period). The model has no significant bias for time-mean temperature and snow accumulation over the ice sheet. Sensitivity test on parameterized supersaturation strength highlights its opposite effect on precipitation ${\delta }^{18}$O and d-excess. Selecting an intermediate supersaturation strength resulted in a minimal bias for surface snow ${\delta }^{18}$O across the continent, with a reduced but systematic positive bias in surface snow d-excess ( ${\sim} $5?). We then assessed seasonal and diurnal isotope variability with daily precipitation and continuous vapor isotopes at Dumont d?Urville (DDU, coastal station) and Concordia (inland station). On a seasonal scale, LMDZ6iso accurately reproduces the seasonal cycle of precipitation ${\delta }^{18}$O and d-excess at both stations. Moving from statistical evaluation to physical analysis, we use the individual process contributions to boundary-layer water vapor isotopes to identify the main drivers controlling the clear-sky isotopic daily cycles. At Concordia, daily isotope variations are mainly driven by surface sublimation, whereas at DDU they are driven by surface sublimation and advection by the katabatic flow. Our results suggest that to further improve water isotopes in LMDZ6iso, fractionation during surface sublimation should be included and fractionation at condensation for low temperature should be better constrained.

Snowfall is an important component of the mass balance of ice sheets and glaciers in Antarctica. In coastal Victoria Land (VL), changes to snowfall can impact ice masses, landscapes, and coastal ecosystems. Coastal VL is characterized by strong gradients in snowfall rates between the polar desert of the McMurdo Dry Valleys and the high accumulation in northern VL. Extreme precipitation events significantly contribute to total precipitation, with the largest contribution in the Terra Nova Bay area. We present a comprehensive analysis of snowfall dynamics in this region, using a Lagrangian moisture source diagnostic to study moisture sources and Self-Organizing Maps (SOM) to link these to different synoptic weather types. The moisture for snowfall in VL originates from the Southern Ocean, with more local sources in the Ross Sea embayment in summer when sea ice is reduced. We show a strong division in moisture sources between northern and southern VL, with the north receiving precipitation from moisture sources to the west and southern VL from the east. Precipitation in northern VL results from meridional transport of marine air from lower latitudes, while precipitation in southern VL is related to cyclonic disturbances in the Ross Sea that bring moisture from the east. Extreme precipitation in northern VL occurs during blocking highs that intensify meridional transport. Such intrusions of marine air, sometimes in the form of atmospheric rivers, do not impact the more isolated western Ross Ice Shelf and southern VL further in the Ross Sea embayment.

Meltwater ponding along the margins of Antarctica poses a threat to ice shelf stability, increasing the risk of accelerated inland ice mass loss. Understanding the key drivers of supraglacial lake formation is therefore essential for assessing the vulnerability and future stability of Antarctic ice shelves. In this study, we combine high-resolution simulation from the regional climate model Modèle Atmosphérique Régional (MAR) with satellite-derived records of supraglacial lakes in coastal Dronning Maud Land to investigate the role of topographic downslope winds on spatial lake distribution. We find that persistent katabatic winds and episodic foehn winds are key controls on the observed regional patterns of lakes. Katabatic winds, most persistent in eastern Dronning Maud Land, exert a sustained impact near grounding zones through snow erosion, scouring and sublimation. Foehn winds predominantly affect ice shelves on the lee (western) side of large ice rises and promontories, causing considerable surface warming. While these downslope winds directly contribute to surface melt and ponding during summer, they also precondition the surface year-round through wind-driven warming and sublimation. Statistical analysis of downslope wind exposure further allows us to identify other Antarctic ice shelves that may become vulnerable to future ponding as firn retention capacity is diminished.

This study compares CL51 ceilometer observations made at Scott Base, Antarctica, with statistics from the ERA5, JRA55, and MERRA2 reanalyses. To enhance the comparison we use a lidar instrument simulator to derive cloud statistics from the reanalyses which account for instrumental factors. The cloud occurrence in the three reanalyses is slightly overestimated above 3 km, but displays a larger underestimation below 3 km relative to observations. Unlike previous studies, we see no relationship between relative humidity and cloud occurrence biases, suggesting that the cloud biases do not result from the representation of moisture. We also show that the seasonal variation of cloud occurrence and cloud fraction, defined as the vertically integrated cloud occurrence, are small in both the observations and the reanalyses. We also examine the quality of the cloud representation for a set of weather states derived from ERA5 surface winds. The variability associated with grouping cloud occurrence based on weather state is much larger than the seasonal variation, highlighting weather state is a strong control of cloud occurrence. All the reanalyses continue to display underestimates below 3 km and overestimates above 3 km for each weather state. But the variability in ERA5 statistics matches the changes in the observations better than the other reanalyses. We also use a machine learning scheme to estimate the quantity of supercooled liquid water cloud from the ceilometer observations. Ceilometer low-level supercooled liquid water cloud occurrences are considerably larger than values derived from the reanalyses, further highlighting the poor representation of low-level clouds in the reanalyses.

The global overturning circulation (GOC) is the largest scale component of the ocean circulation, associated with a global redistribution of key tracers such as heat and carbon. The GOC generates decadal to millennial climate variability, and will determine much of the long-term response to anthropogenic climate perturbations. This review aims at providing an overview of the main controls of the GOC. By controls, we mean processes affecting the overturning structure and variability. We distinguish three main controls: mechanical mixing, convection, and wind pumping. Geography provides an additional control on geological timescales. An important emphasis of this review is to present how the different controls interact with each other to produce an overturning flow, making this review relevant to the study of past, present and future climates as well as to exoplanets’ oceans.

Sea ice is a composite solid material that sustains large fracture features at scales from meters to kilometres. These fractures can play an important role in coupled atmosphere-ocean processes. To model these features, brittle sea ice physics, via the Brittle-Bingham-Maxwell (BBM) rheology, has been implemented in the Lagrangian neXt generation Sea Ice Model (neXtSIM). In Arctic-only simulations, the BBM rheology has shown a capacity to represent observationally consistent sea ice fracture patterns and breakup across a wide range of time and length scales. Still, it has not been tested whether this approach is suitable for the modeling of Antarctic sea ice, which is thinner and more seasonal compared to Arctic sea ice, and whether the ability to reproduce sea ice fractures has an impact on simulating Antarctic sea ice properties. Here, we introduce a new 50-km grid-spacing Antarctic configuration of neXtSIM, neXtSIM-Ant, using the BBM rheology. We evaluate this simulation against observations of sea ice extent, drift, and thickness and compare it with identically-forced neXtSIM simulations that use the standard modified Elastic-Visco-Plastic (mEVP) rheology. In general, using BBM results in thicker sea ice and an improved correlation of sea ice drift with observations than mEVP. We suggest that this is related to short-duration breakup events caused by Antarctic storms that are not well-simulated in the viscous-plastic model.

Dynamical modeling is widely utilized for Antarctic sea ice prediction. However, the relative impact of initializing different model components remains unclear. We compare three sets of hindcasts of the Norwegian Climate Prediction Model (NorCPM), which are initialized by ocean, ocean/sea-ice, or atmosphere data and referred to as the OCN, OCNICE, and ATM hindcasts hereafter. The seasonal cycle of sea ice extent (SIE) in the ATM reanalysis shows a slightly better agreement with observations than the OCN and OCNICE reanalyzes. The trends of sea ice concentration (SIC) in the OCN and OCNICE reanalyzes compare well to observations, but the ATM reanalysis is poor over the western Antarctic. The OCNICE reanalysis yields the most accurate estimation of sea ice variability, while the OCN and ATM reanalyzes are comparable. Evaluation of the hindcasts reveals the predictive skill varies with region and season. Austral winter SIE of the western Antarctic can be skillfully predicted 12 months ahead, while the predictive skill in the eastern Antarctic is low. Austral winter SIE predictability can be largely attributed to high sea surface temperature predictability, thanks to skillful initialization of ocean heat content. The ATM hindcast from July or October performs best due to the effective initialization of sea-ice thickness, which enhances prediction skills until early austral summer via its long memory. Meanwhile, the stratosphere-troposphere coupling contributes to the prediction of springtime. The comparable skill between the OCN and OCNICE hindcasts implies limited benefits from SIC data on prediction when using ocean data.