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Sea ice is an important and complex component of the Earth system and is considered a sensitive indicator of climate change. The seasonal sea ice cycle regulates the exchange of heat and salinity, altering the energy balance between high and low latitudes as well as the ocean and atmospheric circulation. The accurate representation of Antarctic sea ice has been considered a hot topic in the climate modelling community and lacks conclusive answers. In this paper, we evaluated the ability of 11 climate models from Coupled Model Intercomparison Project Phase 5 (CMIP5) and Phase 6 (CMIP6) to simulate the sea ice seasonal cycle in Antarctica in terms of area (SIA) and concentration (SIC), as well as the improvements in the most recent models' version, submitted to CMIP6. The results indicated that all models are able to accurately capture the seasonal cycle of the Antarctic SIA, with the minimum (maximum) occurring in February (September). In the Weddell Sea, Amundsen Sea, Bellingshausen Sea, and the Ross Sea, the simulated sea ice concentration revealed a large and systematic bias in February when compared to observations. In September, a large and systematic bias was found nearby the Southern Ocean's northern limit in the Polar Front. Several CMIP6 models exhibited slight improvements on the SIA and SIC estimate over the previous version (CMIP5). All models indicated a significant sea ice loss in the coming years as a response to CO2 forcing. Despite the advancements in the sea ice representation, our findings show that the models are still unable to accurately represent the regional sea ice changes [ABSTRACT FROM AUTHOR]

The surface mass balance (SMB) of large polar ice sheets and of snow and ice surfaces in general are incompletely understood because of the complexity of processes involved. One such process, drifting and blowing snow, has only been considered in a very simplified way in current meteorological and climatological models. To address this problem, the CRYOWRF model has been developed, a coupled model between the meteorological Weather Research and Forecasting model (WRF) and the snow model SNOWPACK, augmented by a detailed treatment of drifting and blowing snow. Applying CRYOWRF to the SMB of Antarctica, we find that the model reproduces measurements of SMB with similar errors than current models. Drifting and blowing snow and its sublimation play a particularly important role, especially in regions of strong katabatic winds. The CRYOWRF simulations are also in line with satellite estimates of blowing snow frequency. There is a need to further consolidate results by simulations with a higher grid resolution and by including more measurements of SMB contributions from snow fall to transport and sublimation. Plain Language Summary: Assessing current and predicting future sea level rise in connection with the general fate of our snow and ice masses on Earth requires understanding snow precipitation in extreme environments and the dynamics of snow on the surface. Over large parts of Antarctica, drifting and blowing snow and sublimation, which is the phase change of ice back to atmospheric vapor, are the only surface ablation processes and need therefore to be well quantified. With a new model, that shows similar performance to other models, we find that drifting and blowing snow and its sublimation play an important role for the snow mass balance especially in regions with strong winds. This has consequences not only for the snow mass balance alone but for the whole ice sheet dynamics as well as for estimating precipitation in these extreme environments. Key Points: Evaluation of the coupled Weather Research and Forecasting (WRF) and SNOWPACK model CRYOWRF, including a blowing snow module, shows reasonable representation of blowing snowBetter representation of atmospheric conditions at a station level by CRYOWRF compared to WRFBlowing snow is an important component of the Antarctic surface mass balance, especially in the katabatic regions of the continent [ABSTRACT FROM AUTHOR]

The Southern Ocean (SO) clouds exert a significant influence on the Earth's radiation budget. We analyzed ship‐based remote sensing observations of SO clouds over a 5‐month long Department of Energy (DOE) ARM Measurements of Aerosols, Radiation and Clouds over the Southern Oceans (MARCUS) field campaign to better understand cloud phase variability. We developed a method to classify eight categories of hydrometeors (ice, liquid, mixed phase, rain, drizzle, snow, aerosols, and clear sky) based on measurements of lidar, radar and radiosondes. Cloud thermodynamic phases (liquid, ice and mixed phase) at coarser scales were further derived to compare with the DOE Energy Exascale Earth System Model version 1 (E3SMv1) simulation and the Earth Model Column Collaboratory (EMC2) instrument simulator. For a scale‐aware comparison with climate model simulations, we found that spatially averaging the raw remote sensing data (e.g., backscatter and reflectivity) results in increased cloud cover and cloud liquid, whereas, directly averaging cloud phase from higher to lower resolution maintains clear air regions and is thus recommended for in‐cloud frequency comparisons. For cloud thermodynamic phases in stratiform clouds, the E3SMv1 underestimates cloud ice and overestimates cloud liquid at temperatures between −40°C and 0°C. When latitudes increase, both observations and simulations show a transition of dominant phase from liquid to ice for cloud tops as well as for the entire cloud columns, but the model underestimation of ice phase is more severe at higher latitudes. Such model bias is unlikely caused by spatial scale differences or lack of heterogeneity in cloud vertical structure in the simulation. Plain Language Summary: The Southern Ocean region of Earth consists of vast open waters with extensive cloud cover throughout the year. This cloud cover prevents the ocean water below it from absorbing solar heat and maintains global ocean and atmospheric circulation patterns. Thus, it is important to improve our understanding and our ability to model this cloud cover to better predict future changes in the Earth's climate. Here, we analyzed atmospheric data obtained by a ship traversing the open waters between Australia and Antarctica for nearly 5 months. We examined observed cloud properties such as cloud ice and liquid proportions and compared them with global climate model results. We found that the model simulates more liquid and less ice at lower temperatures when compared with observations. Such model bias becomes larger at higher latitudes, indicating that Earth's surface may absorb more solar radiation than the model estimates, especially around Antarctica. Both the observations and the model show that ice clouds are common at higher latitudes whereas liquid clouds are common at lower latitudes. Key Points: Cloud phase with respect to temperature and latitude over the Southern Ocean was identified using 5‐month ship‐based measurementsCompared with observed cloud phase, the E3SMv1 model underestimates ice and overestimates liquid phase between −40°C and 0°CObservations and simulations show similar transition from liquid to ice‐dominated cloud columns and cloud top layers from 43°S to 70°S [ABSTRACT FROM AUTHOR]

The performance of a set of atmospheric models and meteorological reanalyses in the representation of precipitation days in Antarctica is assessed using ground‐based observations such as a precipitation gauge and a Micro Rain Radar during the Year Of Polar Prediction Special Observing Period at Dumont d'Urville (November 2018–February 2019), East Antarctic coast. The occurrence of precipitation is overall well predicted, but the number of days and intensity with snowfall are overestimated by the models. This is reflected by high values of bias, probability of detection, and false alarm ratios, in particular for reanalyses, due to too frequent simulated precipitating days. The Heidke skill score shows the overall great contribution of the models in the forecasting of precipitating days, and the best performances are achieved by numerical weather prediction models. The chronology is better represented when the models benefit from the data assimilation of in‐situ observations, such as in reanalysis or weather forecasting models. Precipitation amounts at the surface are overestimated by most of the models. In addition, data from a ground‐based radar make it possible to evaluate the representation of the vertical profiles of snowfall rate. We can show that an excessive sublimation in the atmospheric boundary layer can compensate for overly strong precipitation flux in the mid and low troposphere. Therefore, the need to expand the measurement of precipitation across the atmospheric column using radars is highlighted, in particular in Antarctica where the cold cloud microphysics is poorly known and observations are particularly rare. [ABSTRACT FROM AUTHOR]

Intrusion of warm modified Circumpolar Deep Water (mCDW) is critical to heat transport onto the continental shelf around Antarctica, with substantial impacts on basal melting of ice shelves and sea ice production. We use hydrographic data collected in Prydz Bay, East Antarctica, and atmospheric and ocean reanalyses to investigate the seasonality of mCDW intrusions onto the East Antarctic continental shelf. Mooring measurements confirm that there is significant intrusion of mCDW over the inner continental shelf of Prydz Bay in March–July (austral autumn and early winter). The warming signal of intruded mCDW over the inner shelf is correlated with wind changes north of the shelf break, with a significant lag. This suggests that the autumn‐winter mCDW intrusions over the inner shelf are significantly affected by the wind regime north of the shelf break in January–May, when a southward displacement of the westerly winds occurs. The southward shift of westerly winds drives the shallowest depth of upwelled mCDW to move poleward and contributes more warm water to the shelf break. This results in the shoaling of mCDW near the shelf break in January–May and promotes mCDW intrusions onto the continental shelf. The dynamic barrier imposed on mCDW intrusions by the strong Antarctic Slope Front in January–May is offset by this shoaling of mCDW. This study indicates the strong sensitivity of continental shelves in East Antarctica to atmospheric forcing changes over the Southern Ocean. Plain Language Summary: Warm modified Circumpolar Deep Water (mCDW) from the Southern Ocean flows onto the continental shelf in many regions around Antarctica. These intrusions transport great amounts of heat to the continental shelves, affecting basal melting of ice shelves and sea ice formation. Data collected over the continental shelf of Prydz Bay, East Antarctica show that these intrusions occur seasonally. When we combine these observations with results from atmospheric model, we find that the strongest intrusion of mCDW over the inner shelf in March–July is related to the variability of westerly winds north of the shelf break in January–May. This is the period when the westerly winds over the Southern Ocean move southward. This causes the mCDW to become shallower near the shelf break and allows more warm water to flow to the inner shelf. Although an intensified Antarctic Slope Front in January–May should block the intrusion of mCDW, the blocking effect is overwhelmed by the shallowing of mCDW. Our findings provide insights into how seasonal variability of atmospheric forcing in the open ocean will affect warm water inflow and heat transport onto continental shelves in East Antarctica, and indicate potential effects of future changes in winds around Antarctica. Key Points: Warm mCDW intrusions in March–July in Prydz Bay are linked to the wind regime in January–May north of the shelf breakThe southward shift of westerly winds in January–May brings about the shoaling of mCDW over the shelf breakThe barrier effect of the strong Antarctic Slope Front on mCDW intrusions is offset by shoaling of mCDW in January–May [ABSTRACT FROM AUTHOR]

This study performs a comprehensive evaluation of the simulated cloud phase in the U.S. Department of Energy, Energy Exascale Earth System Model, atmosphere model version 2 (EAMv2), and version 1 (EAMv1). Enabled by the CALIPSO (Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observation) simulator, EAMv2 and EAMv1 predicted cloud phase is compared against the GCM‐Oriented CALIPSO Cloud Product (CALIPSO‐GOCCP) at high latitudes where mixed‐phase clouds are prevalent. Our results indicate that the underestimation of cloud ice in simulated high‐latitude mixed‐phase clouds in EAMv1 has been significantly reduced in EAMv2. The increased ice clouds in the Arctic mainly result from the modification on the WBF (Wegner‐Bergeron‐Findeisen) process in EAMv2. The impact of the modified WBF process is moderately compensated by the low limit of cloud droplet number concentration in cloud microphysics and the new dCAPE_ULL trigger used in deep convection in EAMv2. Moreover, it is found that the new trigger largely contributes to the better cloud phase simulation over the Norwegian Sea and Barents Sea in the Arctic and the Southern Ocean where large errors are found in EAMv1. However, errors in simulated cloud phase in EAMv1, such as the overestimation of supercooled liquid clouds near the surface in both hemispheres and the underestimation of ice clouds over Antarctica, persist in EAMv2. This study highlights the impact of deep convection parameterizations, which has received little attention, on high‐latitude mixed‐phase clouds, and the importance of continuous improvement of cloud microphysics in climate models for accurately representing mixed‐phase clouds. Key Points: EAMv2 largely improves cloud ice phase at high latitude regions, while biases in liquid phase shown in EAMv1 remainUpdated tuning parameters in Wegner‐Bergeron‐Findeisen process and deep convection are important for reduced negative bias in ice phase cloudsThe new dCAPE_ULL trigger in deep convection is responsible for the better cloud phase simulation over high‐latitude oceans [ABSTRACT FROM AUTHOR]

Sea level rise (SLR) is a long‐lasting consequence of climate change because global anthropogenic warming takes centuries to millennia to equilibrate for the deep ocean and ice sheets. SLR projections based on climate models support policy analysis, risk assessment and adaptation planning today, despite their large uncertainties. The central range of the SLR distribution is estimated by process‐based models. However, risk‐averse practitioners often require information about plausible future conditions that lie in the tails of the SLR distribution, which are poorly defined by existing models. Here, a community effort combining scientists and practitioners builds on a framework of discussing physical evidence to quantify high‐end global SLR for practitioners. The approach is complementary to the IPCC AR6 report and provides further physically plausible high‐end scenarios. High‐end estimates for the different SLR components are developed for two climate scenarios at two timescales. For global warming of +2°C in 2100 (RCP2.6/SSP1‐2.6) relative to pre‐industrial values our high‐end global SLR estimates are up to 0.9 m in 2100 and 2.5 m in 2300. Similarly, for a (RCP8.5/SSP5‐8.5), we estimate up to 1.6 m in 2100 and up to 10.4 m in 2300. The large and growing differences between the scenarios beyond 2100 emphasize the long‐term benefits of mitigation. However, even a modest 2°C warming may cause multi‐meter SLR on centennial time scales with profound consequences for coastal areas. Earlier high‐end assessments focused on instability mechanisms in Antarctica, while here we emphasize the importance of the timing of ice shelf collapse around Antarctica. This is highly uncertain due to low understanding of the driving processes. Hence both process understanding and emission scenario control high‐end SLR. Plain Language Summary: Taking a co‐production approach between scientists and practioners, we provide high‐end sea level rise (SLR) estimates for practitioner application based on an expert evaluation of physical evidence and approaches currently used in policy environments to understand high end risk. We do this for two global warming scenarios, a modest and a strong one, for two time slices 2100 and 2300. The large and growing differences between the scenarios beyond 2100 emphasize the long‐term benefits of mitigation. However, even a modest warming may cause multi‐meter SLR on centennial time scales with profound consequences for coastal areas. Earlier high‐end assessments focused on instability mechanisms in Antarctica, while here we emphasize the importance of the timing of ice shelf collapse around Antarctica as well as how practitioners use high end projections to frame risk. We stress that both emission scenario and limited physical understanding control the outcome. Key Points: A high‐end estimate of sea level rise in 2100 and 2300Decisionmaker/practitioner perspective on high‐endTiming of collapse of ice shelves critical [ABSTRACT FROM AUTHOR]

Prominent excursions in the number of cosmogenic nuclides (e.g., 10Be) around 774 CE/775 document the most severe solar proton event (SPE) throughout the Holocene. Its manifestation in ice cores is valuable for geochronology, but also for solar‐terrestrial physics and climate modeling. Using the ECHAM/MESSy Atmospheric Chemistry (EMAC) climate model in combination with the Warning System for Aviation Exposure to SEP (WASAVIES), we investigate the transport, mixing, and deposition of the cosmogenic nuclide 10Be produced by the 774 CE/775 SPE. By comparing the model results to the reconstructed 10Be time series from four ice core records, we study the atmospheric pathways of 10Be from its stratospheric source to its sink at Earth's surface. The reconstructed post‐SPE evolution of the 10Be surface fluxes at the ice core sites is well captured by the model. The downward transport of the 10Be atoms is controlled by the Brewer‐Dobson circulation in the stratosphere and cross‐tropopause transport via tropopause folds or large‐scale sinking. Clear hemispheric differences in the transport and deposition processes are identified. In both polar regions the 10Be surface fluxes peak in summertime, with a larger influence of wet deposition on the seasonal 10Be surface flux in Greenland than in Antarctica. Differences in the peak 10Be surface flux following the 774 CE/775 SPE at the drilling sites are explained by specific meteorological conditions depending on the geographic locations of the sites. Plain Language Summary: During large solar storms, high energy particles are hurled with enormous force toward Earth by the Sun. As these particles collide with atmospheric constituents (such as oxygen or nitrogen) unique nuclides of cosmogenic origin are formed in the higher atmosphere. From there they are transported downwards and finally precipitate at the surface due to different sink processes. Their imprints can be conserved over thousands of years within natural archives, such as ice cores or tree rings. Analysis of these natural archives around the globe indicates that the strongest solar storm over the last 10.000 years happened around 774 CE/775. This event is estimated to have been up to two orders of magnitude stronger, than the strongest known events documented for the satellite era. In this study, we model and analyze the transport and deposition of the cosmogenic nuclides produced by the extreme 774 CE/775 event, by applying a new experimental setup. Our results might help to interpret the fingerprints of historical extreme events with respect to the prevailing atmospheric conditions. Key Points: The modeled transport and deposition of the cosmogenic nuclide10Be produced by the 774/775 solar proton event was compared to 10Be ice core recordsHemispheric differences in stratospheric and cross‐tropopause transport, and deposition were identified, with polar summertime maxima of 10Be surface fluxDifferences in reconstructed10Be surface fluxes are explained by the local ratio of wet to dry deposition maximizing inthesummertime [ABSTRACT FROM AUTHOR]

Here, we compare the ocean overturning circulation of the early Eocene (47–56 Ma) in eight coupled climate model simulations from the Deep‐Time Model Intercomparison Project (DeepMIP) and investigate the causes of the observed inter‐model spread. The most common global meridional overturning circulation (MOC) feature of these simulations is the anticlockwise bottom cell, fed by sinking in the Southern Ocean. In the North Pacific, one model (GFDL) displays strong deepwater formation and one model (CESM) shows weak deepwater formation, while in the Atlantic two models show signs of weak intermediate water formation (MIROC and NorESM). The location of the Southern Ocean deepwater formation sites varies among models and relates to small differences in model geometry of the Southern Ocean gateways. Globally, convection occurs in the basins with smallest local freshwater gain from the atmosphere. The global MOC is insensitive to atmospheric CO2 concentrations from 1× (i.e., 280 ppm) to 3× (840 ppm) pre‐industrial levels. Only two models have simulations with higher CO2 (i.e., CESM and GFDL) and these show divergent responses, with a collapsed and active MOC, respectively, possibly due to differences in spin‐up conditions. Combining the multiple model results with available proxy data on abyssal ocean circulation highlights that strong Southern Hemisphere‐driven overturning is the most likely feature of the early Eocene. In the North Atlantic, unlike the present day, neither model results nor proxy data suggest deepwater formation in the open ocean during the early Eocene, while the evidence for deepwater formation in the North Pacific remains inconclusive. Plain Language Summary: The ocean's overturning circulation refers to the replenishment of the ocean's deep water by cold dense polar surface waters and its eventual return to the surface. It affects the climate through redistribution of heat across the globe and uptake of atmosphere carbon dioxide (CO2). Here, we explore the overturning circulation of the Early Eocene, a hot period 47–56 million years ago when atmosphere CO2 levels were similar to the "worst case" projections for the end of this century, in eight climate models setup up for that time. Our results, together with available ocean circulation sediment data for the time, indicate that during the early Eocene deep water originated predominantly from cold surface waters around Antarctica. The North Atlantic source of deep water that today contributes to European's relatively mild climate for its latitude, was completely absent at the time. Interestingly, even when the carbon dioxide in the Eocene model simulations was lowered to levels similar to today and before the industrial revolution, the North Atlantic source of deep water remains absent, indicating that it is the distribution of continents and ice‐sheets, rather than CO2 that is responsible for the difference between the modern and Eocene circulation. Key Points: This study evaluates the ocean's meridional overturning circulation during the early Eocene in eight models of the DeepMIP projectThe primary region of deep‐water formation depends both on the atmospheric freshwater flux and the strait geometry in the Southern OceanCompatible with proxy records, six of eight models show that deep waters predominantly originated from the south [ABSTRACT FROM AUTHOR]

The 2015 and 2020 ozone holes set record sizes in October–December. We show that these years, as well as other recent large ozone holes, still adhere to a fundamental recovery metric: the later onset of early spring ozone depletion as chlorine and bromine diminishes. This behavior is also captured in the Whole Atmosphere Chemistry Climate Model. We quantify observed recovery trends of the onset of the ozone hole and in the size of the September ozone hole, with good model agreement. A substantial reduction in ozone hole depth during September over the past decade is also seen. Our results indicate that, due to dynamical phenomena, it is likely that large ozone holes will continue to occur intermittently in October–December, but ozone recovery will still be detectable through the later onset, smaller, and less deep September ozone holes: metrics that are governed more by chemical processes. Plain Language Summary: The ozone hole that forms every spring in the Southern Hemisphere over Antarctica is expected to recover within the next 50 years. However, there have been several large ozone holes recently. In 2015, a record large volcanic eruption injected a large amount of sulfur into the upper atmosphere, which helps deplete ozone. In 2020, the Australian bushfires also injected a large amount of aerosol into the upper atmosphere, with a possible similar consequence. In this study, we show that by investigating a key time period in the early spring when the ozone hole is forming, the dynamical influence and the influence of volcanic and bushfire aerosols on ozone depletion over Antarctica is not as important and therefore ozone recovery can still be detected. Key Points: The seasonal onset of ozone depletion continues to slow down due to decreasing stratospheric chlorine and bromine concentrationsRecent large ozone holes of 2015, 2018, 2020, and 2021 display slower seasonal onset compared to 1999–2008 despite record sizes laterSeptember ozone hole size trends over 2000–2021 at different depth thresholds (such as 220, 175, 130 DU) indicate recovery [ABSTRACT FROM AUTHOR]

Tenuous atmospheric layers, such as high, thin cirrus clouds and blowing snow over Antarctica, play an important role in the climate system, affecting energy fluxes between the Earth and the atmosphere. Our knowledge of the structure of the atmosphere is largely derived from atmospheric satellite measurements. Yet tenuous layers can be hard to detect in satellite lidar data, especially in daylight data characterized by high solar background. In this study, we introduce an approach to detect tenuous atmospheric layers in the atmospheric lidar measurements of NASA's ICESat‐2. The density‐dimension algorithm for ICESat‐2 atmospheric data (DDA‐atmos) identifies atmospheric layers while automatically adapting to different background conditions of night, twilight, and daylight data. This capability, demonstrated for tenuous clouds and blowing snow, offers a data‐based solution to an important climate modeling problem. Atmospheric layer boundaries, detection confidence, and density fields resultant from the DDA‐atmos are reported in ICESat‐2 atmospheric data product ATL09. Plain Language Summary: Tenuous atmospheric layers, such as high, thin cirrus clouds and blowing snow over Antarctica, play an important role in the climate system, because they affect energy fluxes between the Earth and the atmosphere. Our knowledge of the structure of the atmosphere is largely derived from atmospheric satellite measurements. Yet tenuous layers can be hard to detect in satellite lidar data, especially in daylight data characterized by high solar background, which results in high noise. In this study, we introduce an approach to detect tenuous atmospheric layers in the atmospheric lidar measurements of NASA's Ice, Cloud and land Elevation Satellite ICESat‐2. To this end, we develop a mathematical algorithm, the density‐dimension algorithm for ICESat‐2 atmospheric data, that identifies atmospheric layers while automatically adapting to different background conditions of night, twilight, and daylight data. The resultant capability to detect thin clouds and blowing snow in ICESat‐2 data offers a data‐based solution to an important climate modeling problem. The results are publicly available on the ICESat‐2 atmospheric data product ATL09. Key Points: The atmospheric channel of ICESat‐2 measures tenuous clouds and blowing snowThe density‐dimension algorithm for atmospheric data detects tenuous layers while automatically adapting to night and daylight conditionsThis capability offers a data‐based solution to including tenuous clouds in atmospheric climate models [ABSTRACT FROM AUTHOR]

Projections of the sea level contribution from the Greenland and Antarctic ice sheets (GrIS and AIS) rely on atmospheric and oceanic drivers obtained from climate models. The Earth System Models participating in the Coupled Model Intercomparison Project phase 6 (CMIP6) generally project greater future warming compared with the previous Coupled Model Intercomparison Project phase 5 (CMIP5) effort. Here we use four CMIP6 models and a selection of CMIP5 models to force multiple ice sheet models as part of the Ice Sheet Model Intercomparison Project for CMIP6 (ISMIP6). We find that the projected sea level contribution at 2100 from the ice sheet model ensemble under the CMIP6 scenarios falls within the CMIP5 range for the Antarctic ice sheet but is significantly increased for Greenland. Warmer atmosphere in CMIP6 models results in higher Greenland mass loss due to surface melt. For Antarctica, CMIP6 forcing is similar to CMIP5 and mass gain from increased snowfall counteracts increased loss due to ocean warming. Plain Language Summary: The melting of the Greenland and Antarctic ice sheets (GrIS and AIS) will result in higher sea level in the future. How sea level will change depends in part on how the atmosphere and ocean warm and how this affects the ice sheets. We use multiple ice sheet models to estimate possible future sea levels under climate scenarios from the models participating in the new Coupled Model Intercomparison Project phase 6 (CMIP6), which generally indicate a warmer world that the previous effort (CMIP5). Our results show that the possible future sea level change due Antarctica is similar for CMIP5 and CMIP6, but the warmer atmosphere in CMIP6 models leads to higher sea‐level contributions from Greenland by the end of the century. Key Points: We compare results from an ice sheet model inter‐comparison forced using Coupled Model Intercomparison Project phase 6 and phase 5 climate projectionsProjected sea level at 2100 is higher for Greenland under CMIP6 scenarios than CMIP5, but similar for Antarctica under both scenariosCMIP6 warmer climate results in increased Greenland surface melt while increased snowfall mitigates loss from ocean warming for Antarctica [ABSTRACT FROM AUTHOR]

While most precipitation in Antarctica falls as snow, little is known about liquid precipitation, although it can have ecological and climatic impacts. This study combines meteorological reports at 10 stations with the ERA5 reanalysis to provide a climatological characterization of rainfall occurrence over Antarctica. Along the East Antarctic coast, liquid precipitation occurs 22 days per year at most and coincides with maritime intrusions and blocking anticyclones. Over the north‐western Antarctic Peninsula, rainfall occurs more than 50 days per year on average and the recent summer cooling was accompanied by a decrease of −35 annual rainy days per decade between 1998 and 2015 at Faraday‐Vernadsky. Projections from seven latest‐generation climate models reveal that Antarctic coasts will experience a warming and more frequent and intense rainfall by the end of the century. Rainfall is expected to impact new regions of the continent, increasing their vulnerability to melting by the preconditioning of surface snow. Plain Language Summary: Given the cold temperatures prevailing across the continent, most precipitation over Antarctica falls as snow. Nonetheless, infrequent rainfall events have already been observed causing serious damage to penguin colonies and facilitating the melting of the snow on the ground surface. Here, we provide the first climatological characterization of rainfall occurrence over Antarctica by examining reports of visual meteorological observations at 10 Antarctic stations. We can evidence the contrast between the coasts of East and West Antarctica that experience a few days per year with liquid precipitation and the western part of the Antarctic Peninsula where rainfall occurs more than 50 days per year on average. The latter region also experienced a significant decrease in rainfall occurrence during the first 15 years of the 21st century. Simulations with latest generation numerical climate models further reveal that the Antarctic continent is projected to undergo an overall warming accompanied by more frequent and more intense rainfall events at the end of century. Rainfall is also expected to impact regions of the continent that currently do not receive rainfall, making them vulnerable to intense events of surface snow melting preceded by liquid precipitation. Key Points: First climatological characterization of rainfall occurrence in Antarctica based on meteorological reports and atmospheric reanalysesRain events generally coincide with a warm and moist maritime intrusion and a blocking anticycloneCMIP6 scenarios suggest that the overall future warming of Antarctica will be accompanied by more frequent and more intense rainfall events [ABSTRACT FROM AUTHOR]

Climate models exhibit major radiative biases over the Southern Ocean owing to a poor representation of mixed‐phase clouds. This study uses the remote‐sensing dataset from the Measurements of Aerosols, Radiation and Clouds over the Southern Ocean (MARCUS) campaign to assess the ability of the Weather Research and Forecasting (WRF) model to reproduce frontal clouds off Antarctica. It focuses on the modeling of thin mid‐level supercooled liquid water layers which precipitate ice. The standard version of WRF produces almost fully glaciated clouds and cannot reproduce cloud top turbulence. Our work demonstrates the importance of adapting the ice nucleation parameterization to the pristine austral atmosphere to reproduce the supercooled liquid layers. Once simulated, droplets significantly impact the cloud radiative effect by increasing downwelling longwave fluxes and decreasing downwelling shortwave fluxes at the surface. The net radiative effect is a warming of snow and ice covered surfaces and a cooling of the ocean. Despite improvements in our simulations, the local turbulent circulation related to cloud‐top radiative cooling is not properly reproduced, advocating for the need to develop a parameterization for top‐down convection to capture the turbulence‐microphysics interplay at cloud top. Plain Language Summary: Among the major shortcomings of climate models is a poor representation of clouds over the Southern Ocean. Thanks to new measurements from the Measurements of Aerosols, Radiation and Clouds over the Southern Ocean campaign that took place aboard the Aurora Australia ice breaker, we can now better assess the ability of models to represent clouds off Antarctica. In particular, we focus here on clouds that are mostly composed of ice crystals but that are topped by a thin layer of so‐called "supercooled" liquid droplets that form at temperatures below zero Celsius. While the standard version of the model produces clouds composed only of ice, we show that by adapting the formulation of ice crystal formation to the very pristine atmospheric conditions peculiar to the Southern Ocean it is possible to successfully reproduce thin layers of supercooled liquid droplets observed in mixed‐phase clouds. The latter significantly changes how much sunlight these clouds reflect to space, which is critical to understanding the climate. Compared to ice crystals, liquid droplets tend to reflect more solar energy toward space and at the same time, they enhance the cloud infrared emission toward the surface of the Antarctic ice sheet. Key Points: Weather Research and Forecasting‐observation comparison during Measurements of Aerosols, Radiation and Clouds over the Southern Ocean shows the inability of the model in standard configurations to simulate austral mixed‐phase cloudsA parameterization of ice nucleation based on new ice nucleating particle measurements improves the simulation of supercooled liquid water near cloud topFurther parameterization developments targeting the convection at cloud top are needed to reproduce the turbulence‐microphysics interplay [ABSTRACT FROM AUTHOR]

A suite of chemistry‐climate model simulations, forced by pairs of anthropogenic forcings [comprising greenhouse gases (GHGs), ozone depleting substances (ODSs), or aerosols], were employed to investigate whether the high‐latitude Southern Hemisphere (SH) circulation response to these forcings is linearly additive, a common assumption in attribution studies. We find that the geographical pattern of sea‐level pressure (SLP) response to a combination of GHGs and ODSs is linearly additive. However, we find significant differences in the SLP response when combining GHGs and aerosols compared to the sum of the individual forcings, a non‐additivity that is currently masked by the dominance of the ODSs forcing. This non‐linearity also results in changes to the SH split jet. These results were obtained using a coupled chemistry‐climate model, indicating that the non‐linear response is due to chemical interactions between the forcing agents. As such, future simulations investigating a post‐ozone hole Southern Hemisphere climate should consider this chemical interaction. [ABSTRACT FROM AUTHOR]

In spite of the unabated emissions of greenhouse gases into the atmosphere, sea ice around Antarctica has increased over most of the satellite era. Such an increase is not captured by climate models, which simulate a melting over the same period. Over the last few years, moreover, the observed sea ice trends have drastically changed, and this might act to cancel the models‐observations discrepancy. Here we show that in spite of the very recent Antarctic sea ice trend changes, such discrepancy still exists. Analyzing multiple large ensembles of model simulations, we elucidate the origin of the models‐observations discrepancy. We show that internal variability cannot account for the discrepancy, which therefore is likely to stem from biases in the models' forced response to the external forcing. These biases, we show, reside in thermodynamic ocean‐atmosphere coupling, as models fail to simulate the trends in surface heat fluxes from reanalyses over the period 1979–2019. Key Points: In spite of the Antarctic sea ice loss reported in recent years, climate models still fail to capture the observed sea ice trendThe source of discrepancy resides in the models' forced response, not in their ability to capture the internal variabilityThe models' inability to capture the observed sea ice trends is associated with a bias in simulating recent surface heat flux trends [ABSTRACT FROM AUTHOR]

Fully coupled climate models have long shown a wide range of Antarctic sea ice states and evolution over the satellite era. Here, we present a high‐level evaluation of Antarctic sea ice in 40 models from the most recent phase of the Coupled Model Intercomparison Project (CMIP6). Many models capture key characteristics of the mean seasonal cycle of sea ice area (SIA), but some simulate implausible historical mean states compared to satellite observations, leading to large intermodel spread. Summer SIA is consistently biased low across the ensemble. Compared to the previous model generation (CMIP5), the intermodel spread in winter and summer SIA has reduced, and the regional distribution of sea ice concentration has improved. Over 1979–2018, many models simulate strong negative trends in SIA concurrently with stronger‐than‐observed trends in global mean surface temperature (GMST). By the end of the 21st century, models project clear differences in sea ice between forcing scenarios. Plain Language Summary: Coupled climate models are complex computer programs that simulate the interaction of the atmosphere, ocean, land surface, and cryosphere. An important feature of the Southern Ocean is its sea ice cover, which typically expands in winter to cover an area comparable to that of Russia. Climate models have shown very different amounts of Antarctic sea ice coverage and very different trajectories of sea ice change in response to expected greenhouse gas emissions. This year, new coupled climate models released under the Coupled Model Intercomparison Project (CMIP6) will form the basis of the next IPCC assessment report. Here, we compare output from those models to satellite observations of the areal coverage of sea ice. As a whole, the models successfully capture some elements of the observed seasonal cycle of sea ice but underestimate the summer minimum sea ice area. Compared to results from the previous model generation (CMIP5), the range across models has reduced, and the location of sea ice agrees better with observations. Models project sea ice loss over the 21st century in all scenarios, but confidence in the rate of loss is limited, as most models show stronger global warming trends than observed over the recent historical period. Key Points: CMIP6‐mean Antarctic sea ice area is close to observations, but intermodel spread remains substantialWe find modest improvements in the simulation of sea ice area and concentration compared to CMIP5Most CMIP6 models simulate sea ice losses and stronger‐than‐observed GMST trends over 1979–2018 [ABSTRACT FROM AUTHOR]

Dynamical dependence between key observables and the surface mass balance (SMB) over Antarctica is analyzed in two historical runs performed with the MPI‐ESM‐P and the CESM1‐CAM5 climate models. The approach used is a novel method allowing for evaluating the rate of information transfer between observables that goes beyond the classical correlation analysis and allows for directional characterization of dependence. It reveals that a large proportion of significant correlations do not lead to dependence. In addition, three coherent results concerning the dependence of SMB emerge from the analysis of both models: (i) The SMB over the Antarctic Plateau is mostly influenced by the surface temperature and sea ice concentration and not by large‐scale circulation changes; (ii) the SMB of the Weddell Sea and the Dronning Maud Land coasts are not influenced significantly by the surface temperature; and (iii) the Weddell Sea coast is not significantly influenced by the sea ice concentration. Key Points: The analysis of the rate of information transfer allows for clarifying dynamical dependence beyond the classical correlation analysisThe surface mass balance over the Plateau, the central part of Antarctica, is mainly influenced by temperature and sea ice concentrationThe surface mass balance on the Weddell sea and Dronning Maud Land coasts displays a dynamics with a large influence of global‐scale modes [ABSTRACT FROM AUTHOR]

The authors present a description of the climate model CM4.0 from the U.S. Geophysical Fluid Dynamics Laboratory. They mention the design of the model with land, atmosphere, and ocean components, the simulation quality of the El Niño and Madden-Julian oscillations, and discuss some potential weaknesses such as inaccurate Antarctic sea ice simulation.

Current chemistry climate models do not include polar emissions and chemistry of halogens. This work presents the first implementation of an interactive polar module into the very short‐lived (VSL) halogen version of the Community Atmosphere Model with Chemistry (CAM‐Chem) model. The polar module includes photochemical release of molecular bromine, chlorine, and interhalogens from the sea‐ice surface, and brine diffusion of iodine biologically produced underneath and within porous sea‐ice. It also includes heterogeneous recycling of inorganic halogen reservoirs deposited over fresh sea‐ice surfaces and snow‐covered regions. The polar emission of chlorine, bromine, and iodine reach approximately 32, 250, and 39 Gg/year for Antarctica and 33, 271, and 4 Gg/year for the Arctic, respectively, with a marked seasonal cycle mainly driven by sunlight and sea‐ice coverage. Model results are validated against polar boundary layer measurements of ClO, BrO, and IO, and satellite BrO and IO columns. This validation includes satellite observations of IO over inner Antarctica for which an iodine "leapfrog" mechanism is proposed to transport active iodine from coastal source regions to the interior of the continent. The modeled chlorine and bromine polar sources represent up to 45% and 80% of the global biogenic VSLCl and VSLBr emissions, respectively, while the Antarctic sea‐ice iodine flux is ~10 times larger than that from the Southern Ocean. We present the first estimate of the contribution of polar halogen emissions to the global tropospheric halogen budget. CAM‐Chem includes now a complete representation of halogen sources and chemistry from pole‐to‐pole and from the Earth's surface up to the stratopause. Plain Language Summary: We present the first implementation of an interactive polar module into the halogen version of the Community Atmosphere Model with Chemistry (CAM‐Chem) model with the intention of expanding the model applicability to the polar regions, besides its wide usage for atmospheric studies throughout the tropics and midlatitudes. The state‐of‐the‐art polar module considers full gas‐phase and heterogeneous inorganic chlorine, bromine, and iodine chemistry and sources, which add up to the organic halogen emissions from the ocean surface (the so‐called very short‐lived substances, VSL). The online sea‐ice halogen sources depend on the seasonal variation of different types of icy surfaces and the intensity of radiation reaching the polar surface. Our results indicate that the contribution of polar halogen sources represents between 45% and 80% of the global biogenic VSL chlorine and bromine emissions, respectively; and that the Antarctic iodine sea‐ice annual flux is ~10 times larger than the total iodine source arising from the Southern Ocean. This work provides, for the first time, quantitative estimates of the annual and seasonal flux strength of each halogen family from the Arctic and Antarctic, as well as their contribution to the global tropospheric halogen budget, highlighting the importance of including the contribution of polar tropospheric halogens in global chemistry‐climate models. Key Points: The contribution of polar sea‐ice sources to the global tropospheric halogen budget has been computed using the CAM‐Chem modelThe annual halogen flux from the sea‐ice surface represents between 45% and 80% of the global chloro‐ and bromo‐carbon oceanic VSL emissionsIn Antarctica, the annual iodine sea‐ice flux is ~10 times larger than the oceanic inorganic iodine source [ABSTRACT FROM AUTHOR]

As the first mature global ocean general circulation model based on unstructured‐mesh methods, the multiresolution Finite Element Sea ice‐Ocean Model (FESOM) has shown great capability in reconstructing the ocean and sea ice in both standalone and coupled simulations at a relatively low computational cost. Parameterizations of some important processes, including the vertical mixing induced by surface waves, however, are still missing, contributing to temperature biases in the upper ocean. In this work we incorporate the vertical mixing induced by nonbreaking surface waves derived from a wave model into FESOM and compare its effect with that of shortwave penetration, another key process to vertically redistribute the heat in the upper ocean. Numerical experiments with and without the shortwave penetration scheme and the nonbreaking surface wave mixing reveal that both processes ameliorate the simulation of upper‐ocean temperature in middle and low latitudes mainly on the summer hemisphere. The role of nonbreaking surface waves is more pronounced in decreasing the mean cold biases at 50 m (by 1.0 °C, in comparison to 0.5 °C achieved by applying shortwave penetration). We conclude that the incorporation of mixing induced by nonbreaking surface waves into FESOM is practically very helpful and suggest that it needs to be considered in other ocean climate models as well. Plain Language Summary: Nowadays, numerical ocean, weather, and climate forecasts play an important role in the daily life of human beings. An accurate prediction could help us prepare day‐to‐day activities orderly. However, the prediction ability has been much lower than expected. As an example, ocean models often simulate a warmer sea surface temperature and cooler subsurface (30–100 m deep) temperature in subtropical oceans, especially in summer, which can lead to big errors in the weather and climate forecasting. This situation was partly alleviated by distributing solar radiation in the upper ocean rather than only heating up the ocean surface. Although shortwave penetration makes some improvement on ocean model performance, it is still far from solving the common simulated temperature bias in the upper ocean. The simulated temperature is considerably improved by incorporating the mixing induced by nonbreaking surface waves into the new generation ocean model FESOM. It turns out that the nonbreaking wave is more capable in ameliorating the simulated upper‐ocean temperature than the shortwave penetration. Key Points: Both nonbreaking surface wave and shortwave penetration can enhance the temperature simulation of the upper oceanModel improvement due to nonbreaking wave is more considerable than shortwave penetration, especially in subsurface oceanThe regions where nonbreaking wave generates stronger improvement are where large temperature bias exist [ABSTRACT FROM AUTHOR]

On 30th January 1982, the research station on Signy Island (South Orkney Islands) reported a daily maximum temperature of 19.8 °C. This is a record maximum for any station south of 60°S. We use surface observations, atmospheric reanalyses and high-resolution atmospheric model simulations to investigate the drivers of this extreme event. At the time of the record temperature exceptionally warm air was being advected southwards towards the South Orkney Islands from the subtropical South Atlantic. This air mass cooled significantly at levels below 1 km during its long track over the cold Southern Ocean but remained relatively warm above this level. Atmospheric model simulations show that warm air from upper levels was brought down towards the surface over Signy Island in a föhn wind generated by northerly flow over Coronation Island, a mountainous island just to the north of Signy Island. Modelled temperatures over Signy Island are in good agreement with observations and thus support the hypothesis that the record temperature was caused by a combination of exceptional warm advection with conditions suitable for the generation of föhn. Since conditions conducive to föhn occur relatively frequently, föhn warming may have a significant influence on the local climate and ecology of Signy Island. [ABSTRACT FROM AUTHOR]