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The future evolution of the West Antarctic Ice Sheet (WAIS) will strongly influence the global sea-level rise in the coming decades. Ice shelf melting in that sector is partly controlled by the low-pressure system located off the West Antarctic coast, namely the Amundsen Sea Low (ASL). When the ASL is deep, an overall increase in ice shelf melting is noticed. Because of the sparse observational network and the strong internal variability, our understanding of the long-term climate changes in the atmospheric circulation is limited, and therefore its impact on ice melting as well. Among all the processes involved in the West Antarctic climate variability, an increasing number of studies have pointed out the strong impact of the climate in the tropical Pacific. However, most of those studies focus on the past decades, which prevents the analysis of the role of the multi-decadal tropical variability on the West Antarctic climate. Here, we combine annually-resolved paleoclimate records, in particular ice core and coral records, and the physics of climate models through paleoclimate data assimilation to provide a complete spatial multi-field reconstruction of climate variability in the tropics and Antarctic. This allows for studying both the year-to-year and multi-decadal variability of the tropical-Antarctic teleconnections. As data assimilation provides a climate reconstruction that is dynamically constrained, the contribution of the tropical variability on the West Antarctic climate changes can be directly assessed. Our results indicate that climate variability in the tropical Pacific is the main driver of ASL variability at the multi-decadal time scale, with a strong link to the Interdecadal Pacific Oscillation (IPO). However, the deepening of the Amundsen Sea Low over the 20th century cannot be explained by tropical climate variability. By using large ensembles of climate model simulations, our analysis suggests anthropogenic forcing as the primary driver of this 20th century ASL deepening. In summary, the 20th century ASL deepening is explained by the forcing, but the multi-decadal variability related to the IPO is superimposed on this long-term trend.

Although the West Antarctic surface climate has experienced large changes over the past decades with widespread surface warming, an overall increase in snow accumulation and a deepening of the Amundsen Sea Low, the exact role of human activities in these changes has not yet been fully investigated, which limits confidence in future projections. Here, we perform a detection and attribution analysis using instrumental and proxy-based reconstructions, and two large climate model simulation ensembles to quantify the forced response in these observed changes. We show that surface climate changes since the 1950s were driven by anthropogenic forcing, in particular the greenhouse gas forcing and stratospheric ozone depletion. Therefore, our results indicate that the 21st century changes will depend on both the greenhouse gas emissions and the ozone layer recovery.

The future evolution of the Antarctic Ice Sheet (AIS), particularly the West Antarctic Ice Sheet (WAIS), will strongly influence global sea-level rise during the 21st century and beyond. However, because of the sparse observational network in concert with the strong internal variability, our understanding of the long-term climate and ice sheet changes in the Antarctic is limited. Among all the processes involved in Antarctic climate variability and change, an increasing number of studies have pointed out the strong relationship between the climate in the tropics and Antarctic (also called tropical-Antarctic teleconnections), especially between the Pacific Ocean and the West Antarctic region. Most of those studies focus only on the past decades, but to fully understand the long-term Antarctic climate changes associated with tropical variability longer time-series are needed. This is achieved here by using annually-resolved paleoclimate records (ice core and coral records) that cover at least the last two centuries to study both the year-to-year and multi-decadal variability of tropical-Antarctic teleconnections. These records are incorporated into a data assimilation framework that optimally combines the paleoclimate records with the physics of the climate model. As data assimilation provides a climate reconstruction that is dynamically constrained – through the spatial covariance in the climate model – the contribution of tropical variability on Antarctic climate changes can be directly assessed. Different sensitivity tests are performed to isolate the contribution of each tropical basin. Additionally, the roles of multi-decadal and year-to-year variability are compared by averaging the annual paleoclimate records at a lower temporal resolution. This new method of combining the two time-scales is proposed in order to preserve the multi-decadal variability in the annual climate reconstruction.

The climate of the polar regions is characterized by large fluctuations and has experienced dramatic changes over the past decades. In particular, the patterns of changes in sea ice and ice sheet mass are complex in the Southern Hemisphere. The Antarctic Ice Sheet has also lost mass in the past decades, especially in Western Antarctica, with a spectacular thinning and weakening of ice shelves, i.e., the floating extensions of the grounded ice sheet. Despite recent advances in observing and modelling the Antarctic climate, the mechanisms behind this long-term mass loss remain poorly understood because of the limited amount of observations and the large biases of climate models in polar regions, in concert with the large internal variability prevailing in the Antarctic. Among all the processes involved in the mass variability, changes in the general atmospheric circulation of the Southern Hemisphere may have played a substantial role. One of the most important atmospheric modes of climate variability in the Southern Ocean is the Southern Annular Mode (SAM), which represents the position and the strength of the westerly winds. During years with a positive SAM index, lower sea level pressure at high latitudes and higher sea level pressure at low latitudes occur, resulting in a stronger pressure gradient and intensified Westerlies. However, the current knowledge of the impact of these fluctuations of the Westerlies on the Antarctic cryosphere is still limited. Over the past few years, some efforts investigated the impact of the SAM on the Antarctic sea ice and the surface mass balance of the ice sheet from an atmosphere-only perspective. Recently, a few oceanic studies have focused on the local impact of SAM-related fluctuations on the ice-shelf basal melt in specific regions of Antarctica, particularly Western Antarctica. However, to our knowledge, there is no such study at the scale of the whole Antarctic continent. In this study, we performed idealized experiments with a pan-Antarctic regional ice-shelf cavity-resolving ocean - sea-ice model for different phases of the SAM. We show that positive (negative) phases lead to increased (decreased) upwelling and subsurface ocean temperature and salinity close to ice shelves. A one-standard-deviation increase of the SAM leads to a net basal mass loss of 40 Gt yr-1, with strong regional contrasts: increased melt in the Western Pacific and Amundsen-Bellingshausen sectors and the opposite response in the Ross sector. Taking these as a baseline sensitivity, we estimate last millennium and end-of-21st-century ice-shelf basal melt changes due to SAM of -60.7 Gt yr-1 and 1.8 to 26.8 Gt yr-1 (depending on the emission scenario considered), respectively, compared to the present.

The agreement between simulated and reconstructed multidecadal to centennial climate variability has improved over the past decades. However, significant disagreements still exist, especially at regional scale. In the Southern Ocean, both reconstructions and climate models display large variability at those timescales but models fail in reproducing some key elements such as the centennial variability in the strength of the westerly winds inferred from various types of proxy data. Data assimilation combines in an optimal way information from proxy data and climate models. It can help in identifying the cause of such model-data mismatch by improving the reconstructions as well as by testing the compatibility of those reconstructions with model physics or between different types of proxy data. Two examples will be discussed here. The first one focuses on the shift in the westerly winds between the 14th and 16th century, showing that it is clear in reconstructions based on classical statistical methods and on data assimilation but it is not simulated in models without data assimilation. In the second example, we will discuss the deep ocean convection and open ocean formation in the Southern Ocean that induce large multi-decadal to centennial variability in some global models while it is totally absent in many others. We will check how data assimilation can be used to test the validity of the simulations and to determine which model behavior is the most realistic.

Reconstructions of Antarctic surface air temperature (SAT) covering the past two millennia include some large centennial variabilities that are still not well understood because of the model-data discrepancies. Paleoenvironmental and instrumental observations have highlighted strong interconnections in the Antarctic climate system as illustrated by close relationships between atmosphere and ocean (including sea ice) at all time scales. For instance, over past decades, the Amundsen Sea Low pressure (ASL) is associated with opposite regional sea ice changes in the Bellingshausen-Amundsen and Ross sea sector as well as with variations in snow accumulation over West Antarctica. This inspires us to explore the potentiality of better reconstructing and understanding the drivers of the centennial-scale variability of Antarctic SAT during the Common Era by taking advantage of those links between the Antarctic continental and the Southern Ocean data. To this end, we have compiled proxy-based sea surface temperature reconstructions for the Southern Ocean and qualitative sea-ice reconstructions around Antarctica, together with those having published ice-core based water isotopic and snow accumulation records. We first analyze the continent-ocean relationships by constraining the climate model with continental records through a data assimilation procedure. Results show that we are able to generally reproduce reconstructed variations in the Southern Ocean at centennial scale, particularly for sea surface temperature (SST) along the south Chilean coast and sea ice along the Antarctic Peninsula. In a second step, experiments with data assimilation combining both oceanic and continental records help us to determine how the inclusion of oceanic records improves the reconstruction of the SAT, atmospheric circulation, and sea ice (and SST) over the past two millennia in the high latitudes.

Tree-ring widths represent the most commonly used proxy to reconstruct the climate of the last millennium at high resolution, thanks to their large-scale availability. The approach often relies on a relationship between tree-ring width series and climate estimated on the basis of a linear regression. The underlying linearity and stationarity assumptions may be inadequate. Dendroclimatic process-based models, such as MAIDEN (Modeling and Analysis In DENdroecology), may be able to overcome some of the limitations of the statistical approach. MAIDEN is a mechanistic ecophysiological model that simulates tree-ring growth starting from surface air temperature, precipitation and CO2 concentration daily inputs. In this study, we successfully include the MAIDEN model into a data assimilation procedure as a proxy system model to robustly compare the outputs of an Earth system model with tree-ring width observations and provide a spatially-gridded reconstruction of continental temperature, precipitation and winds in the mid to high latitudes of the Southern Hemisphere over the past centuries. More specifically, we evaluate the benefits of using process-based tree-growth models such as MAIDEN for reconstructing past climate with data assimilation compared to the commonly used linear regression. The comparison of the reconstructions with instrumental data indicates an equivalent skill of both the regression- and process-based proxy system models in the data assimilation framework. Nevertheless, the MAIDEN model still brings important advantages that could result in more robust reconstructions beyond the instrumental era. Moreover, improvements continuously made in such models or in their calibration procedure also offer encouraging perspectives. Important steps have thus been made to demonstrate that using a process-based model like MAIDEN as a proxy system model is a promising way to improve the large-scale climate reconstructions with data assimilation.

We explore a methodology to statistically downscale snowfall – the primary driver of surface mass balance in Antarctica – from an ensemble of historical (1850–present day) simulations performed with an earth system model over the coastal region of Dronning Maud Land (East Antarctica). This approach consists of associating daily snowfall simulations from a polar-oriented regional atmospheric climate model at 5.5 km spatial resolution with specific weather patterns observed over 1979–2010 CE with the atmospheric reanalyses ERA-Interim and ERA5. This association is then used to generate the spatial distribution of snowfall for the period from 1850 to present day for an ensemble of 10 members from the Community Earth System Model (CESM2). The new dataset of daily and yearly snowfall accumulation based on this methodology is presented in this paper (MASS2ANT dataset; https://doi.org/10.5281/zenodo.4287517; Ghilain et al., 2021). Based on a comparison with available ice cores and spatial reconstructions, our results show that the spatio-temporal distribution of snowfall is improved in the downscaled dataset compared with the CESM2 simulations. This dataset thus provides information that may be useful in identifying the large-scale patterns associated with the local precipitation conditions and their changes over the past century.

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.

Ocean and ice sheet in the West Antarctic sector have witnessed large climate changes during the second half of the 20th century including a strong and widespread continental warming, important regional changes in sea-ice extent and snow accumulation, as well as a major mass loss from the melting of some ice shelves. However, the potential links between those observed changes are still unclear and instrumental data do not allow determining if they are part of a long-term evolution or specific to the recent decades. In this study, we analyze the climate variability of the past two centuries in the West Antarctic sector by reconstructing the key atmospheric variables (atmospheric circulation, near-surface air temperature and snow accumulation) as well as the sea-ice extent at the annual timescale using a data assimilation approach. To this end, information from Antarctic ice core records (snow accumulation and δ18O) and tree-ring width sites located in the mid-latitudes of the Southern Hemisphere are combined with the physics of climate models using a data assimilation method. This ultimately provides a complete spatial reconstruction over the west Antarctic region. Our reconstruction reproduces well the main characteristics of the observed changes over the instrumental period. We show that the observed sea-ice reduction in the Bellingshausen-Amundsen Sea sector over the satellite era is part of a long-term trend, starting at around 1850 CE, while the sea-ice expansion in the Ross Sea sector has only started around 1950 CE. Furthermore, according to our reconstruction, the Amundsen Sea Low pressure (ASL) displays no significant linear trend in its strength or position over 1850-1950 CE but becomes stronger and shifts eastward afterwards. The year-to-year sea-ice variations in the Ross Sea sector are strongly related to the ASL variability over the past two centuries, including the recent trends. By contrast, the link between ASL and sea ice the Bellingshausen-Amundsen Sea sector changes with time, being stronger in recent decades than before, Our reconstruction also suggests that the continental response to the variability of the ASL may not be stationary over time, being significantly affected by modification of the mean circulation. Finally, we show that the widespread warming since 1958 CE in West Antarctica is unusual in the context of past 200 years and is explained by both the deeper ASL and the positive phase of the Southern Annular Mode.

The climate of polar regions is characterized by large fluctuations and has experienced dramatic changes over the past decades. In the high latitudes of the Southern Hemisphere, the patterns of changes in sea ice and ice sheet mass, in particular, are more complex than for the Northern Hemisphere. Some regions have warmed less than the global average with some sea-ice advance, in particular in the Ross Sea, while other regions such as the Bellingshausen Sea have warmed significantly and displayed sea-ice loss. The Antarctic Ice Sheet has also lost mass in the past decades, with a spectacular thinning and weakening of ice shelves, i.e., the floating extensions of the grounded ice sheet. Despite recent advances in observing and modelling the Antarctic climate, the mechanisms at the origin of those trends are very uncertain because of the limited amount of observations and the large biases of climate models in polar regions, in concert with the large internal variability prevailing in the Antarctic. One of the most important atmospheric modes of climate variability in the Southern Ocean is the Southern Annular Mode (SAM), which represents the position and the strength of the westerly winds. During years with a positive SAM index, lower sea level pressure at high latitudes and higher sea level pressure at low latitudes occur, resulting in a stronger pressure gradient and intensified Westerlies. However, the current knowledge of the impact of these fluctuations of the Westerlies on the Southern Ocean and Antarctic cryosphere is still limited. Some efforts have been devoted over the past few years to the impact of the SAM on the Antarctic sea ice and the surface mass balance of the ice sheet from an atmospheric-specific perspective. Recently, a few studies have focused on the local impact on ice-shelf basal melt in specific regions of Antarctica. However, to our knowledge, there is no such study of the impact of the SAM on ice-shelf basal melt at the pan-Antarctic scale. In this communication, we will address this issue by using simulations performed with the regional ocean and sea-ice model NEMO-LIM3.6 at a spatial resolution of 0.25° forced by the ERA5 reanalysis over the period 1979-2018 CE. The impact of both the annular and the non-annular components of the SAM on ice-shelf basal melt will be assessed through regressions and correlations between the seasonal or annual averages of the SAM index and the ice-shelf basal melt.

Several studies have shown that there is often a poor match between surface mass balance (SMB, mass gain at the surface of the ice sheet) simulated by regional climate models and the one locally measured from ice cores in Antarctica. Models’ representation of the physical processes that affect SMB is known to be imperfect, while ice core records may be strongly influenced by local processes such as post-depositional wind redistribution and precipitation intermittency. These two sources of uncertainty likely both have a role to play in the discrepancy identified between modeled and observed ice core SMB estimates over the past centuries.The goal here is to estimate the uncertainties associated with the difference between a point-wise measurement of SMB as provided by the ice core and the SMB averages over a grid of several square kilometers of the models. To do so, we use ground-penetrating radar (GPR) data, collected over several ice rises, located along the high accumulation Princess Ragnhild Coast (East Antarctica), to obtain a multi-year resolution record that goes back ∼30-40 years, representing SMB spatial and temporal variability at the scale of a few km2 for each ice rise. Ice cores were collected during each radar field campaign, which allows us to place age constraints on the radar stratigraphy obtained and compare the GPR SMB estimates with the ice core SMB estimate.Therefore, we are able to calculate an error of representativeness for each ice core SMB, estimated as the difference between the average GPR SMB over a few km2 and the ice core SMB. This representativeness error can be split into two components: a systematic error (on the order of ∼0.1 m w.e. yr-1) and a random error (on the order of ±1 cm w.e. yr-1). Finally, we then compare our corrected ice core SMB records to regional SMB derived from a state-of-the-art polar-oriented regional climate model to quantify the impact of ice core uncertainties on the modeled-observed SMB discrepancy.

Trees are one of the main archives to reconstruct past climate variability at the interannual scale. The links between tree-ring proxies and climate have usually been estimated on the basis of statistical approaches, assuming linear and stationary relationships. Yet, both assumptions can be inadequate. This issue can be overcome by the use of process-based dendroclimatic models. For example, MAIDEN (Modeling and Analysis In DENdroecology) is a mechanistic tree-growth model that simulates tree-ring growth starting from surface air temperature, precipitation and CO2 daily inputs. VS-Lite (Vaganov-Shashkin Lite) is a simplified model that is more generally used in global applications and simulates unitless tree-growth indexes with monthly temperature and precipitation as inputs. In this study, we provide a climate reconstruction of continental temperature, precipitation and winds in the mid to high latitudes of the Southern Hemisphere over the last millennium that takes into account explicitly the links between climate and tree growth with process-based dendroclimatic models. To this end, an offline data assimilation procedure is used to combine the information from the physics of the climate system, as included in climate models, and paleoclimate records, in particular tree-ring width and ice cores records (snow accumulation and δ18O). Those records are the best available continental proxies in the Southern Hemisphere continents (South America, Australia, Tasmania, New Zealand and Antarctica) for reconstructing the past climate. MAIDEN and VS-Lite are used here as proxy system models, also referred to as observation operators in data assimilation framework, to make the link between climate model outputs and indirect climate observations from tree-rings. The ice cores records are directly compared to the outputs of the climate model. More specifically, we evaluate the benefits of using tree-growth models such as VS-Lite and MAIDEN for reconstructing past climate with data assimilation compared to the commonly used linear regression.

Recent Antarctic surface climate change has been characterized by greater warming trends in West Antarctica than in East Antarctica. Although the changes over recent decades are well studied, the short instrumental record limits our ability to determine if such asymmetric patterns are common for Antarctica and the processes at their origin. Here, we will focus on the years 0-1000 CE as some ice core records display very contrasted trends during this period. Furthermore, the climate models are unable to reproduce the warming displayed in some reconstructions from 1 to 500 CE over East Antarctica. In order to understand the origin of these apparent incompatibilities and investigate the effect of proxy selection on regional reconstructions over 0-1000 CE, we performed several offline data assimilation experiments based on different groups of d18O records and the isotope-enabled general circulation models (iCESM). When assimilating different d18O data sets, large differences appear in the pattern of temperature trend over 0-500 CE, but the patterns over 500-1000 CE are more consistent among the various experiments. This implies that the spatial pattern of temperature trend over 0-500 CE is still uncertain because of this high sensitivity on the choice of the proxies to constrain the model results, while the pattern over 500-1000 is more robust, with the greater cooling over West Antarctica than East Antarctica. This pattern over 500-1000 CE relates to the intensifying of the low pressure centered in the Amundsen Sea, which induces enhanced southerly flow through most of WAIS.

The surface mass balance (SMB) over the Antarctic Ice Sheet displays large temporal and spatial variations. Due to the complex Antarctic topography, modelling the climate at high resolution is crucial to accurately represent the dynamics of SMB. While ice core records provide a means to infer the SMB over centuries, the view is very spatially constrained. General circulation models (GCMs) estimate its spatial distribution over centuries, but with a resolution that is too coarse to capture the large variations due to local orographic effects. We have therefore explored a methodology to statistically downscale snowfall accumulation, the primary driver of SMB, from climate model historical simulations (1850–present day) over the coastal region of Dronning Maud Land. An analog method is set up over a period of 30 years with the ERA-Interim and ERA5 reanalyses (1979–2010 AD) and associated with snowfall daily accumulation forecasts from the Regional Atmospheric Climate Model (RACMO2.3) at 5.5 km spatial resolution over Dronning Maud in East Antarctica. The same method is then applied to the period from 1850 to present day using an ensemble of ten members from the CESM2 model. This method enables to derive a spatial distribution of the accumulation of snowfall, the principal driver of the SMB variability over the region. A new dataset of daily and yearly snowfall accumulation based on this methodology is presented in this paper (MASS2ANT dataset, https://doi.org/10.5281/zenodo.4287517, Ghilain et al. (2021)), along with comparisons with ice core data and available spatial reconstructions. It offers a more detailed spatio-temporal view of the changes over the past 150 years compared to other available datasets, allowing a possible connection with the ice core records, and provides information that may be useful in identifying the large-scale patterns associated to the local precipitation conditions and their changes over the past century.

The West Antarctic climate has witnessed large changes during the second half of the twentieth century including a strong and widespread continental warming, important regional changes in sea-ice extent and snow accumulation, as well as a major mass loss from the melting of some ice shelves. However, the potential links between those observed changes are still unclear and instrumental data do not allow determination of whether they are part of a long-term evolution or specific to the recent decades. In this study, we analyze the climate variability of the past two centuries in the West Antarctic sector by reconstructing the key atmospheric variables (atmospheric circulation, near-surface air temperature and snow accumulation) as well as the sea-ice extent at the annual timescale using a data assimilation approach. To this end, information from Antarctic ice core records (snow accumulation and $$\delta ^{{18}}\hbox{O}$$ ) and tree-ring width records situated in the mid-latitudes of the Southern Hemisphere are combined with the physics of climate models using a data assimilation method. This ultimately provides a complete spatial reconstruction over the West Antarctic region. Our reconstruction reproduces well the main characteristics of the observed changes over the instrumental period. We show that the observed sea-ice reduction in the Bellingshausen-Amundsen Sea sector over the satellite era is part of a long-term trend, starting at around 1850 CE, while the sea-ice expansion in the Ross Sea sector has only started around 1950 CE. Furthermore, according to our reconstruction, the Amundsen Sea Low pressure (ASL) displays no significant linear trend in its strength or position over 1850–1950 CE but becomes stronger and shifts eastward afterwards. The year-to-year sea-ice variations in the Ross Sea sector are strongly related to the ASL variability over the past two centuries, including the recent trends. By contrast, the link between ASL and sea-ice in the Bellingshausen-Amundsen Sea sector changes with time, being stronger in recent decades than before. Our reconstruction also suggests that the continental response to the variability of the ASL may not be stationary over time, being significantly affected by modification of the mean atmospheric circulation. Finally, we show that the widespread warming since 1958 CE in West Antarctica is unusual in the context of past 200 years and is explained by both the deeper ASL and the positive phase of the Southern Annular Mode.

Large open-ocean polynyas, defined as ice-free areas within the sea ice pack, have only rarely been observed in the Southern Ocean over the past decades. In addition to smaller recent events, an impressive sequence occurred in the Weddell Sea in 1974, 1975 and 1976 with openings of more than 300 000 km2 that lasted the full winter. These big events have a huge impact on the sea ice cover, deep-water formation, and, more generally, on the Southern Ocean and the Antarctic climate. However, we have no estimate of the frequency of the occurrence of such large open-ocean polynyas before the 1970s. Our goal here is to test if polynya activity could be reconstructed using continental records and, specifically, observations derived from ice cores. The fingerprint of big open-ocean polynyas is first described in reconstructions based on data from weather stations, in ice cores for the 1970s and in climate models. It shows a signal characterized by a surface air warming and increased precipitation in coastal regions adjacent to the eastern part of the Weddell Sea, where several high-resolution ice cores have been collected. The signal of the isotopic composition of precipitation is more ambiguous; thus, we base our reconstructions on surface mass balance records alone. A first reconstruction is obtained by performing a simple average of standardized records. Given the similarity between the observed signal and the one simulated in models, we also use data assimilation to reconstruct past polynya activity. The impact of open-ocean polynyas on the continent is not large enough, compared with the changes due to factors such as atmospheric variability, to detect the polynya signal without ambiguity, and additional observations would be required to clearly discriminate the years with and without open-ocean polynya. Thus, it is reasonable to consider that, in these preliminary reconstructions, some high snow accumulation events may be wrongly interpreted as the consequence of polynya formation and some years with polynya formation may be missed. Nevertheless, our reconstructions suggest that big open-ocean polynyas, such as those observed in the 1970s, are rare events, occurring at most a few times per century. Century-scale changes in polynya activity are also likely, but our reconstructions are unable to precisely assess this aspect at this stage.

Over the last century, the increase in snow accumulation has partly mitigated the total dynamic Antarctic Ice Sheet mass loss. However, the mechanisms behind this increase are poorly understood. Here we analyze the Antarctic Ice Sheet atmospheric moisture budget based on climate reanalysis and model simulations to reveal that the interannual variability of regional snow accumulation is controlled by both the large-scale atmospheric circulation and short-lived synoptic-scale events (i.e. storm systems). Yet, when considering the entire continent at the multi-decadal scale, only the synoptic-scale events can explain the recent and expected future snow accumulation increase. In a warmer climate induced by climate change, these synoptic-scale events transport air that can contain more humidity due to the increasing temperatures leading to more precipitation on the continent. Our findings highlight that the multi-decadal and interannual snow accumulation variability is governed by different processes, and that we thus cannot rely directly on the mechanisms driving interannual variations to predict long-term changes in snow accumulation in the future. Long-term changes in future snow accumulation in Antarctica are influenced more strongly by changes in storm systems than the large-scale circulation, according to an analysis of the Antarctic moisture budget from climate simulations and reanalysis data.

Large open-ocean polynyas, defined as ice-free areas within the sea ice pack, have been observed only rarely over the past decades in the Southern Ocean. In addition to smaller recent events, an impressive sequence occurred in the Weddell Sea in 1974, 1975 and 1976 with openings of more than 300,000 km2 that lasted the full winter. Those big events have a huge impact on the sea ice cover, deep-water formation and more generally on the Southern Ocean and the Antarctic climate. However, we have no estimate of the frequency of the occurrence of such large open-ocean polynyas before the 1970s. Our goal here is to test if polynya activity could be reconstructed using continental records, and specifically, observations derived from ice cores. The fingerprint of big open-ocean polynyas is first described in reconstructions based on data from weather stations, in ice cores for the 1970s and in climate models. It shows a clear signal, characterized by a surface air warming and increased precipitation in coastal regions adjacent to the eastern part of the Weddell Sea where several high-resolution ice cores have been collected. The signal of isotopic composition of precipitation is more ambiguous and we thus base our reconstructions on surface mass balance records only. A first reconstruction is obtained by performing a simple average of standardized records. Given the similarity between the observed signal and the one simulated in models, we also use data assimilation to reconstruct past polynya activity. The impact of open ocean polynyas on the continent is not large enough compared to the changes due, for instance, to atmospheric variability to detect without ambiguity the polynya signal and additional observations would be required to discriminate clearly the years with and without open ocean polynya. It is thus reasonable to consider that, in these preliminary reconstructions, some high accumulation events may be wrongly interpreted as the consequence of polynya formation while some years with polynya formation may be missed. Nevertheless, our reconstructions suggest that big open ocean polynyas, such as the ones that were observed in the 1970s, are rare events, occurring at most a few times per century. Century-scale changes in polynya activity are also likely but our reconstructions are unable to assess precisely this aspect at this stage.

Over recent decades, the Antarctic Ice Sheet has witnessed large spatial variations at its surface through the surface mass balance (SMB). Since the complex Antarctic topography, working at high resolution is crucial to represent accurately the dynamics of SMB. While ice cores provide a mean to infer the SMB over centuries, the view is very spatially constrained. Global Climate models estimate the spatial distribution of SMB over centuries, but with a too coarse resolution with regards to the large variations due to local orographic effects. We have therefore explored a methodology to statistically downscale the SMB components from the climate model historical simulations (1850-present day). An analogue method is set up over a period of 30 years with the ERA-Interim reanalysis (1979-2010 AD) and associated with SMB components from the Regional Atmospheric Climate Model (RACMO) at 5 km spatial resolution over Dronning Maud in East Antarctica. The same method is then applied to the period from 1850 to present days using an ensemble of 10 simulations from the CESM2 model. This method enables to derive a spatial distribution of SMB. In addition, the changes in precipitation delivery mechanisms can be unveiled.

Ice cores constitute an important record of the past surface mass balance (SMB) of the ice sheets, with SMB ultimately modulating the ice sheets’ sea level impact. For the Antarctic Ice Sheet (AIS), SMB is dominated by snow accumulation and strongly controlled by atmospheric circulation. Large-scale atmospheric depressions collect warmth and moisture from further north that they then release over the AIS in the form of widespread accumulation or focused atmospheric rivers. This implies that snow deposited at the surface of the AIS should show strongly coupled SMB and surface air temperatures (SAT) variations. Ice cores do not record SAT directly but their d18O record is often used as a temperature proxy. Here, using the PAGES 2k Network ice core compilations of SMB and d18O of Thomas et al. (2017) and Stenni et al. (2017), we obtain a weak correlation between SMB and d18O over historical timescales, and an equivalently weak correlation between SMB and SAT based on the Nicolas & Bromwich (2014) SAT reconstructions. However, we calculate a strong and positive SMB-SAT correlation in the majority of regions of the AIS using Global Climate Models (GCM) and the regional model RACMO2.3p2. To resolve the discrepancy between measured and modeled signals, we show that averaging the ice core records in close spatial proximity increases their SMB-SAT correlation. This increase in measured SMB-SAT correlation likely results from noise present in the ice core records, but is not enough to match the strong correlation calculated in the models. On the model side, the high spatial resolution of the RACMO2.3p2 model allows us to highlight a number of areas of the AIS where SMB and SAT are not strongly correlated. We describe how wind-driven processes acting on the SMB and SAT locally, through Foehn and katabatic effects, can overwhelm the large-scale atmospheric input that induces the positive SMB-SAT correlations. In particular, we focus on Dronning Maud Land, East Antarctica, where each ice promontory clearly shows this wind-driven snow redistribution. Nevertheless, those regions displaying a low SMB-SAT correlation cover only a small fraction of the AIS and are not sufficient to explain the model-data discrepancy, suggesting a critical role of processes at a scale smaller than the one resolved by the regional model. References:Thomas, E. R., 2017, Regional Antarctic snow accumulation over the past 1000 years, Climate of the Past, 13, 1491–1513.Stenni, B. et al., 2017, Antarctic climate variability on regional and continental scales over the last 2000 years, Climate of the Past, 13, 1609–1634.Nicolas, J. P. & Bromwich, D. H., 2014, New reconstruction of Antarctic near-surface temperatures: Multidecadal trends and reliability of global reanalyses, Journal of Climate, 27, 8070–8093.

Ice cores are an important record of the past surface mass balance (SMB) of ice sheets, with SMB mitigating the ice sheets’ sea level impact over the recent decades. For the Antarctic Ice Sheet (AIS), SMB is dominated by large-scale atmospheric circulation, which collects warm moist air from further north and releases it in the form of snow as widespread accumulation or focused atmospheric rivers on the continent. This implies that the snow deposited at the surface of the AIS should record strongly coupled SMB and surface air temperature (SAT) variations. Ice cores use δ18O as a proxy for SAT as they do not record SAT directly. Here, using isotope-enabled global climate models and the RACMO2.3 regional climate model, we calculate positive SMB-SAT and δ18O-SMB correlations over ∼90 % of the AIS. The high spatial resolution of the RACMO2.3 model allows us to highlight a number of areas where SMB and SAT are not correlated, and show that wind-driven processes acting locally, such as Foehn and katabatic effects, can overwhelm the large-scale atmospheric input in SMB and SAT responsible for the positive SMB-SAT correlations. We focus in particular on Dronning Maud Land, East Antarctica, where the ice promontories clearly show these wind-induced effects. However, using the PAGES2k ice core compilations of SMB and δ18O of Thomas et al. (2017) and Stenni et al. (2017), we obtain a weak correlation, on the order of 0.1, between SMB and δ18O over the past ~150 years. We obtain an equivalently weak correlation between ice core SMB and the SAT reconstruction of Nicolas and Bromwich (2014) over the past ~50 years, although the ice core sites are not spatially co-located with the areas displaying a low SMB-SAT correlation in the models. To resolve the discrepancy between the measured and modeled signals, we show that averaging the ice core records in close spatial proximity increases their SMB-SAT correlation. This increase shows that the weak measured correlation likely results from random noise present in the ice core records, but is not large enough to match the correlation calculated in the models. Our results indicate thus a positive correlation between SAT and SMB in models and ice core reconstructions but with a weaker value in observations that may be due to missing processes in models or some systematic biases in ice core data that are not removed by a simple average.

Improving our knowledge of the temporal and spatial variability of the Antarctic Ice Sheet (AIS) surface mass balance (SMB) is crucial to reduce the uncertainties of past, present, and future Antarctic contributions to sea level rise. An examination of the surface air temperature–SMB relationship in model simulations demonstrates a strong link between the two. Reconstructions based on ice cores display a weaker relationship, indicating a model–data discrepancy that may be due to model biases or to the non-climatic noise present in the records. We find that, on the regional scale, the modeled relationship between surface air temperature and SMB is often stronger than between temperature and δ18O. This suggests that SMB data can be used to reconstruct past surface air temperature. Using this finding, we assimilate isotope-enabled SMB and δ18O model output with ice core observations to generate a new surface air temperature reconstruction. Although an independent evaluation of the skill is difficult because of the short observational time series, this new reconstruction outperforms the previous reconstructions for the continental-mean temperature that were based on δ18O alone. The improvement is most significant for the East Antarctic region, where the uncertainties are particularly large. Finally, using the same data assimilation method as for the surface air temperature reconstruction, we provide a spatial SMB reconstruction for the AIS over the last 2 centuries, showing large variability in SMB trends at a regional scale, with an increase (0.82 Gt yr−2) in West Antarctica over 1957–2000 and a decrease in East Antarctica during the same period (−0.13 Gt yr−2). As expected, this is consistent with the recent reconstruction used as a constraint in the data assimilation.

Ice cores are an important record of the past surface mass balance (SMB) of ice sheets, with SMB mitigating the ice sheets' sea level impact over the recent decades. For the Antarctic Ice Sheet (AIS), SMB is dominated by large-scale atmospheric circulation, which collects warm moist air from further north and releases it in the form of snow as widespread accumulation or focused atmospheric rivers on the continent. This suggests that the snow deposited at the surface of the AIS should record strongly coupled SMB and surface air temperature (SAT) variations. Ice cores use δ18O as a proxy for SAT as they do not record SAT directly. Here, using isotope-enabled global climate models and the RACMO2.3 regional climate model, we calculate positive SMB–SAT and SMB–δ18O annual correlations over ∼90 % of the AIS. The high spatial resolution of the RACMO2.3 model allows us to highlight a number of areas where SMB and SAT are not correlated, and we show that wind-driven processes acting locally, such as foehn and katabatic effects, can overwhelm the large-scale atmospheric contribution in SMB and SAT responsible for the positive SMB–SAT annual correlations. We focus in particular on Dronning Maud Land, East Antarctica, where the ice promontories clearly show these wind-induced effects. However, using the PAGES2k ice core compilations of SMB and δ18O of Thomas et al. (2017) and Stenni et al. (2017), we obtain a weak annual correlation, on the order of 0.1, between SMB and δ18O over the past ∼150 years. We obtain an equivalently weak annual correlation between ice core SMB and the SAT reconstruction of Nicolas and Bromwich (2014) over the past ∼50 years, although the ice core sites are not spatially co-located with the areas displaying a low SMB–SAT annual correlation in the models. To resolve the discrepancy between the measured and modeled signals, we show that averaging the ice core records in close spatial proximity increases their SMB–SAT annual correlation. This increase shows that the weak measured annual correlation partly results from random noise present in the ice core records, but the change is not large enough to match the annual correlation calculated in the models. Our results thus indicate a positive correlation between SAT and SMB in models and ice core reconstructions but with a weaker value in observations that may be due to missing processes in models or some systematic biases in ice core data that are not removed by a simple average.

Driftwood is frequently used to estimate past changes of sea ice extent and circulation in the Arctic. Nevertheless, driftwood observations are difficult to interpret because of the potentially complex relation with climate change. In order to determine the origin of the observed changes, we built a driftwood transport model (DTM) simulating the driftwood trajectories from the boreal forest to Arctic coasts. The model is driven by three main variables, which are the sea ice velocity, concentration and the sea surface current velocity that can be derived from observations or climate model outputs (e.g. from a General Climate Model – GCM). Overall, the DTM model agrees with the observations, although this comparison needs to be taken with caution because of the sparse data and the uncertainties of driftwood provenance. Through simulations performed with the DTM model, we confirm the strong influence of the variability of the atmospheric circulation on the spatial driftwood distribution. Model simulations of the Mid-Holocene period driven by six GCMs show that small local changes in sea ice circulation – a westward shift in the Transpolar Drift and a reduced Beaufort Gyre during the Mid-Holocene compared to the present period – suffice to explain the driftwood landing change during the Mid-Holocene, with a non-negligible contribution from reduced sea ice concentration. Consequently, a change in driftwood deposit should not be directly interpreted as large modifications in atmospheric circulation and the complexity of the response of driftwood trajectories to past climate changes clearly highlights the interest of using a model to interpret driftwood records.

Improving our knowledge of the temporal and spatial variability of the Antarctic Ice Sheet (AIS) Surface Mass Balance (SMB) is crucial to reduce the uncertainties of past, present and future Antarctic contributions to sea level rise. Here, we show that Global Climate Models (GCMs) can reproduce the present-day (1979–2005) AIS SMB and the temporal variations over the last two centuries. An examination of the surface temperature–SMB relationship in model simulations demonstrates a strong link between the two. Reconstructions based on ice cores display a weaker relationship, indicating a model-data discrepancy that may be due to model biases or to the non-climatic noise present in the records. We find that, on the regional scale, the modelled temperature-SMB relationship is stronger than the relationship between δ18O-temperature. This suggests that SMB data can be used to reconstruct past surface temperatures. Using this finding, we assimilate isotope-enabled model SMB and δ18O output with ice-core observations, to generate a new surface temperature reconstruction. Although an independent evaluation of the skill is difficult because of the short observational time series, this new reconstruction outperforms the previous reconstructions for the continental-mean temperature that were based on δ18O alone with a linear correlation coefficient with the observed surface temperatures (1958–2010 CE) of 0.73. The improvement is largest for the East Antarctic region, where the uncertainties are particularly large. Finally, we provide a spatial SMB reconstruction of the AIS over the last two centuries showing 1) large variability in SMB trends at regional scale; and 2) a large SMB increase (0.82 Gt year−2) in West Antarctica over 1957–2000 while at the same time, East Antarctica has experienced a large SMB decrease (−3.3 Gt year−2), which is consistent with a recent reconstruction.