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Author(s): Li, X; Cai, W; Meehl, GA; Chen, D; Yuan, X; Raphael, M; Holland, DM; Ding, Q; Fogt, RL; Markle, BR; Wang, G; Bromwich, DH; Turner, J; Xie, SP; Steig, EJ; Gille, ST; Xiao, C; Wu, B; Lazzara, MA; Chen, X; Stammerjohn, S; Holland, PR; Holland, MM; Cheng, X; Price, SF; Wang, Z; Bitz, CM; Shi, J; Gerber, EP; Liang, X; Goosse, H; Yoo, C; Ding, M; Geng, L; Xin, M; Li, C; Dou, T; Liu, C; Sun, W; Wang, X; Song, C | Abstract: Over the modern satellite era, substantial climatic changes have been observed in the Antarctic, including atmospheric and oceanic warming, ice sheet thinning and a general Antarctic-wide expansion of sea ice, followed by a more recent rapid loss. Although these changes, featuring strong zonal asymmetry, are partially influenced by increasing greenhouse gas emissions and stratospheric ozone depletion, tropical–polar teleconnections are believed to have a role through Rossby wave dynamics. In this Review, we synthesize understanding of tropical teleconnections to the Southern Hemisphere extratropics arising from the El Nino–Southern Oscillation, Interdecadal Pacific Oscillation and Atlantic Multidecadal Oscillation, focusing on the mechanisms and long-term climatic impacts. These teleconnections have contributed to observed Antarctic and Southern Ocean changes, including regional rapid surface warming, pre-2015 sea ice expansion and its sudden reduction thereafter, changes in ocean heat content and accelerated thinning of most of the Antarctic ice sheet. However, due to limited observations and inherent model biases, uncertainties remain in understanding and assessing the importance of these teleconnections versus those arising from greenhouse gases, ozone recovery and internal variability. Sustained pan-Antarctic efforts towards long-term observations, and more realistic dynamics and parameterizations in high-resolution climate models, offer opportunities to reduce these uncertainties.

A large majority of the direct observational record for glacier changes falls within the industrial period, from the 19th century onward, associated with global glacier retreat. Given this availability of data and the significant focus in contemporary glacier modelling falling on recent retreat, glacier models are typically calibrated using – and validated with – only observations of glaciers that are considerably out of equilibrium. In order to develop a broader picture of the skill of one glacier model – the Open Global Glacier Model (OGGM) – we model glaciers for extended historical timescales of 850–2004 CE using a selection of six general circulation model (GCM) outputs. We select glaciers for which long-term length observations are available in order to compare these observations with the model results, and we find glaciers with such observations in almost all glacierised regions globally. In many regions, the mean modelled glacier changes are consistent with observations, with recent observed retreat in these regions typically at the steeper end of the range of modelled retreats. However, on the scale of individual glaciers, performance of the model is worse, with overall correlation between observed and modelled retreat weak for all of the GCM datasets used to force the model. We also model the same set of glaciers using modified climate time series from each of the six GCMs that keep temperature or precipitation constant, testing the impact of each individually. Temperature typically explains considerably more variance in glacier lengths than precipitation, but results suggest that the interaction between the two is also significant within OGGM and neither can be seen as a simple proxy for glacier length changes. OGGM proves capable of reproducing recent observational trends on at least a qualitative level in many regions, with a modelling period over a considerably larger timescale than it is calibrated for. Prospects are good for more widespread use of OGGM for timescales extending to the pre-industrial period, where glaciers were typically larger and experience less rapid (and less globally consistent) geometry changes, but additional calibration will be required in order to have confidence in the magnitude of modelled changes, particularly on the scale of individual glaciers.

The Totten Glacier in East Antarctica is of major climate interest because of the large fluctuation of its grounding line and of its potential vulnerability to climate change. The ocean above the continental shelf in front of the Totten ice shelf exhibits large extents of landfast sea ice with low interannual variability. Landfast sea ice is mostly not or sole crudely represented in current climate models. These models are potentially omitting or misrepresenting important effects related to this type of sea ice, such as its influence on coastal polynya locations. Yet, the impact of the landfast seaice on the ocean – ice shelf interactions is poorly understood. Using a series of high-resolution, regional NEMO-LIM-based experiments including anexplicit treatment of ocean – ice shelf interactions over the years 2001-2010, we simulate a realistic landfast sea ice extent in the area of Totten Glacierthrough a combination of a sea ice tensile strength parameterisation and a grounded iceberg representation. We show that the presence of landfast seaice impacts seriously both the location of coastal polynyas and the ocean mixed layer depth along the coast, in addition to favouring the intrusion ofmixed Circumpolar Deep Water into the ice shelf cavities. Depending on the local bathymetry and the landfast sea ice distribution, landfast sea ice affects ice shelf cavities in different ways, either by increasing the ice melt (+28% for the Moscow University ice shelf) or by reducing its seasonal cycle(+10% in March-May for the Totten ice shelf). This highlights the importance of including an accurate landfast sea ice representation in regional andeventually global climate models

We introduce PARASO, a novel five-component fully-coupled regional climate model over an Antarctic circumpolar domain covering the full Southern Ocean. The state-of-the-art models used are f.ETISh1.7 (ice sheet), NEMO3.6 (ocean), LIM3.6 (sea ice), COSMO5.0 (atmosphere) and CLM4.5 (land), which are here run at an horizontal resolution close to 1/4°. One key-feature of this tool resides in a novel two-way coupling interface for representing ocean – ice-sheet interactions, through explicitly resolved ice-shelf cavities. The impact of atmospheric processes on the Antarctic ice sheet is also conveyed through computed COSMO-CLM – f.ETISh surface mass exchanges. In this technical paper, we briefly introduce each model's configuration and document the developments that were carried out in order to establish PARASO. The new offline-based NEMO – f.ETISh coupling interface is thoroughly described. Our developments also include a new surface tiling approach to combine open-ocean and sea-ice covered cells within COSMO, which was required to make this model relevant in the context of coupled simulations in polar regions. We present results from a 2000–2001 coupled two-year experiment. PARASO is numerically stable and fully operational. The 2-year simulation conducted without fine tuning of the model reproduced the main expected features, although remaining systematic biases provide perspectives for further adjustment and development.

Abrupt cooling is observed at the end of interglacials in many paleoclimate records, but the mechanism responsible remains unclear. Using model simulations, we demonstrate that there exists a threshold in the level of astronomically induced insolation below which abrupt changes at the end of interglacials of the past 800,000 years occur. When decreasing insolation reaches the critical value, it triggers a strong, abrupt weakening of the Atlantic meridional overturning circulation and a cooler mean climate state accompanied by high-amplitude variations lasting for several thousand years. The mechanism involves sea ice feedbacks in the Nordic and Labrador Seas. The ubiquity of this threshold suggests its fundamental role in terminating the warm climate conditions at the end of interglacials.

The Cook Ice Cap (CIC) on the sub-Antarctic Kerguelen Islands recently experienced extremely negative surface mass balance. Further deglaciation could have important impacts on endemic and invasive fauna and flora. To put this exceptional glacier evolution into a multi-centennial-scale context, we refined the evolution of the CIC over the last millennium, investigated the associated climate conditions and explored its potential evolution by 2100 ce. A glaciological model, constrained by cosmic ray exposure dating of moraines, historical documents and recent direct mass balance observations, was used to simulate the ice-cap extents during different phases of advance and retreat between the last millennium and 2100 ce. Cosmogenic dating suggests glacial advance around the early Little Ice Age (LIA), consistent with findings from other sub-Antarctic studies, and the rather cold and humid conditions brought about by the negative phase of the Southern Annular Mode (SAM). This study contributes to our currently limited understanding of palaeoclimate for the early LIA in the southern Indian Ocean. Glaciological modelling and observations confirm the recent decrease in CIC extent linked to the intensification of the SAM. Although affected by large uncertainties, future simulations suggest a complete disappearance of CIC by the end of the century.

The last deglaciation is a time of large climate transition from a cold Last Glacial Maximum at 21,000 years BP with extensive ice sheets, to the warmer Holocene 9,000 years BP onwards with reduced ice sheets. Despite more and more proxy data documenting this transition, the evolution of climate is not fully understood and difficult to simulate. The PMIP4 protocol (Ivanovic et al., 2016) has indicated which boundary conditions to use in model simulations during this transition. The common boundary conditions should enable consistent multi model and model-data comparisons. While the greenhouse gas concentration evolution and orbital forcing are well known and easy to prescribe, the evolution of ice sheets is less well constrained and several choices can be made by modelling groups. First, two ice sheet reconstructions are available: ICE-6G (Peltier et al., 2015) and GLAC-1D (Tarasov et al., 2014). On top of topographic changes, it is left to modelling groups to decide whether to account for the associated bathymetry and land-sea mask changes, which is technically more demanding. These choices could potentially lead to differences in the climate evolution, making model comparisons more complicated.We use the iLOVECLIM model of intermediate complexity (Goosse et al., 2010) to evaluate the impact of different ice sheet reconstructions and the effect of bathymetry changes on the global climate evolution during the Last deglaciation. We test the two ice sheet reconstructions (ICE-6G and GLAC-1D), and have implemented changes of bathymetry and land-sea mask. In addition, we also evaluate the impact of accounting for the Antarctic ice sheet evolution compared to the Northern ice sheets only.We show that despite showing the same long-term changes, the two reconstructions lead to different evolutions. The bathymetry plays a role, although only few changes take place before ~14ka. Finally, the impact of the Antarctic ice sheet is important during the deglaciation and should not be neglected.ReferencesGoosse, H., et al., Description of the Earth system model of intermediate complexity LOVECLIM version 1.2, Geosci. Model Dev., 3, 603–633, https://doi.org/10.5194/gmd-3-603-2010, 2010Ivanovic, R. F., et al., Transient climate simulations of the deglaciation 21–9 thousand years before present (version 1) – PMIP4 Core experiment design and boundary conditions, Geosci. Model Dev., 9, 2563–2587, https://doi.org/10.5194/gmd-9-2563-2016, 2016Peltier, W. R., Argus, D. F., and Drummond, R., Space geodesy constrains ice age terminal deglaciation: The global ICE-6G_C (VM5a) model, J. Geophys. Res.-Sol. Ea., 120, 450–487, doi:10.1002/2014JB011176, 2015Tarasov,L., et al., The global GLAC-1c deglaciation chronology, melwater pulse 1-a, and a question of missing ice, IGS Symposium on Contribution of Glaciers and Ice Sheets to Sea-Level Change, 2014

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.

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.

From at least 1979 up until 2016, the surface of the Southern Ocean cooled down, leading to a small Antarctic sea ice extent increase, which is in stark contrast with the Arctic Ocean. The attribution of the origin of these robust observations is still very uncertain. Among other phenomena, the direct, two-way interactions between the Southern Ocean and the Antarctic ice sheet, through basal melting of its numerous and large ice-shelf cavities, have been suggested as a potentially important contributor of this cooling. In order to address this question, we perform multidecadal coupled ice sheet – ocean numerical simulations relying on f.ETISh-v1.7 and NEMO3.6-LIM3 for simulating the Antarctic ice sheet and Southern Ocean (including sea ice), respectively. This presentation is twofold. First, we present the technical aspects of the coupling infrastructure (e.g. workflow and exchanged information in between models). Second, we investigate the ice sheet – ocean feedbacks on the Southern Ocean, their interactions, and the roles of the related physical mechanisms on the ocean surface cooling.

Instrumental records show that global mean sea level (GMSL) rose by approximately 15 cm in the 20th Century, with estimates of contributing factors suggesting the major components are ocean thermal expansion and melting of continental ice sheets and glaciers. However, little is known about the individual contributions to GMSL changes over the preindustrial common era (PCE) and the potential differences in the mechanisms controlling those changes between different time periods. Here, we describe the GMSL changes in the PCE by comparing proxy-based reconstructions with estimates derived from model experiments. The ocean thermal expansion is estimated on the basis of Coupled (Paleoclimate) Model Intercomparison Project (CMIP/PMIP) experiments. The contributions of ice sheets and glaciers are based on simulations with an ice-sheet model (IMAU-ICE) and a global glacier model (The Open Global Glacier Model), respectively. We also describe the thermal expansion response in the different ocean basins over the last millennium. The findings provide new insights on the current anthropogenic warming and sea-level rise in a wider context.

Much of the rainfall variability in the Guinean coast area during the boreal summer is driven by the sea surface temperature (SST) variations in the eastern equatorial Atlantic, amplified by land-atmosphere interactions. This oceanic region corresponds to the center of action of the Atlantic Equatorial mode, also termed Atlantic Niño (ATL3), which is the leading SST mode of variability in the tropical Atlantic basin. In years of positive ATL3, above normal SST conditions in the ATL3 area weaken the sea level pressure gradient between the West African lands and the ocean, which in turn reduces the monsoon flow penetration into Sahel. Subsequently, the rainfall increases over the Guinean coast area. According to observations and climate models, the relation between the Atlantic Niño and the rainfall in coastal Guinea is stationary over the 20th century. While this relation remains unchanged over the 21st century in climate model projections, the strength of the teleconnection is reduced in a warmer climate. The weakened ATL3 effect on the rainfall over the tropical Atlantic (in years of positive ATL3) has been attributed to the stabilization of the atmosphere column above the tropical Atlantic. Analysis of historical and high anthropogenic emission scenario (the Shared Socioeconomic Pathways 5-8.5) simulations from 31 models participating in the sixth phase of the Coupled Model Intercomparison Project suggests an additional role of the Bjerkness feedback. A weakened SST amplitude related to ATL3 positive phases reduces the anomalous westerlies, which in turn increases the upwelling cooling effect on the sea surface. Both the Guinean coast region and the equatorial Atlantic experiment the projected rainfall reduction associated with ATL3, with a higher confidence over the ocean than over the coastal lands.

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.

We demonstrate modelling of regional- and global-scale volume changes in glaciers over the last millennium with the Open Global Glacier Model (OGGM) - a glacier geometry and surface mass balance model in active development - using reconstructed climate data timeseries from a set of 6 GCMs. The goals are: 1) to better understand how well different longer-term (extending back to the pre-industrial period) climate datasets perform specifically in terms of their impact on glaciers; 2) to analyse the ability of OGGM to model glaciers over longer timescales while still capturing observed changes over the period of instrumental record; and 3) to determine which regions are better or worse suited to this type of modelling on large scales. A secondary goal is to understand the relative impact of precipitation and temperature - the two primary climate variables used to drive OGGM - on regional glacier volume over this time period, using synthetic climate inputs which isolate long-term trends from each variable individually. Modelling over this last millennium timescale is important due to the preponderance of available instrumental data being much more recent, with glacier models developed and calibrated using data that are mostly recorded in a period of pronounced global glacier retreat. Modelling periods that include both recent warming (and associated observed glacier retreat) and the preceding period that is without such globally coherent changes in climate provides a valuable test of glacier models, to ensure they can generate both relative stability in glacier geometry in stable climates with realistic variability and subsequent reduction in ice mass where appropriate in response to clearer recent temperature trends.

The mismatch between oceanic proxy data and climate model results over the past millennia has been a long-lasting challenge. Although both are valuable sources of paleoclimate information, there is a strong discrepancy in variance between models and proxies, so that they cannot be compared directly. In addition, local sea-surface temperature (SST) reconstructions are often inconsistent among proxy types. We first performed several offline data assimilation experiments with different standardized SST proxy datasets using the climate models LOVECLIM and CESM in order to investigate the effect of proxy selection on local and regional reconstructions over the Common Era (0-2000 CE). All experiments work technically at the local scale, but the spatial pattern of the reconstructions vary with the type(s), number and density of proxies, and, where there is no proxy, the choice of the model. We then developed empirical scaling factors based on independent SST observations to correct for the discrepancy between model and proxy amplitude. While it is essential to scale proxies, scaling the model leads to complications because of the biases in the sea ice extent. Data assimilation of scaled proxies results in coherent SST reconstructions at the scale of the North Atlantic, with timing and amplitude that are in agreement with those given by forced models. Finally, results are compared to online data assimilation experiments.

The EASM largely determines variations in summer precipitation in the East Asian monsoon region where approximately one-quarter of the world’s population live. A reliable East Asian summer monsoon (EASM) index covering several centuries is important in order to understand EASM dynamics. The wind-field is frequently used to calculate the EASM index during the instrumental period. However, available climate proxy data rather respond to direct precipitation changes. A gridded extended summer (May–September, MJJAS) precipitation reconstruction for China covering AD 1470–2000 is used to indirectly reconstruct two types of EASM indices (defined by the strength of the 850hPa southwesterly winds and a north-south gradient of the zonal winds), using the negative correlation between the EASM index and summer (June–August, JJA) rainfall in the middle and lower reaches of the Yangtze River of China. The two EASM indices are validated by independent historical documentary data for eastern China. The physical processes ruling the EASM variability are explored, highlighting a baroclinic structure over the middle and lower reaches of the Yangtze River. It includes an anticyclonic circulation accompanied by high pressure anomalies in the lower troposphere and a cyclonic circulation with low pressure anomaly in the upper troposphere. This is associated with a decrease in atmospheric water vapor content (due to divergence), which will decrease summer rainfall in the region, and contribute to the strengthen of the EASM variability. The dominated and inter-annual component of the EASM variation is possibly linked to the ‘ENSO-like’ sea surface temperature according to a data assimilation experiment performed with the Community Earth System Model-Last Millennium Ensemble (CESM-LME) simulation.

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.

Dynamical climate models have been extensively used over the last decade to perform seasonal sea ice predictions in the context of ensemble forecasting. To date, the sensitivity to the initial conditions has received the most attention through the evaluation of the theoretical limit of Antarctic sea ice predictability imposed by the chaotic evolution of the climate system. The respective contributions of perturbed ocean–sea ice initial conditions and perturbed atmospheric boundary conditions to this predictability remains unevaluated, though. Using the coupled ocean–sea ice model NEMO3.6–LIM3, we developed a suitable framework for evaluating both influences on seasonal Antarctic sea ice predictions. This study reveals that the uncertainty associated with the evolution of the atmospheric conditions is a major limitation to the realization of skilful sea ice extent (SIE) predictions. However, it has a limited impact on sea ice volume (SIV) predictions. The discrepancies between the SIE and SIV predictabilities have been attributed to the presence of very thin ice, which accounts for much of the SIE variability in winter. We also demonstrated that an incorrect estimate of the ocean–sea ice initial conditions has a weaker, but not negligible influence. The time evolution of different plausible ocean–sea ice initial conditions under perfect knowledge of the atmospheric conditions suggest that the initial SIE errors cannot be totally reduced by the atmospheric forcing. They even increase during the melt season. The high persistence of the SIV anomalies is found to be responsible for this behaviour. These findings imply that a correct initialization of the sea ice thickness (SIT) might be more important than previously thought for seasonal Antarctic sea ice predictions, especially if one wants to predict the SIE during the melt season.

The reconstructed surface-temperature time series from boreholes in Antarctica have significantly contributed to our understanding of multidecadal and centennial temperature changes and thus provide a good way to evaluate the ability of climate models to reproduce low-frequency climate variability. However, up to now, there has not been any systematic model–data comparison based on temperature from boreholes at a regional or local scale in Antarctica. Here, we discuss two different ways to perform such a comparison using borehole measurements and the corresponding reconstructions of surface temperature at the West Antarctic Ice Sheet (WAIS) Divide, Larissa, Mill Island, and Styx Glacier in Antarctica. The standard approach is to compare the surface temperature simulated by the climate model at the grid cell closest to each site with the reconstructions in the time domain derived from the borehole temperature observations. Although some characteristics of the reconstructions, for instance the nonuniform smoothing, limit to some extent the model–data comparison, several robust features can be evaluated. In addition, a more direct model–data comparison based on the temperature measured in the boreholes is conducted using a forward model that simulates explicitly the subsurface temperature profiles when driven with climate model outputs. This comparison in the depth domain is not only generally consistent with observations made in the time domain but also provides information that cannot easily be inferred from the comparison in the time domain. The major results from these comparisons are used to derive metrics that can be applied for future model–data comparison. We also describe the spatial representativity of the sites chosen for the metrics. The long-term cooling trend in West Antarctica from 1000 to 1600 CE (−1.0 ∘C) is generally reproduced by the models but often with a weaker amplitude. The 19th century cooling in the Antarctic Peninsula (−0.94 ∘C) is not reproduced by any of the models, which tend to show warming instead. The trend over the last 50 years is generally well reproduced in West Antarctica and at Larissa (Antarctic Peninsula) but overestimated at other sites. The wide range of simulated trends indicates the importance of internal variability in the observed trends and shows the value of model–data comparison to investigate the response to forcings.

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.

Satellite observations show a small overall increase in Antarctic sea ice extent (SIE) over the period 1979–2015. However, this upward trend needs to be balanced against recent pronounced SIE fluctuations occurring there. In the space of 3 years, the SIE sank from its highest value ever reached in September 2014 to record low in February 2017. In this work, a set of six state-of-the-art global climate models is used to evaluate the potential predictability of the Antarctic sea ice at such timescales. This first multi-model study of Antarctic sea ice predictability reveals that the ice edge location can potentially be predicted up to 3 years in advance. However, the ice edge location predictability shows contrasted seasonal performances, with high predictability in winter and no predictability in summer. The reemergence of the predictability from one winter to next is provided by the ocean through its large thermal inertia. Sea surface heat anomalies are stored at depth at the end of the winter and influences the sea ice advance the following year as they resurface. The effectiveness of this mechanism across models is found to depend upon the depth of the mixed layer. One should be very cautious about these potential predictability estimates as there is evidence that the Antarctic sea ice predictability is promoted by deep Southern Ocean convection. We therefore suspect models with excessive convection to show higher sea ice potential predictability results due to an incorrect representation of the Southern Ocean.

The high heterogeneity of sea ice properties implies that its effects on the ocean are spatially variable at horizontal scales as small as a few meters. Previous studies have shown that taking this variability into account in models could be required to simulate adequately mixed layer processes and the upper ocean temperature and salinity structures. Although many advanced sea ice models include a subgrid-scale ice thickness distribution, potentially providing heterogeneous surface boundary conditions, the information is lost in the coupling with a unique ocean grid cell underneath. The present paper provides a thorough examination of boundary conditions at the ocean surface in the NEMO-LIM model, which can be used as a guideline for studies implementing subgrid-scale ocean vertical mixing schemes. Freshwater, salt, solar heat and non-solar heat fluxes are examined, as well as the norm of the surface stress. All of the thermohaline fluxes vary considerably between the open water and ice fractions of grid cells. To a lesser extent, this is also the case for the surface stress. Moreover, the salt fluxes in both hemispheres and the solar heat fluxes in the Arctic show a dependence on the ice thickness category, with more intense fluxes for thinner ice, which promotes further subgrid-scale heterogeneity. Our analysis also points out biases in the simulated open water fraction and in the ice thickness distribution, which should be investigated in more details in order to ensure that the latter is used to the best advantage.

Recent studies have investigated the potential link between the freshwater input derived from the melting of the Antarctic ice sheet and the observed recent increase in sea ice extent in the Southern Ocean. In this study, we assess the impact of an additional freshwater flux on the trend in sea ice extent and concentration in simulations with data assimilation, spanning the period 1850–2009, as well as in retrospective forecasts (hindcasts) initialised in 1980. In the simulations with data assimilation, the inclusion of an additional freshwater flux that follows an autoregressive process improves the reconstruction of the trend in ice extent and concentration between 1980 and 2009. This is linked to a better efficiency of the data assimilation procedure but can also be due to a better representation of the freshwater cycle in the Southern Ocean. The results of the hindcast simulations show that an adequate initial state, reconstructed thanks to the data assimilation procedure including an additional freshwater flux, can lead to an increase in the sea ice extent spanning several decades that is in agreement with satellite observations. In our hindcast simulations, an increase in sea ice extent is obtained even in the absence of any major change in the freshwater input over the last decades. Therefore, while the additional freshwater flux appears to play a key role in the reconstruction of the evolution of the sea ice in the simulation with data assimilation, it does not seem to be required in the hindcast simulations. The present work thus provides encouraging results for sea ice predictions in the Southern Ocean, as in our simulation the positive trend in ice extent over the last 30 years is largely determined by the state of the system in the late 1970s.

One of the clearest manifestations of ongoing global climate change is the dramatic retreat and thinning of the Arctic sea-ice cover. While all state-of-the-art climate models consistently reproduce the sign of these changes, they largely disagree on their magnitude the reasons for which remain contentious. As such, consensual methods to reduce uncertainty in projections are lacking. Here, using the CMIP ensemble, we propose a process-oriented approach to revisit this issue. We show that intermodel differences in sea-ice loss and, more generally, in simulated sea-ice variability, can be traced to differences in the simulation of seasonal growth and melt. The way these processes are simulated is relatively independent of the complexity of the sea-ice model used, but rather a strong function of the background thickness. The larger role played by thermodynamic processes as sea ice thins further suggests that the recent and projected reductions in sea-ice thickness induce a transition of the Arctic towards a state with enhanced volume seasonality but reduced interannual volume variability and persistence, before summer ice-free conditions eventually occur. These results prompt modelling groups to focus their priorities on the reduction of sea-ice thickness biases. The research leading to these results has received funding from the Belgian Fonds National de la Recherche Scientifique (F.R.S.-FNRS), and the European Commission’s Horizon 2020 projects APPLICATE (GA 727862) and PRIMAVERA (GA 641727). We acknowledge the World Climate Research Programme’s Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modelling groups (listed in the Supplementary Information) for producing and making available their model output. We acknowledge the CESM Large Ensemble Community Project and supercomputing resources provided by NSF/CISL/Yellowstone for access to the CESM-LE data. The authors thank C. M. Bitz and D. Notz for useful discussions, and F. Kauker for providing the ITRP data. The authors thank M. M. Holland and E. C. Hunke for the review of this manuscript.

The concept of feedback is key in assessing whether a perturbation to a system is amplified or damped by mechanisms internal to the system. In polar regions, climate dynamics are controlled by both radiative and non-radiative interactions between the atmosphere, ocean, sea ice, ice sheets and land surfaces. Precisely quantifying polar feedbacks is required for a process-oriented evaluation of climate models, a clear understanding of the processes responsible for polar climate changes, and a reduction in uncertainty associated with model projections. This quantification can be performed using a simple and consistent approach that is valid for a wide range of feedbacks, offering the opportunity for more systematic feedback analyses and a better understanding of polar climate changes., Estimating the magnitude of radiative and non-radiative feedbacks is key for understanding the climate dynamics of polar regions. Here the authors propose an inclusive methodology to quantify the influence of all those feedbacks, stimulating more systematic analyses in observational and model ensembles.

Predicting the summer Arctic sea ice conditions a few months in advance has become a challenging priority. Seasonal prediction is partly an initial condition problem; therefore, a good knowledge of the initial sea ice state is necessary to hopefully produce reliable forecasts. Most of the intrinsic memory of sea ice lies in its thickness, but consistent and homogeneous observational networks of sea ice thickness are still limited in space and time. To overcome this problem, we constrain the ocean–sea ice model NEMO-LIM3 with gridded sea ice concentration retrievals from satellite observations using the ensemble Kalman filter. No sea ice thickness products are assimilated. However, thanks to the multivariate formalism of the data assimilation method used, sea ice thickness is globally updated in a consistent way whenever observations of concentration are available. We compare in this paper the skill of 27 pairs of initialized and uninitialized seasonal Arctic sea ice hindcasts spanning 1983–2009, driven by the same atmospheric forcing as to isolate the pure role of initial conditions on the prediction skill. The results exhibit the interest of multivariate sea ice initialization for the seasonal predictions of the September ice concentration and are particularly encouraging for hindcasts in the 2000s. In line with previous studies showing the interest of data assimilation for sea ice thickness reconstruction, our results thus show that sea ice data assimilation is also a promising tool for short-term prediction, and that current seasonal sea ice forecast systems could gain predictive skill from a more realistic sea ice initialization.

The sensitivity of Antarctic sea-ice to increasing glacial freshwater release into the Southern Ocean is studied in a series of 31-year ocean/sea-ice/iceberg model simulations. Glaciological estimates of ice-shelf melting and iceberg calving are used to better constrain the spatial distribution and magnitude of freshwater forcing around Antarctica. Two scenarios of glacial freshwater forcing have been designed to account for a decadal perturbation in glacial freshwater release to the Southern Ocean. For the first time, this perturbation explicitly takes into consideration the spatial distribution of changes in the volume of Antarctic ice shelves, which is found to be a key component of changes in freshwater release. In addition, glacial freshwater-induced changes in sea ice are compared to typical changes induced by the decadal evolution of atmospheric states. Our results show that, in general, the increase in glacial freshwater release increases Antarctic sea ice extent. But the response is opposite in some regions like the coastal Amundsen Sea, implying that distinct physical mechanisms are involved in the response. We also show that changes in freshwater forcing may induce large changes in sea-ice thickness, explaining about one half of the total change due to the combination of atmospheric and freshwater changes. The regional contrasts in our results suggest a need for improving the representation of freshwater sources and their evolution in climate models.

Although atmospheric reanalyses are an extremely valuable tool to study the climate of polar regions, they suffer from large uncertainties in these data-poor areas. In this work, we examine how Antarctic sea ice biases in an ocean-sea ice model are related to these forcing uncertainties. Three experiments are conducted in which the NEMO-LIM model is driven by different atmospheric forcing sets. The minimum ice extent, the ice motion and the ice thickness are sensitive to the reanalysis chosen to drive the model, while the wintertime ice extent and inner pack concentrations are barely affected. The analysis of sea ice concentration budgets allows identifying the processes leading to differences between the experiments, and also indicates that large and similar errors compared to observations are present in all three cases. Our assessment of the influence of forcing inaccuracies on the simulated Antarctic sea ice allows disentangling two types of model biases: the ones that can be reduced thanks to better atmospheric forcings, and those that would require improvements of the physics of the ice or ocean model.

International audience; Ocean-driven basal melting has been shown to be the main ablation process responsible for the recession of many Antarctic ice shelves and marine-terminating glaciers over the last decades. However, much less is known about the drivers of ice shelf melt prior to the short instrumental era. Based on diatom oxygen isotope (δ18Odiatom; a proxy for glacial ice discharge in solid or liquid form) records from western Antarctic Peninsula (West Antarctica) and Adélie Land (East Antarctica), higher ocean temperatures were suggested to have been the main driver of enhanced ice melt during the Early-to-Mid Holocene while atmosphere temperatures were proposed to have been the main driver during the Late Holocene. Here, we present a new Holocene δ18Odiatom record from Prydz Bay, East Antarctica, also suggesting an increase in glacial ice discharge since ~4500 years before present (~4.5 kyr BP) as previously observed in Antarctic Peninsula and Adélie Land. Similar results from three different regions around Antarctica thus suggest common driving mechanisms. Combining marine and ice core records along with new transient accelerated simulations from the IPSL-CM5A-LR climate model, we rule out changes in air temperatures during the last ~4.5 kyr as the main driver of enhanced glacial ice discharge. Conversely, our simulations evidence the potential for significant warmer subsurface waters in the Southern Ocean during the last 6 kyr in response to enhanced summer insolation south of 60°S and enhanced upwelling of Circumpolar Deep Water towards the Antarctic shelf. We conclude that ice front and basal melting may have played a dominant role in glacial discharge during the Late Holocene.

Climate trends in the Antarctic region remain poorly characterised, owing to the brevity and scarcity of direct climate observations and the large magnitude of interannual to decadal-scale climate variability. Here, within the framework of the PAGES Antarctica 2k working group, we build an enlarged database of ice core water stable isotope records from Antarctica, consisting of 112 records. We produce both unweighted and weighted isotopic (δ18O) composites and temperature reconstructions since 0 CE, binned at 5 and 10-year resolution, for 7 climatically-distinct regions covering the Antarctic continent. Following earlier work of the Antarctica 2k working group, we also produce composites and reconstructions for the broader regions of East Antarctica, West Antarctica, and the whole continent. We use three methods for our temperature reconstructions: i) a temperature scaling based on the δ18O-temperature relationship output from an ECHAM5-wiso model simulation nudged to ERA-interim atmospheric reanalyses from 1979 to 2013, and adjusted for the West Antarctic Ice Sheet region to borehole temperature data; ii) a temperature scaling of the isotopic normalized anomalies to the variance of the regional reanalysis temperature and iii) a composite-plus-scaling approach used in a previous continental scale reconstruction of Antarctic temperature since 1 CE but applied to the new Antarctic ice core database. Our new reconstructions confirm a significant cooling trend from 0 to 1900 CE across all Antarctic regions where records extend back into the 1st millennium, with the exception of the Wilkes Land coast and Weddell Sea coast regions. Within this long-term cooling trend from 0–1900 CE we find that the warmest period occurs between 300 and 1000 CE, and the coldest interval from 1200 to 1900 CE. Since 1900 CE, significant warming trends are identified for the West Antarctic Ice Sheet, the Dronning Maud Land coast and the Antarctic Peninsula regions, and these trends are robust across the distribution of records that contribute to the unweighted isotopic composites and also significant in the weighted temperature reconstructions. Only for the Antarctic Peninsula is this most recent century-scale trend unusual in the context of natural variability over the last 2000-years. However, projected warming of the Antarctic continent during the 21st Century may soon see significant and unusual warming develop across other parts of the Antarctic continent. The extended Antarctica 2k ice core isotope database developed by this working group opens up many avenues for developing a deeper understanding of the response of Antarctic climate to natural and anthropogenic climate forcings. The first long-term quantification of regional climate in Antarctica presented herein is a basis for data-model comparison and assessments of past, present and future driving factors of Antarctic climate.

In this study, we assess systematically the impact of different initialisation procedures on the predictability of the sea ice in the Southern Ocean. These initialisation strategies are based on three data assimilation methods: the nudging, the particle filter with sequential importance resampling and the nudging proposal particle filter. An Earth system model of intermediate complexity is used to perform hindcast simulations in a perfect model approach. The predictability of the Antarctic sea ice at interannual to multi-decadal timescales is estimated through two aspects: the spread of the hindcast ensemble, indicating the uncertainty of the ensemble, and the correlation between the ensemble mean and the pseudo-observations, used to assess the accuracy of the prediction. Our results show that at decadal timescales more sophisticated data assimilation methods as well as denser pseudo-observations used to initialise the hindcasts decrease the spread of the ensemble. However, our experiments did not clearly demonstrate that one of the initialisation methods systematically provides with a more accurate prediction of the sea ice in the Southern Ocean than the others. Overall, the predictability at interannual timescales is limited to 3 years ahead at most. At multi-decadal timescales, the trends in sea ice extent computed over the time period just after the initialisation are clearly better correlated between the hindcasts and the pseudo-observations if the initialisation takes into account the pseudo-observations. The correlation reaches values larger than 0.5 in winter. This high correlation has likely its origin in the slow evolution of the ocean ensured by its strong thermal inertia, showing the importance of the quality of the initialisation below the sea ice.

The consistency between new quantitative reconstructions of Arctic sea ice concentration based on dinocyst assemblages and the results of climate models has been investigated for the mid-Holocene. The response of the models mainly follows the increase in summer insolation, modulated to a limited extent by changes in atmospheric circulation. This leads to differences between regions in the models that are smaller than in the reconstruction. It is, however, impossible to precisely assess the models' skills because the sea ice concentration changes at the mid-Holocene are small in both the reconstructions and the models and of the same order of magnitude as the reconstruction uncertainty. Performing simulations with data assimilation using the model LOVECLIM amplifies the regional differences and improves the model–data agreement as expected. This is mainly achieved through a reduction of the southward winds in the Barents Sea and an increase in the westerly winds in the Canadian Basin, inducing an increase in the ice concentration in the Barents and Chukchi seas. This underlines the potential role of atmospheric circulation in explaining the reconstructed changes during the Holocene.

The large natural variability of the Antarctic sea ice is a key characteristic of the system that might be responsible for the small positive trend in sea ice extent observed since 1979. In order to gain insight in the processes responsible for this variability, we have analysed in a control simulation performed with a coupled climate model a strong positive ice-ocean feedback that amplifies sea ice variations. When sea ice concentration increases in a region, in particular close to the ice edge, the mixed layer depth tends to decrease. This can be caused by a net inflow of ice and thus of freshwater that stabilizes the water column. Another stabilizing mechanism at interannual time scales that appears more widespread in our simulation is associated with the downward salt transport due to the seasonal cycle of ice formation: brine is released in winter when ice is formed and mixed over a deep layer while the freshwater flux caused by ice melting is included in a shallow layer, resulting in a net vertical transport of salt. Because of this stronger stratification due to the presence of sea ice, more heat is stored at depth in the ocean and the vertical oceanic heat flux is reduced, which contributes to maintain a higher ice extent. This positive feedback is not associated with a particular spatial pattern. Consequently, the spatial distribution of the trend in ice concentration is largely imposed by the wind changes that can provide the initial perturbation. A positive freshwater flux could alternatively be the initial trigger but the amplitude of the final response of the sea ice extent is finally set up by the amplification related to ice-ocean feedback. Initial conditions have also an influence as the chance to have a large increase in ice extent is higher if starting from a state characterized by a low value.

Reproducible climate reconstructions of the Common Era (1 CE to present) are key to placing industrial-era warming into the context of natural climatic variability. Here we present a community-sourced database of temperature-sensitive proxy records from the PAGES2k initiative. The database gathers 692 records from 648 locations, including all continental regions and major ocean basins. The records are from trees, ice, sediment, corals, speleothems, documentary evidence, and other archives. They range in length from 50 to 2000 years, with a median of 547 years, while temporal resolution ranges from biweekly to centennial. Nearly half of the proxy time series are significantly correlated with HadCRUT4.2 surface temperature over the period 1850-2014. Global temperature composites show a remarkable degree of coherence between high- and low-resolution archives, with broadly similar patterns across archive types, terrestrial versus marine locations, and screening criteria. The database is suited to investigations of global and regional temperature variability over the Common Era, and is shared in the Linked Paleo Data (LiPD) format, including serializations in Matlab, R and Python., PAGES, a core project of Future Earth, is supported by the U.S. and Swiss National Science Foundations. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. Some of this work was conducted as part of the North America 2k Working Group supported by the John Wesley Powell Center for Analysis and Synthesis, funded by the U.S. Geological Survey. B. Bauer, W. Gross, and E. Gille (NOAA National Centers for Environmental Information) are gratefully acknowledged for helping assemble the data citations and creating the NCEI versions of the PAGES 2k data records. We thank all the investigators whose commitment to data sharing enables the open science ethos embodied by this project.

We derive the terms in the Antarctic sea ice concentration budget from the output of three models, and compare them to observations of the same terms. Those models include two climate models from the 5th Coupled Model Intercomparison Project (CMIP5) and one ocean–sea ice coupled model with prescribed atmospheric forcing. Sea ice drift and wind fields from those models, in average over April-October 1992-2005, all exhibit large differences with the available observational or reanalysis datasets. However, the discrepancies between the two distinct ice drift products or the two wind reanalyses used here are sometimes even greater than those differences. Two major findings stand out from the analysis. Firstly, large biases in sea ice drift speed and direction in exterior sectors of the sea ice covered region tend to be systematic and consistent with those in winds. This suggests that sea ice errors in these areas are most likely wind-driven, so as errors in the simulated ice motion vectors. The systematic nature of these biases is less prominent in interior sectors, nearer the coast, where sea ice is mechanically constrained and its motion in response to the wind forcing more depending on the model rheology. Second, the intimate relationship between winds, sea ice drift and the sea ice concentration budget gives insight on ways to categorize models with regard to errors in their ice dynamics. In exterior regions, models with seemingly too weak winds and slow ice drift consistently yield a lack of ice velocity divergence and hence a wrong wintertime sea ice growth rate. In interior sectors, too slow ice drift, presumably originating from issues in the physical representation of sea ice dynamics as much as from errors in surface winds, leads to wrong timing of the late winter ice retreat. Those results illustrate that the applied methodology provides a valuable tool for prioritizing model improvements based on the ice concentration budget–ice drift biases–wind biases relationship prevailing in the simulation of Antarctic sea ice over the last decades.

The heterogeneity of ocean surface conditions associated with a spatially variable sea ice cover needs to be represented in models in order to represent adequately mixed layer processes and the upper ocean density structure. This study assesses the sensitivity of the ocean-sea ice model NEMO-LIM to a subgrid-scale representation of ice-ocean interactions. The sea ice component includes an ice thickness distribution, which provides heterogeneous surface buoyancy fluxes and stresses. A multi-column ocean scheme is developed to take them explicitly into account, by computing convection and turbulent vertical mixing separately in the open water/lead fraction of grid cells and below each ice thickness category. For the first time in a three-dimensional simulation, the distinct temperature and salinity profiles of the ocean columns are allowed to be maintained over several time steps. It is shown that the model response is highly sensitive to the homogenization time scale between the columns. If the latter are laterally mixed with time scales shorter than 10 h, subgrid-scale effects exist but the mean state is practically unaffected. For longer mixing time scales, in both hemispheres, the main impacts are reductions in under-ice mean mixed layer depths and in the summer melt of sea ice, following decreased oceanic heat flux at the ice base. Large changes in the open water temperature in summer suggest that the scheme could trigger important feedback processes in coupled simulations.

The Holocene climate is simulated in a 9000-yr-long transient experiment performed with the ECBilt-CLIO-VECODE coupled atmosphere-sea ice-ocean-vegetation model. This experiment is forced with annually varying orbital parameters and atmospheric concentrations of CO2 and CH4. The objective is to study the impact of these long-term forcings on the surface temperature evolution during different seasons in the high-latitude Southern Hemisphere. We find in summer a thermal optimum in the midHolocene (6-3 ka BP), with temperatures locally 3°C above the preindustrial mean. In autumn the temperatures experienced a long-term increase, particularly during the first few thousand years. The opposite trend was simulated for winter and spring, with a relatively warm Southern Ocean at 9 ka BP in winter (up to 3.5°C above the preindustrial mean) and a warm continent in spring (+3°C), followed by a gradual cooling towards the present. These long-term temperature trends can be explained by a combination of (1) a delayed response to orbital forcing, with temperatures lagging insolation by 1 to 2 months owing to the thermal inertia of the system, and (2) the long memory of the Southern Ocean. This long memory is related to the storage of the warm late winter-spring anomaly below the shallower summer mixed layer until next winter. Sea ice plays an important role as an amplifying factor through the ice-albedo and ice-insulation feedbacks. Our experiments can help to improve our understanding of the Holocene signal in proxies. For instance, the results suggest that, in contrast to recent propositions, teleconnections to the Northern Hemisphere appear not necessarily to explain the history of Southern Hemisphere temperature changes during the Holocene.

Short-term and decadal sea-ice prediction systems need a realistic initial state, generally obtained using ice-ocean model simulations with data assimilation. However, only sea-ice concentration and velocity data are currently assimilated. In this work, an Ensemble Kalman Filter system is used to assimilate observed ice concentration and freeboard (i.e. thickness of emerged sea ice) data into a global coupled ocean–sea-ice model. The impact and effectiveness of our data assimilation system is assessed in two steps: firstly, through the assimilation of synthetic data (i.e., model-generated data) and, secondly, through the assimilation of satellite data. While ice concentrations are available daily, freeboard data used in this study are only available during six one-month periods spread over 2005–2007. Our results show that the simulated Arctic and Antarctic sea-ice extents are improved by the assimilation of synthetic ice concentration data. Assimilation of synthetic ice freeboard data improves the simulated sea-ice thickness field. Using real ice concentration data enhances the model realism in both hemispheres. Assimilation of ice concentration data significantly improves the total hemispheric sea-ice extent all year long, especially in summer. Combining the assimilation of ice freeboard and concentration data leads to better ice thickness, but does not further improve the ice extent. Moreover, the improvements in sea-ice thickness due to the assimilation of ice freeboard remain visible well beyond the assimilation periods.

The annual and seasonal temperatures in the Arctic over the past 1150 years are analyzed in simulations performed with the three-dimensional Earth system model of intermediate complexity LOVECLIM forced by changes in solar irradiance, volcanic activity, land use, greenhouse gas concentrations and orbital parameters. The response of the system to individual forcings for each season is examined in order to evaluate the contribution of each forcing to the seasonal contrast. For summer, our results agree relatively well with the reconstruction of Kaufman et al. (2009). Our modelling results suggest that the temperature changes during this period were characterized by large seasonal differences. In particular, while annual mean temperatures display a decreasing trend during the pre-industrial period, spring temperatures appear to rise. The variations in the Earth’s orbital parameters are the main cause for those seasonal differences. Larger climate variations are simulated in autumn compared with the other seasons in response to each forcing, particularly in response to changes in greenhouse gas concentration during the industrial period and in response to land use forcing, which surprisingly has a significant impact on Arctic temperature. These contrasting changes for the different seasons also underline the need for an adequate estimate of the season represented by a proxy.

Two hindcast (1983–2007) simulations are performed with the global, ocean-sea ice models NEMO-LIM2 and NEMO-LIM3 driven by atmospheric reanalyses and climatologies. The two simulations differ only in their sea ice component, while all other elements of experimental design (resolution, initial conditions, atmospheric forcing) are kept identical. The main differences in the sea ice models lie in the formulation of the subgrid-scale ice thickness distribution, of the thermodynamic processes, of the sea ice salinity and of the sea ice rheology. To assess the differences in model skill over the period of investigation, we develop a set of metrics for both hemispheres, comparing the main sea ice variables (concentration, thickness and drift) to available observations and focusing on both mean state and seasonal to interannual variability. Based upon these metrics, we discuss the physical processes potentially responsible for the differences in model skill. In particular, we suggest that (i) a detailed representation of the ice thickness distribution increases the seasonal to interannual variability of ice extent, with spectacular improvement for the simulation of the recent observed summer Arctic sea ice retreats, (ii) the elastic-viscous-plastic rheology enhances the response of ice to wind stress, compared to the classical viscous-plastic approach, (iii) the grid formulation and the air-sea ice drag coefficient affect the simulated ice export through Fram Strait and the ice accumulation along the Canadian Archipelago, and (iv) both models show less skill in the Southern Ocean, probably due to the low quality of the reanalyses in this region and to the absence of important small-scale oceanic processes at the models' resolution (~1°).

One of the main features of the oceanic circulation along Antarctica is the Antarctic Slope Current (ASC). This circumpolar current flows westwards and contributes to communication between the three major oceanic basins around Antarctica. The ASC is not very well known due to remote location and the presence of sea ice during several months, allowing in situ studies only during summertime. Moreover, only few modelling studies of this current have been carried out. Here, we investigate the sensitivity of this simulated current to four different resolutions in a coupled ocean-sea ice model and to two different atmospheric forcing sets. Two series of simulations are conducted. For the first series, global model configurations are run at coarse (2°) to eddy-permitting (0.25°) resolutions with the same atmospheric forcing. For the second series, simulations with two different atmospheric forcings are performed using a regional circumpolar configuration (south of 30° S) at 0.5° resolution. The first atmospheric forcing is based on a global atmospheric reanalysis and satellite data, while the second is based on a downscaling of the global atmospheric reanalysis by a regional atmospheric model calibrated to Antarctic meteorological conditions. Sensitivity experiments to resolution indicate that a minimum model resolution of 0.5° is needed to capture the dynamics of the ASC in terms of water mass transport and recirculation. Sensitivity experiments to atmospheric forcing fields shows that the wind speed along the Antarctic coast strongly controls the water mass transport and the seasonal cycle of the ASC. An increase in annual mean of easterlies by about 30 % leads to an increase in the mean ASC transport by about 40 %. Similar effects are obtained on the seasonal cycle: using a wind forcing field with a larger seasonal cycle (+30 %) increases by more than 30 % the amplitude of the seasonal cycle of the ASC. To confirm the importance of wind seasonal cycle, a simulation without wind speed seasonal cycle is carried out. This simulation shows a decrease by more than 50 % of the amplitude of the ASC transport seasonal cycle without changing the mean value of ASC transport.

Little is known about errors in the atmospheric forcings of large-scale sea ice-ocean models around Antarctica. These forcings involve atmospheric reanalyses, typically those from the National Center for Environmental Prediction and National Center from Atmospheric Research (NCEP-NCAR), climatologies, and empirical parameterizations of atmosphere-ice heat and radiation fluxes. In the present paper, we evaluate the atmospheric forcing fields of sea ice models in the Southern Ocean using meteorological and radiation observations from two drifting station experiments over Antarctic sea ice. These are Sea Ice Mass Balance in the Antarctic (SIMBA, Bellingshausen Sea, October 2007) and ISPOL (Ice Station POLarstern, Weddell Sea, December 2004). For the comparison, it is assumed that those point measurements are representative of the whole model grid cell they were collected in. Analysis suggests that the NCEP-NCAR reanalyses have relatively low biases for variables that are assimilated by the system (temperature, winds and humidity) and are less accurate for those which are not (cloud fraction and radiation fluxes). The main deficiencies are significant day-to-day errors in air temperature (root-mean-square error 1.4-3.8°C) and a 0.2-0.6 g/kg mean overestimation in NCEP-NCAR specific humidity. In addition, associated with an underestimation of cloud fraction, NCEP-NCAR shortwave radiation features a large positive bias (43-109 w/m2), partly compensated by a 20-45 W/m2 negative bias in longwave radiation. Those biases can be drastically reduced by using empirical formulae of radiation fluxes and climatologies of relative humidity and cloud cover. However, this procedure leads to a loss of day-to-day and interannual variability in the radiation fields. We provide technical recommendations on how the radiation forcing should be handled to reduce sea ice model forcing errors. The various errors in forcing fields found here should not hide the great value of atmospheric reanalyses for the simulation of the ice-ocean system.

We use the Earth system model of intermediate complexity LOVECLIM to show the effect of coupling interactive ice sheets on the climate sensitivity of the model on a millennial time scale. We compare the response to a 2xCO2 warming scenario between fully coupled model versions including interactive Greenland and Antarctic ice sheet models and model versions with fixed ice sheets. For this purpose an ensemble of different parameter sets have been defined for LOVECLIM, covering a wide range of the model's sensitivity to greenhouse warming, while still simulating the present-day climate and the climate evolution over the last millennium within observational uncertainties. Additional freshwater fluxes from the melting ice sheets have a mitigating effect on the model's temperature response, leading to generally lower climate sensitivities of the fully coupled model versions. The mitigation is effectuated by changes in heat exchange within the ocean and at the sea-air interface, driven by freshening of the surface ocean and amplified by sea-ice related feedbacks. The strength of the effect depends on the response of the ice sheets to the warming and on the model's climate sensitivity itself. The effect is relatively strong in model versions with higher climate sensitivity due to the relatively large polar amplification of LOVECLIM. With the ensemble approach in this study we cover a wide range of possible model responses.

The main characteristics of the new version 1.2 of the three-dimensional Earth system model of intermediate complexity LOVECLIM are briefly described. LOVECLIM 1.2 includes representations of the atmosphere, the ocean and sea ice, the land surface (including vegetation), the ice sheets, the icebergs and the carbon cycle. The atmospheric component is ECBilt2, a T21, 3-level quasi-geostrophic model. The ocean component is CLIO3, which consists of an ocean general circulation model coupled to a comprehensive thermodynamic-dynamic sea-ice model. Its horizontal resolution is of 3° by 3°, and there are 20 levels in the ocean. ECBilt-CLIO is coupled to VECODE, a vegetation model that simulates the dynamics of two main terrestrial plant functional types, trees and grasses, as well as desert. VECODE also simulates the evolution of the carbon cycle over land while the ocean carbon cycle is represented by LOCH, a comprehensive model that takes into account both the solubility and biological pumps. The ice sheet component AGISM is made up of a three-dimensional thermomechanical model of the ice sheet flow, a visco-elastic bedrock model and a model of the mass balance at the ice-atmosphere and ice-ocean interfaces. For both the Greenland and Antarctic ice sheets, calculations are made on a 10 km by 10 km resolution grid with 31 sigma levels. LOVECLIM1.2 reproduces well the major characteristics of the observed climate both for present-day conditions and for key past periods such as the last millennium, the mid-Holocene and the Last Glacial Maximum. However, despite some improvements compared to earlier versions, some biases are still present in the model. The most serious ones are mainly located at low latitudes with an overestimation of the temperature there, a too symmetric distribution of precipitation between the two hemispheres, and an overestimation of precipitation and vegetation cover in the subtropics. In addition, the atmospheric circulation is too weak. The model also tends to underestimate the surface temperature changes (mainly at low latitudes) and to overestimate the ocean heat uptake observed over the last decades., Fonds national de la recherche scientifique (Belgium), Belgian Science Policy Office, Institut national des sciences de l'univers (France), Netherlands Organization for Scientific Research (RAPID project ORMEN)

Sea ice has a non-zero salinity that varies in space and time. This affects the sea ice thermal properties as well as the ice–ocean salt and freshwater exchanges, which may influence the sea ice mass balance and the polar oceans’ characteristics. However, current sea ice models neglect or misrepresent the ice salinity. In this paper, we address the question of the importance of large-scale sea ice salinity variations for the sea ice mass balance and the upper ocean. To examine this question, we formulate salinity variations in the framework of the sea ice thickness distribution theory, using a simple parameterization for brine entrapment and drainage. The latter is tested one-dimensionally and then included in a three-dimen- sional large-scale ice–ocean model, OPA9-LIM3, which is run over 1970–2006, forced by a combination of atmospheric reanalyses and climatologies. Due to differences in the physical forcings, the model sim- ulates Arctic and Antarctic sea ice salinity fields that profoundly differ, with a seasonal cycle that is found in reasonable agreement with available ice core data. Then, the role of salinity variations is analyzed by comparing the results of the simulation including the interactive salinity with several sensitivity runs using simpler representations of ice salinity. The simulated large-scale sea ice mass balance and upper ocean characteristics are found to be quite sensitive to the representation of ice salinity. In the Arctic, salinity variations induce changes in ice thickness up to one meter in some regions, due to modifications in the sea ice thermal properties. Around Antarctica, including salinity variations increases the simulated winter sea ice volume by up to 28% because of changes in ice–ocean interactions that stabilize the ocean. The model sensitivity to the sea ice salinity is of the same order of magnitude as a 10% change in bare ice albedo. Given the importance of salinity on the simulated sea ice characteristics, sea ice salinity variations should be included in assessments of the response of the high-latitude oceans to ongoing and future cli- mate change

Melting icebergs are a mobile source of fresh water as well as a sink of latent heat. In most global climate models, the spatio-temporal redistribution of fresh water and latent heat fluxes related to icebergs is parameterized by an instantaneous more or less arbitrary flux distribution over some parts of the oceans. It is uncertain if such a parameterization provides a realistic representation of the role of icebergs in the coupled climate system. However, icebergs could have a significant climate role, in particular during past abrupt climate change events which have been associated with armada's of icebergs. We therefore present the interactive coupling of a global climate model to a dynamic thermodynamic iceberg model, leading to a more plausible spatio-temporal redistribution of fresh water and heat fluxes. We show first that our model is able to reproduce a reasonable iceberg distribution in both hemispheres when compared to recent data. Second, in a series of sensitivity experiments we explore cooling and freshening effects of dynamical icebergs on the upper Southern Ocean and we compare these dynamic iceberg results to the effects of an equivalent parameterized iceberg flux. In our model without interactive icebergs, the parameterized fluxes are distributed homogeneously South of 55°S, whereas dynamic icebergs are found to be concentrated closer to shore except for a plume of icebergs floating North-East from the tip of the Antarctic Peninsula. Compared to homogeneous fluxes, the dynamic icebergs lead to a 10% greater net production of Antarctic bottom water (AABW). This increased bottom water production involves open ocean convection, which is enhanced by a less efficient stratification of the ocean when comparing to a homogeneous flux distribution. Icebergs facilitate the formation of sea-ice. In the sensitivity experiments, both the fresh water and the cooling flux lead to a significant increase in sea-ice area of 12% and 6%, respectively, directly affecting the highly coupled and interactive air/sea/ice system. The consequences are most pronounced along the sea-ice edge, where this sea-ice facilitation has the greatest potential to affect ocean stratification, for example by heat insulation and wind shielding, which further amplifies the cooling and freshening of the surface waters. © 2008 Elsevier Ltd. All rights reserved.

Simulations performed with the climate model LOVECLIM, aided with a simple data assimilation technique that forces a close matching of simulated and observed surface temperature variations, are able to reasonably reproduce the observed changes in the lower atmosphere, sea ice and ocean during the second half of the twentieth century. Although the simulated ice area slightly increases over the period 1980–2000, in agreement with observations, it decreases by 0.5 × 106 km2 between early 1960s and early 1980s. No direct and reliable sea ice observations are available to firmly confirm this simulated decrease, but it is consistent with the data used to constrain model evolution as well as with additional independent data in both the atmosphere and the ocean. The simulated reduction of the ice area between the early 1960s and early 1980s is similar to the one simulated over that period as a response to the increase in greenhouse gas concentrations in the atmosphere while the increase in ice area over the last decades of the twentieth century is likely due to changes in atmospheric circulation. However, the exact contribution of external forcing and internal variability in the recent changes cannot be precisely estimated from our results. Our simulations also reproduce the observed oceanic subsurface warming north of the continental shelf of the Ross Sea and the salinity decrease on the Ross Sea continental shelf. Parts of those changes are likely related to the response of the system to the external forcing. Modifications in the wind pattern, influencing the ice production/melting rates, also play a role in the simulated surface salinity decrease.

Deep-sea and ice-core records show that interglacial periods were overall less "warm" before about 420 000 years ago than after, with relatively higher ice volume and lower greenhouse gases concentration. This is particularly the case for the interglacial Marine Isotope Stage 13 which occurred about 500 000 years ago. However, by contrast, the loess and other proxy records from China suggest an exceptionally active East Asian summer monsoon during this interglacial. A three-dimension Earth system Model of Intermediate complexity was used to understand this seeming paradox. The astronomical forcing and the remnant ice sheets present in Eurasia and North America were taken into account in a series of sensitivity experiments. Expectedly, the seasonal contrast is larger and the East Asian summer monsoon is reinforced compared to Pre-Industrial time when Northern Hemisphere summer is at perihelion. Surprisingly, the presence of the Eurasian ice sheet was found to reinforce monsoon, too, through a south-eastwards perturbation planetary wave. The trajectory of this wave is influenced by the Tibetan plateau.