The Antarctic sea ice extent has displayed several regime shifts over the past 65 years. Consistent lines of evidence indicate a decline in Antarctic sea ice extent from 1958 to 1978, which precedes the availability of continuous satellite observations. Subsequently, there was a significant sea ice expansion over 1979–2015 before the large drop observed in the past few years that led to record lows. The origin of those shifts and contrasting trends are analyzed here using a new reconstruction of atmospheric temperature, sea level pressure and sea ice extent spanning the period 1958-2023. We employ a data assimilation method that combines long simulations as well as large ensembles performed with climate models with long-term station-based records of temperature and sea level pressure at mid and high latitudes of the Southern Hemisphere. The reconstruction is thus totally independent from sea ice extent observations that are used as validation, showing the good performance of the method. In contrast to previous reconstructions and estimates, reconstructing simultaneously the atmospheric circulation, temperature, and sea ice extent ensures compatibility among the variables and thus a more straightforward dynamical interpretation. Our reconstruction indicates that no change in the reconstructed atmospheric circulation could be directly related to the regime shifts in sea ice extent trends but the covariance structure of the temperature strongly varies across periods, with more homogenous temperature anomalies for the early and recent periods and a more complex spatial pattern for the years 1979–2015. This might suggest a time-dependent contribution of the ocean, which will be further analyzed in a simulation performed with the NEMO model driven by the ERA5 reanalysis.

How to cite: Goosse, H., Dalaiden, Q., Francis, F., and Fogt, R.: Origin of the trends in Antarctic sea ice extent over the period 1958-2023 , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-875, https://doi.org/10.5194/egusphere-egu24-875, 2024.

Antarctic sea ice extent (SIE) reached a new record low of 1.79 million km² on 21 February 2023, 38% lower than the climatological average. In this study, we trace this record back to its possible origins by providing a detailed view on the evolution of the coupled ocean-atmosphere-sea ice system during the 12 months that preceded the event (March 2022 to February 2023). The impact of preceding winter and spring conditions on the summer minimum is assessed with the help of observations, reanalyses, and output from a regional ocean-sea ice coupled model NEMO3.6-LIM3. We find that the 2022-2023 annual cycle was characterized by consistently low SIE values throughout the year preceding the record, by anomalously high SIE melting rates in December 2022, and by circumpolar negative SIE anomalies in almost all basins of the Southern Ocean in February 2023. Through autumn and winter (March to August 2022), advection-induced positive air temperature anomalies inhibited the development of sea ice in the Weddell and Bellingshausen Seas, which preconditioned an ice-free state in the Bellingshausen Sea as early as October 2022. Concurrently, strong southerly winds in the Eastern Ross Sea caused by an anomalously deep Amundsen Sea Low in spring (September to November) transported significant volumes of sea ice northward, contributing to severe melting offshore in December and, through increased divergence near the coast, triggered the ice-albedo feedback onshore. As a consequence, a coastal polynya appeared in the western part of the Amundsen Sea due to stronger surface sea ice melting. This ice-albedo feedback was unusually active in late 2022 and favored accelerated melt towards the minimum in February 2023. This study highlights the impacts of multifactorial processes during the preceding seasons to explain the recent summer sea ice minima.

How to cite: Wang, J., Massonnet, F., Goosse, H., Luo, H., Yang, Q., and Barthélemy, A.: The 2023 record low Antarctic sea ice traced to synergistic influences of preconditioning, wind-induced transport and the ice albedo feedback, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1737, https://doi.org/10.5194/egusphere-egu24-1737, 2024.

Since 2015, Antarctic sea ice extent has declined by ~53%, and reached consecutive record lows in the austral summers of 2022 and 2023. These events have raised major concern as to whether a regime shift towards more extreme and frequent low sea ice extents has begun. Potential impacts on the climate system are far-reaching and continent-wide studies are urgently needed. Due to Antarctica's remote and harsh environment, in situ observations are however sparse. NASA's ICESat-2, a laser altimeter launched in 2018, provides precise sea ice surface elevation data at high-resolution, with along-track sampling every ~0.7 m. This sampling allows us to resolve meter-scale features in the sea ice pack, such as pressure ridges, which modify the shape of the ice thickness distribution and play an important role in ocean-atmosphere momentum flux through form drag. We apply a bespoke processing technique, called the University of Maryland-Ridge Detection Algorithm (UMD-RDA), to derive the surface topography of sea ice in the Southern Ocean over a 5-year period, spanning 2018-2023. Using the UMD-RDA we can capture seasonal and interannual variability in surface roughness, pressure ridge sail height, and ridge sail spacing. We find that during the 2018-2023 period, on average, across the full Southern Ocean ice pack, sea ice surface roughness reaches a maximum in January/February followed by a minimum in April. Sail height is at its maximum in January and minimum in June, while sail spacing is at its minimum in January and maximum in June. Interannual variability shows that the 2023 season is an outlier with respect to the 5-year 2018-2023 average. In 2023 there was a decrease of ~20% in surface roughness during the April minimum, a decrease of ~8% in sail height during the June minimum, and an increase of ~31% in sail spacing during the June maximum. This suggests that, in 2023, the sea ice pack was less deformed overall than in preceding years. We also assess seasonal and interannual variability in surface roughness and ridge morphology in five distinct regions including the Amundsen-Bellingshausen (A-B), Ross, Pacific, Indian, and Weddell Seas. The A-B, Ross, and Pacific sectors showed the greatest change in 2023, with respect to the 2018-2023 average, with a decrease in surface roughness of ~34%, ~26%, and ~14%, respectively. Sail spacing within the A-B, Ross, and Pacific sectors, with respect to the 2018-2023 average, increased by ~83%, ~61%, and ~35%, respectively. Furthermore, the ICESat-2 ATL10 sea ice freeboard dataset shows a ~50% decrease in freeboard within the A-B sector in 2023. These results provide evidence that a substantial amount of thicker, older, and rougher ice was likely exported out of the A-B region. Our results can provide insight into the mechanisms responsible for the recent record low sea ice extents and could uncover new relationships between deformation, roughness, and ice extent.

How to cite: Duncan, K. and Farrell, S.: Annual Cycle of Antarctic Sea Ice Deformation from ICESat-2, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10502, https://doi.org/10.5194/egusphere-egu24-10502, 2024.

The impact of melt ponds on sea ice albedo has been observed and documented. In general circulation models, ponds are now accounted for through indirect diagnostic treatments (“implicit” schemes) or prognostic melt-pond parameterizations (“explicit” schemes). However, there has been a lack of studies showing the impacts of these schemes on simulated Arctic climate. We focus here on rectifying this using the general circulation model HadGEM3, one of the few models with a detailed explicit pond scheme. We identify the impact of melt ponds on the sea ice and climate, and associated ice–ocean–atmosphere interactions. We run a set of constant forcing simulations for three different periods and show, for the first time, that using mechanistically different pond schemes can lead to very significantly different sea ice and climate states. Under near-future conditions, an implicit scheme never yields an ice-free summer Arctic, while an explicit scheme yields an ice-free Arctic in 35% of years and raises autumn Arctic air temperatures by 5° to 8°C. We find that impacts on climate and sea ice depend on the ice state: under near-future and last-interglacial conditions, the thin sea ice is very sensitive to pond formation and parameterization, whereas during the preindustrial period the thicker sea ice is less sensitive to the pond scheme choice. Both of these two commonly used parameterizations of sea ice albedo yield similar results under preindustrial conditions but in warmer climates lead to very different Arctic sea ice and ocean and atmospheric temperatures. Thus, changes to physical parameterizations in the sea ice model can have large impacts on simulated sea ice, ocean, and atmosphere.

How to cite: Diamond, R., Schroeder, D., Sime, L., Ridley, J., and Feltham, D.: The Significance of the Melt-Pond Scheme in a CMIP6 Global Climate Model, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6230, https://doi.org/10.5194/egusphere-egu24-6230, 2024.

Future projections of Arctic sea ice remain poorly constrained, due in large part to the significant inter-model spread across the CMIP6 archive. Various recent studies have explored novel calibration methods to better constrain future sea ice conditions, especially the timing of an ice-free Arctic, but can come to different conclusions based on the calibration approach taken. Some approaches exclude outlier models, while others seek to exploit sensitivities of sea ice area/extent to global warming (e.g., Northern Hemisphere temperatures) to better constrain the multi-model ensemble. As long-term and reliable observations of sea ice thickness are lacking, calibration efforts have primarily relied on sea ice concentration/area data from the passive microwave satellite record. 

We are leading a new NASA-funded effort to utilize the multi-year record of observed sea ice freeboard and derived sea ice thickness from ICESat-2, together with similar data from the original ICESat and ESA’s CryoSat-2 missions, to reduce inter-model uncertainty in future sea ice projections. Although the sea ice altimetry data record is more limited in space and time than the longer-term passive microwave concentration record, it can offer significant advantages; for example, freeboard is measured very accurately by modern laser altimetry satellites, providing more information within the consolidated ice pack, and is now output by some of the CMIP6 models, enabling direct comparisons between the model and the satellite measurements. Only a small fraction of CMIP6 models provide the direct output of derived freeboard so assumptions (mainly related to the bulk ice and snow density) need to be made when estimating freeboard with the core model output. Initial results suggest this can have an important impact on the comparisons. Converting the observations of freeboard to sea ice thickness introduces significantly more uncertainty to the observed data but can radically simplify the model comparison effort. 

In this presentation we will showcase our initial efforts to better utilize the satellite altimetry record for calibrating CMIP6 simulations of future sea ice conditions across both poles, but with a primary focus on projections of the timing of an ice-free Arctic. We discuss some of the nuances of using freeboard as a more direct observational constraint compared to thickness, providing motivation for more modeling groups to provide the direct ice density and freeboard outputs in the lead-up to CMIP7. 

Finally, our analysis has all been carried out within the NASA-supported CryoCloud compute environment using the cloud-based (AWS) CMIP6 data archive, so we include additional insight into the benefits of this analysis approach and the small but important impact from differences in model output availability (compared to the recent IPCC analysis). 

How to cite: Petty, A., Cardinale, C., and Smith, M.: Improving sea ice projections with the modern-era satellite altimetry record of freeboard and thickness, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10681, https://doi.org/10.5194/egusphere-egu24-10681, 2024.

Sea-ice thickness is a crucial parameter for a variety of scientific disciplines, including climate science, oceanography, and ecology. It plays a vital role in regulating exchanges of heat, moisture and momentum between the polar oceans and the atmosphere, influencing ocean currents, and affecting local cloud cover and precipitation.

The ESA-funded project SIN’XS, led by NOVELTIS, AWI, LEGOS, and UCL, aims to comprehensively assess available sea-ice thickness and snow thickness products and their uncertainties. We are building up a database of large-scale datasets (satellite-based and models) as well as reference datasets (in-situ, airborne, moorings, etc.) to better understand the variability and change in observed ice thickness in both hemispheres. A web portal enables users to interactively explore and analyse data. In the talk, we will introduce the project and database and present the first results. We will also encourage potential collaborators to contribute to the project by submitting data to our website. We look forward to collaborating with the scientific community to better understand the complexities of sea-ice thickness and its impact on our planet. The ultimate goal of SIN’XS is to provide a reconciled and comprehensive sea-ice thickness estimate.

How to cite: Ludwig, V., Belot, C., Da Silva, E., Fleury, S., Haas, C., Hendricks, S., Munesa, E., Pastor, J., Paul, S., Tsamados, M., Bouffard, J., Di Bella, A., and Scagliola, M.: Comprehensive assessment of sea-ice thickness datasets: The ESA SIN’XS project, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9852, https://doi.org/10.5194/egusphere-egu24-9852, 2024.

Sea-ice deformation is commonly estimated from satellite imagery in low spatial and temporal resolutions. This coincides with the fact that the lower bound of scale invariance in ice deformation is analytically estimated at the scale of ice thickness. Estimating deformation patterns from more accurate buoy records can in turn be problematic due to their sparse spatial coverage while the previous analysis of radar imagery has been disturbed noisy data. In response to the gap in high resolution empirical data, we deploy a novel deep neural network-based motion tracking method with ice-radar imagery gathered continuously during MOSAiC expedition for statistical analysis of sea ice deformation. The proposed method enables estimating ice dynamics at length scales down to 10 meters at a 10-minute temporal scale in a 10 km ×10 km domain. Overcoming issues with high-frequency noise in radar data, we output ~10^8 daily deformation-rate estimates with accuracy comparable or higher than those gained by using ice buoys. The method allows quantification of the highly intermittent and localized deformation and, thus, the analysis of established scaling laws at resolutions never analyzed before. In light of the changing ice conditions in the Arctic, we emphasize seasonal variability and separation between ice zones.

How to cite: Uusinoka, M., Polojärvi, A., and Haapala, J.: Local-scale analysis on sea-ice deformation based on radar imagery and deep learning, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19034, https://doi.org/10.5194/egusphere-egu24-19034, 2024.

The Arctic has experienced a rapid sea ice loss in the Barents and Kara Seas in winter during the last few decades. Such sea ice loss has been attributed to anthropogenic warming and internal variability, but their relative contribution remains unclear. Using machine-learning methods and large ensemble simulations, we successfully reproduce Barents-Kara sea ice trends as the joint impact of anthropogenic and internal atmospheric variability components. Results show that the loss of Barents-Kara sea ice extent over the recent 20 years (1997-2017) is significantly enhanced by atmospheric internal variability (>50%) acting on top of anthropogenic warming. Overall, this study highlights that internal variability plays a more important role in recent winter Arctic sea ice loss than previously thought, and promotes similar machine-learning methods for attributing sea ice trends in other polar regions and seasons.

How to cite: Siew, P. Y. F., Wu, Y., Ting, M., Zheng, C., Ding, Q., and Seager, R.: Significant contribution of internal variability to recent Barents-Kara sea ice loss in winter, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14415, https://doi.org/10.5194/egusphere-egu24-14415, 2024.

Arctic sea ice outflow to the Atlantic Ocean is essential to the Arctic sea ice mass budget and the marine environments in the Barents and Greenland seas (BGS). With the extremely positive Arctic Oscillation (AO) in winter (JFM) 2020, the feedback mechanisms of anomalies in Arctic sea ice outflow and their impacts on winter–spring sea ice and other marine environmental conditions in the subsequent months until early summer in the BGS were investigated. The results reveal that the total sea ice area flux (SIAF) through the Fram Strait, the Svalbard–Franz Josef Land passageway, and the Franz Josef Land–Novaya Zemlya passageway in winter and June 2020 was higher than the 1988–2020 climatology. The relatively large total SIAF, which was dominated by that through the Fram Strait (77.6 %), can be significantly related to atmospheric circulation anomalies, especially with the positive phases of the winter AO and the winter–spring relatively high air pressure gradient across the western and eastern Arctic Ocean. Such abnormal winter
atmospheric circulation patterns have induced wind speeds anomalies that accelerate sea ice motion (SIM) in the Atlantic sector of Transpolar Drift, subsequently contributing to the variability in the SIAF (R=+0.86, P<0.001). The abnormally large Arctic sea ice outflow led to increased sea
ice area (SIA) and thickness in the BGS, which has been observed since March 2020, especially in May–June. The increased SIA impeded the warming of the sea surface temperature (SST), with a significant negative correlation between April SIA and synchronous SST as well as the lagging SST of 1–3 months based on the historic data from 1982–2020. Therefore, this study suggests that winter–spring Arctic sea ice outflow can be considered a predictor of changes in sea ice and other marine environmental conditions in the BGS in the subsequent months, at least until early summer. The results promote our understanding of the physical connection between the central Arctic Ocean and the BGS.

How to cite: Zhang, F., Lei, R., Zhai, M., Pang, X., and Li, N.: The impacts of anomalies in atmospheric circulations on Arctic sea ice outflow and sea ice conditions in the Barents and Greenland seas: case study in 2020, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3299, https://doi.org/10.5194/egusphere-egu24-3299, 2024.