Arctic sea ice mediates atmosphere-ocean momentum transfer, which drives upper ocean circulation. How Arctic Ocean surface stress and velocity respond to sea ice decline and changing winds under global warming is unclear. Here we show that state-of-the-art climate models consistently predict an increase in future (2015-2100) ocean surface stress in response to increased surface wind speed, declining sea ice area, and a weaker ice pack. While wind speeds increase most during fall (+2.2% per decade), surface stress rises most in winter (+5.1%  per decade) being amplified by reduced internal ice stress. This is because, as sea ice concentration decreases in a warming climate, less energy is dissipated by the weaker ice pack, resulting in more momentum transfer to the ocean. The increased momentum transfer accelerates Arctic Ocean surface velocity (+31-47% by 2100), leading to elevated ocean kinetic energy and enhanced vertical mixing. The enhanced surface stress also increases the Beaufort Gyre Ekman convergence and freshwater content, impacting Arctic marine ecosystems and the downstream ocean circulation. The impacts of projected changes are profound, but different and simplified model formulations of atmosphere-ice-ocean momentum transfer introduce considerable uncertainty, highlighting the need for improved coupling in climate models.

How to cite: Muilwijk, M., Hattermann, T., Martin, T., and Granskog, M.: Future sea ice weakening amplifies wind-driven trends in surface stress and Arctic Ocean spin-up, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11156, https://doi.org/10.5194/egusphere-egu25-11156, 2025.

Since the beginning of the satellite era in 1979, September sea ice area over the Arctic has nearly halved, and the rapid sea ice decline in the early 2000s fueled concerns that the first ice-free Arctic summer could occur before 2020.  In light of these dire forecasts, therefore, it is remarkable that no statistically significant decline in September Arctic sea ice coverage has occurred over past two decades, as we demonstrate here.

This 20-year-long hiatus in pan-Arctic sea ice decline is robust across observational datasets, and also robust to the choice metric (sea ice area or extent).  In fact, the present hiatus is seen in all months of the year, not only in September.

One is immediately led to ask whether climate models are able to capture multi-decadal-long periods with no Arctic sea ice decline in the presence of strong anthropogenic radiative forcing.  To answer this, we analyze multiple large ensembles of CMIP5 and CMIP6 simulations over the first half of the 21st century.  We find that 20-year-long periods with no significant Arctic in sea ice loss occur rather frequently in climate models, even under high emissions scenarios.  Roughly 20-30% of the hundreds of model runs analyzed here show 2005-2024 trends smaller than the small observed trend, although the intermodel spread is considerable.  Sub-selecting models based on their ability of simulating observed climatological sea ice, or on their equilibrium climate sensitivity, or on the specific scenario forcings, does not alter the key result.

Our analysis also reveals that the simulated forced response, in most models, is considerably larger than the observed trends.  This highlights the important role of internal variability in enhancing and, more recently, in reducing Arctic sea ice decline.  In fact, our analysis of model output reveals that a different configuration of internal climate variability could have caused an overall growth in Arctic sea ice over the past 20 years, surprisingly enough.

Looking at the coming decades, and focusing on those climate simulation which are consistent with the present observed trends, we find the hiatus is 50% likely to persist for another five years, and could plausibly last another full decade (with roughly 30% chance).

Taken together, our findings lead us to conclude that the current hiatus in Arctic sea ice decline, even as emissions of greenhouse gases continue to rise, is not an unexpected event that questions our basic understanding of the Arctic climate system.  Climate models show that it can occur rather frequently, and that it could plausibly persist for years to come.

How to cite: Polvani, L., England, M., and Screen, J.: A surprising, but not unexpected, multi-decadal hiatus in Arctic sea ice decline, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7248, https://doi.org/10.5194/egusphere-egu25-7248, 2025.

Most climate models do not reproduce the 1979–2014 increase in Antarctic sea ice area (SIA). This was a contributing factor in successive Intergovernmental Panel on Climate Change reports allocating low confidence to model projections of sea ice over the 21st century. However, due to the rapid declines in Antarctic sea ice since 2016, the linear trend in annual mean Antarctic SIA is no longer positive. We therefore investigate what impact this has on the evaluation of trends from the CMIP6 multi-model ensemble and show that the recent rapid declines bring observed SIA trends back into line with the models. More generally, the level of agreement between observed and modelled linear trends depends both on the length of the time series examined ('timescale') and the exact years ('time period').  Our novel result that trends over the full satellite era 1979–2023 do not disagree between observations and models could imply that models are better able to represent changes over longer timescales than previously thought. However, this is not the only interpretation. One confounding aspect is the abrupt nature of recent change, as a result of which the full time series does not appear particularly linear. This presentation will discuss these aspects and the implications for future research priorities.

How to cite: Holmes, C., Bracegirdle, T. J., Holland, P. R., Stroeve, J., and Wilkinson, J.: New perspectives on the skill of modelled sea ice trends in light of recent Antarctic sea ice loss, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8393, https://doi.org/10.5194/egusphere-egu25-8393, 2025.

ABSTRACT:

In 2023, Antarctic sea-ice extent (SIE) reached record lows, with winter SIE falling to 2.5Mkm² below the satellite era average. With this multi-model study, we investigate the occurrence of anomalies of this magnitude in latest-generation global climate models. When these anomalies occur, SIE takes decades to recover: this indicates that SIE may transition to a new, lower, state over the next few decades. Under internal variability alone, models are extremely unlikely to simulate these anomalies, with return period >1000 years for most models. The only models with return period <1000 years for these anomalies have likely unrealistically large interannual variability. Based on extreme value theory, the return period is reduced from 2650 years under internal variability to 580 years under a strong climate change forcing scenario.

REFERENCE:

Diamond, Rachel, et al. "CMIP6 models rarely simulate Antarctic winter sea‐ice anomalies as large as observed in 2023." Geophysical Research Letters 51.10 (2024): e2024GL109265.

PLAIN LANGUAGE SUMMARY:

In 2023, the area of winter Antarctic sea ice fell to the lowest measured since satellite records began in late 1978. It is still under debate how far this low can be explained by natural variations, and how much can be explained by climate change. Global climate models are tools used to study past and predict future global change. We show that, without climate change, the latest generation of these models are extremely unlikely to simulate a sea-ice reduction from the mean as large as observed in winter 2023. Including strong climate change quadruples the chance of such a reduction, but the chance is still very low. When these rare reductions are simulated, sea ice takes around 10 years to recover to a new, lower, area: this indicates that Antarctic sea ice may transition to a new, lower, state over the next few decades.

How to cite: Diamond, R., Sime, L., Holmes, C., and Schroeder, D.: CMIP6 Models Rarely Simulate Antarctic Winter Sea-Ice Anomalies as Large as Observed in 2023, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11201, https://doi.org/10.5194/egusphere-egu25-11201, 2025.

The Marginal Ice Zone (MIZ) is a dynamic region between open water
and consolidated ice, crucial for heat and moisture exchange and support-
ing diverse marine ecosystems. With Arctic sea ice thinning and the melt
season lengthening, monitoring the MIZ has become increasingly impor-
tant. This study analyzed Arctic MIZ trends over 40 years (1983–2022)
using Bootstrap SIC data and two definitions: one based on the SIC
threshold (MIZ_t) and another on the SIC anomaly (MIZ_σ ). MIZt was de-
fined as 0.15 0.15 ≤ SIC < 0.80, while MIZσ used grid cells with a median
standard deviation of SIC anomaly above 0.11, derived from the probabil-
ity density function. This research represents a novel exploration of the
Arctic MIZ using a SIC anomaly-based approach. Both definitions showed
similar seasonal trends, but MIZ_σ peaked during freeze-up (October) and
break-up (July), while MIZ_t peaked in summer (August). MIZ_σ fractions
were consistently higher than those from MIZ_t across all seasons. Finally,
October and August exhibit the most rapid increases in both MIZ_t and
MIZ_σ fractions, coinciding with accelerated sea ice decline. These results
highlight the importance of selecting an MIZ definition tailored to specific
research or applications.

How to cite: Soleymani, A., Crawford, A., and Scott, K. A.: Interannual Variability of the Arctic Marginal Ice Zone Over Four Decades: A Comparison of Two Definitions, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7366, https://doi.org/10.5194/egusphere-egu25-7366, 2025.

Understanding the evolution of Arctic sea-ice is crucial due to its socio-economic impacts. Usual descriptors (e.g., sea-ice extent, sea-ice age and ice-free duration) quantify changes but do not account for the full seasonal cycle. Here, using satellite observations of sea-ice concentration (1979-2023), we perform a k-means clustering of the Arctic sea-ice seasonal cycle, initializing with equal quantile separation and using Mahalanobis distance. We identify four optimal seasonal cycle clusters: ocean-only (no ice year-round), permanent sea-ice (full coverage with a minimum of 0.7 sea-ice concentration), and two clusters showing ice-free conditions, namely partial and full winter freezing. The latter has larger sea-ice concentration in winter, more abrupt melting and freezing, and shorter ice-free season than the former. Hence, the starting dates for melting are good precursors of ice-free duration. The probability of belonging to the open-ocean cluster increased by 1.6% per decade mostly due to cluster spatial expansion in the Atlantic side. The permanent sea-ice decreased by 1.5% per decade with a likelihood reduction in the Pacific side. The last two clusters do not exhibit any trend but spatial shifts occur. We further diagnose cluster transitions and subsequently infer regions of stabilization and destabilization. The East Siberian and Laptev Seas are destabilized (losing their typical permanent sea-ice seasonal cycle) while the Kara and Chukchi Seas have stabilized (experiencing a new typical seasonal cycle, the partial winter-freezing cluster). This work provides a new way to describe Arctic regional changes using a statistical framework based on physical behaviours of sea-ice.

How to cite: Simon, A., Tandeo, P., Sévellec, F., and Lique, C.: Arctic regional changes revealed by clustering of sea-ice observations, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4117, https://doi.org/10.5194/egusphere-egu25-4117, 2025.

Floe size distribution (FSD) is a parameter that describes the geometric features of discrete sea ice floes. It plays a crucial role in the momentum, energy and mass exchanges between atmosphere and ocean over the frozen waters, through regulating the ice field consolidation and lead distribution. Previous studies on characterizing the Arctic FSD mainly focused on the marginal ice zone (MIZ) in the peripheral waters. However, continuous ice thinning and enhanced response of ice motion to wind forcing lead to more intense sea ice fragmentation in the Arctic pack ice zone (PIZ). This, in turn, further strengthens sea ice mobility and contributes to the Arctic sea ice outflow. Therefore, this study focuses on the FSD at the northern entrance of the Nares Strait, a region characterized by severe ice conditions and high ice dynamics, which is essential for the outflow of Arctic multi-year ice. We firstly developed a parameter-free method based on a deep convolutional neural network and graph partitioning algorithm to retrieve floes geometry in this specific region from Sentinel-1 synthetic aperture radar images. Using manual produced ground truth data as the benchmark, the proposed method outperformed four conventional algorithms, including K-means, dynamic local thresholding, watershed, and kernel graph cut, in visual assessment and quantitative evaluation. It achieved an overall accuracy and F1-score of 97.0% and 97.6%, respectively. Subsequently, the method was applied to obtain the FSD at the northern entrance of the Nares Strait in 2019. Result showed that the FSD exhibited a power-law distribution for floes with mean caliper diameter ranging from approximately 3 to 53 km for most time. Exceptions occurred in early autumn at the onset of ice freezing, where invalid power law exponent α emerged due to the finite image size and/or abnormal ice advection. We further found that the variations of α were primarily regulated by sea ice thickness, ice advection, and events of floe breakup and welding. Compared with that identified in the Arctic MIZ, seasonal change in FSD in this region appeared relatively moderate, owing to high sea ice concentration and different regulating mechanisms.This work provides a practical algorithm for floe geometry retrieval and a rare case study on the seasonal change in FSD in the Arctic PIZ.

How to cite: Yang, F., Liu, T., and Lei, R.: Seasonal change in floe size distribution at the northern entrance of the Arctic Nares Strait derived from Sentinel-1 images: retrieval method and case study in 2019, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1736, https://doi.org/10.5194/egusphere-egu25-1736, 2025.

How to cite: Rhee, D., Wells, A., and Hewitt, I.: Hydrodynamic interactions significantly effect frazil ice crystal collisions in the ocean, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16126, https://doi.org/10.5194/egusphere-egu25-16126, 2025.

The Arctic, a central place to our global climate, is mainly covered by sea ice. The motion of sea ice is important as it exports freshwater from the central Arctic to the North Atlantic. The motion itself is on a large scale driven by atmospheric and oceanic patterns. Yet, fluctuating velocities are superimposed on this mean circulation. These fluctuating velocities represent atmospheric and oceanic turbulence as well as internal sea ice dynamics. One main property of the sea-ice fluctuating velocity is its high intermittency induced by the fracturing of sea ice. To understand the dynamical properties of the fluctuating velocities, we study the kinematic energy using Lagrangian statistics derived from observed trajectories, inspired by classical multi-scale analysis from fluid turbulence. We use trajectories from the International Arctic Buoy Program (IABP), covering a 40-years period of the sea-ice covered central Arctic, both in summer and winter seasons. The energy spectra is found to follow the Kolmogorov -5/3 scaling, which is classically observed for fluid turbulence. The cross-correlated acceleration-velocity structure function (Sau) provides information on the energy cascade between spatial scales. While noisy, the computed Sau is negative in the 10-1000 km scales, which would imply a direct energy cascade (from large to small scales). The imprint of the atmospheric and oceanic turbulence must present a direct energy cascade. However, as the characteristics of the sea-ice fluctuating velocity fields are also impacted by the sea ice internal physics, such a negative cascade could result from the energy transfer from large-scale forcing fields down to the smallest fractures in the sea ice. While the statistics of the sea-ice turbulence are similar over the whole 40-years period, differences are found between the old and modern data. These changes point towards a transition of dynamical regime that the Arctic sea ice is undergoing.

How to cite: Caneill, R., Rampal, P., and Bourgoin, M.: Sea-ice turbulent dynamics derived from Lagrangian buoys tracks, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6431, https://doi.org/10.5194/egusphere-egu25-6431, 2025.

How to cite: Martin, J., Dadic, R., Anderson, B., Pirazzini, R., Vargo, L., and Wigmore, O.: How Flat is Flat? Investigating the Spatial Variability of Snow Surface Temperature and Topography on Landfast Sea Ice Using Drone-Based Mapping , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4593, https://doi.org/10.5194/egusphere-egu25-4593, 2025.