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This study investigates the impact of sea ice and snow changes on surface air temperature (SAT) trends on the multidecadal time scale over the mid- and high-latitudes of Eurasia during boreal autumn, winter and spring based on a 30-member ensemble simulations of the Community Earth System Model (CESM). A dynamical adjustment method is used to remove the internal component of circulation-induced SAT trends. The leading mode of dynamically adjusted SAT trends is featured by same-sign anomalies extending from northern Europe to central Siberia and to the Russian Far East, respectively, during boreal spring and autumn, and confined to western Siberia during winter. The internally generated component of sea ice concentration trends over the Barents-Kara Seas contributes to the differences in the thermodynamic component of internal SAT trends across the ensemble over adjacent northern Siberia during all the three seasons. The sea ice effect is largest in autumn and smallest in winter. Eurasian snow changes contribute to the spread in dynamically adjusted SAT trends as well around the periphery of snow covered region by modulating surface heat flux changes. The snow effect is identified over northeast Europe-western Siberia in autumn, north of the Caspian Sea in winter, and over eastern Europe-northern Siberia in spring. The effects of sea ice and snow on the SAT trends are realized mainly by modulating upward shortwave and longwave radiation fluxes.

Pigmented microalgae inhabiting snow and ice environments lower the albedo of glacier and ice-sheet surfaces, significantly enhancing surface melt. Our ability to accurately predict their role in glacier and ice-sheet surface mass balance is limited by the current lack of empirical data to constrain their representation in predictive models. Here we present new empirical optical properties for snow and ice algae and incorporate them in a radiative transfer model to investigate their impact on snow and ice surface albedo. We found ice algal cells to be more efficient absorbers than snow algal cells, but their blooms had comparable impact on surface albedo due to the different photic conditions of their habitats. We then used the model to reconstruct the effect of ice algae on bare ice albedo spectra collected at our field site in southern Greenland, where blooms dropped the albedo locally by between 3 and 43%, equivalent to 1–10 L m$^{-2}$ d$^{-1}$ of melted ice. Using the newly parametrized model, future studies could investigate biological albedo reduction and algal quantification from remote hyperspectral and multispectral imagery.

Volcanic activity has been shown to affect Earth's climate in a myriad of ways. One such example is that eruptions proximate to surface ice will promote ice melting. In turn, the crustal unloading associated with melting an ice sheet affects the internal dynamics of the underlying magma plumbing system. Geochronologic data from the Andes over the last two glacial cycles suggest that glaciation and volcanism may interact via a positive feedback loop. At present, accurate sea‐level predictions hinge on our ability to forecast the stability of the West Antarctic Ice Sheet, and thus require consideration of two‐way subglacial volcano‐deglaciation processes. The West Antarctic Ice Sheet is particularly vulnerable to collapse, yet its position atop an active volcanic rift is seldom considered. Ice unloading deepens the zone of melting and alters the crustal stress field, impacting conditions for dike initiation, propagation, and arrest. However, the consequences for internal magma chamber dynamics and long‐term eruption behavior remain elusive. Given that unloading‐triggered volcanism in West Antarctica may contribute to the uncertainty of ice loss projections, we adapt a previously published thermomechanical magma chamber model and simulate a shrinking ice load through a prescribed lithostatic pressure decrease. We investigate the impacts of varying unloading scenarios on magma volatile partitioning and eruptive trajectory. Considering the removal of km‐thick ice sheets, we demonstrate that the rate of unloading influences the cumulative mass erupted and consequently the heat released into the ice. These findings provide fundamental insights into the complex volcano‐ice interactions in West Antarctica and other subglacial volcanic settings. Plain Language Summary In regions like West Antarctica, volcanic eruptions occur underneath ice sheets. When hot magma comes in contact with ice, it can accelerate the melting of the ice cover. Beyond this, as climate change causes ice sheets to shrink, the decreasing weight on a volcano may affect its likelihood of erupting. The effects of ice loss above volcanoes on the underlying volcanic activity are not well understood. We conducted computer simulations to explore how gradual ice loss affects magma stored in the Earth's crust. We find that volcanoes beneath shrinking ice sheets are sensitive to the rate at which the ice sheet shrinks. As the ice melts away, the reduced weight on the volcano allows the magma to expand, applying pressure upon the surrounding rock that may facilitate eruptions. Additionally, the reduced weight from the melting ice above also allows dissolved water and carbon dioxide to form gas bubbles, which causes pressure to build up in the magma chamber and may eventually trigger an eruption. Under these conditions, we find that the removal of an ice sheet above a volcano results in more abundant and larger eruptions, which may potentially hasten the melting of overlying ice through complex feedback mechanisms. Key Points During deglaciation, the evolution of a crustal magma chamber beneath kilometers of ice is sensitive to the rate at which ice is removed A critical rate of unloading can trigger additional eruption events Ice unloading expedites the onset of volatile exsolution, with consequences for magma chamber pressurization and eruption size

The frequency of extreme drought events in northeastern China (NEC) has increased since the 2000s, and such a decadal anomalous trend may lead to significant stress on agriculture and economic development. The correlation between Arctic sea ice loss in spring and extreme summer droughts over NEC was investigated. The results show that the loss of sea ice over the Barents Sea in spring is associated with extreme droughts and positive height anomalies over NEC in summer. The physical processes include two pathways. First, sea ice loss from the Barents Sea to the Kara Sea results in reducing baroclinicity over the ice loss region but increasing baroclinicity over the ice melting region, which is favorable to the wave ridge over northern Europe and negative-phase Summer North Atlantic Oscillation (SNAO). One wave train originates from negative-phase SNAO over North Atlantic–Europe and spreads to central Europe, central Asia, and NEC. Second, another wave motion flux originates from the Barents–Kara Sea propagating eastward, and then disperses southward to NEC. Both wave trains lead to anomalous anticyclonic circulation and westward subtropical high, which favors descending motion and less water vapor flux, thereby contributing to extreme drought.

The fast decline of Arctic sea ice necessitates a stronger focus on understanding the Arctic sea ice predictability and developing advanced forecast methods for all seasons and for pan-Arctic and regional scales. In this study, the operational forecasting system combining an advanced eddy-permitting ocean–sea ice ensemble reanalysis ORAS5 and state-of-the-art seasonal model-based forecasting system SEAS5 is used to investigate effects of sea ice dynamics and thermodynamics on seasonal (growth-to-melt) Arctic sea ice predictability in 1993–2020. We demonstrate that thermodynamics (growth/melt) dominates the seasonal evolution of mean sea ice thickness at pan-Arctic and regional scales. The thermodynamics also dominates the seasonal predictability of sea ice thickness at pan-Arctic scale; however, at regional scales, the predictability is dominated by dynamics (advection), although the contribution from ice growth/melt remains perceptible. We show competing influences of sea ice dynamics and thermodynamics on the temporal change of ice thickness predictability from 1993–2006 to 2007–20. Over these decades, there was increasing predictability due to growth/melt, attributed to increased winter ocean heat flux in both Eurasian and Amerasian basins, and decreasing predictability due to advection. Our results demonstrate an increasing impact of advection on seasonal sea ice predictability as the region of interest becomes smaller, implying that correct modeling of sea ice drift is crucial for developing reliable regional sea ice predictions. This study delivers important information about sea ice predictability in the “new Arctic” conditions. It increases awareness regarding sea ice state and implementation of sea ice forecasts for various scientific and practical needs that depend on accurate seasonal sea ice forecasts.

Seismology is increasingly used to infer the magnitude and direction of glacial ice flow. However, the effects of interstitial meltwater on seismic properties remain poorly constrained. Here, we extend previous studies on seismic anisotropy in temperate ices to consider the role of melt preferred orientation (MPO). We used the ELLE numerical toolbox to simulate microstructural shear deformation of temperate ice with variable MPO strength and orientation, and calculated the effective seismic properties of these numerical ice‐melt aggregates. Our models demonstrate that even 3.5% melt volume is sufficient to rotate fast directions by up to 90°, to increase Vp anisotropy by up to +110%, and to modify Vs anisotropy by −9 to +36%. These effects are especially prominent at strain rates ≥3.17 × 10−12 s−1. MPO may thus obscure the geophysical signatures of temperate ice flow in regions of rapid ice discharge, and is therefore pivotal for understanding ice mass loss. Plain Language Summary Ice on Earth is pulled toward the sea by gravity, contributing to global mean sea level rise. To better understand the flow, or movement, of ice at the continent scale, geophysical surveys are increasingly being used to measure the microscopic alignment (“fabric”) of ice crystals, since ice with a strong fabric flows more readily. However, in temperate regions close to the ice melting point, melt pockets may also become aligned, creating additional macroscopic geophysical signatures. Here, we use numerical simulations to examine the combined effects of ice crystal fabric and melt alignment on the geophysical (seismic) properties of ice containing small amounts of melt. We show that melt can change the seismic fast direction (related to the inferred flow direction) of ice by up to 90°, particularly as the volume of melt exceeds 3.5%, and that different melt orientations can either enhance or diminish the anisotropy‐based estimates of flow that some studies use to predict ice mass loss. These effects are especially prominent in faster‐flowing ice, highly relevant to ice mass loss in warming regions. Geophysical studies that do not account for melt orientation may therefore produce incorrect estimates of flow, leading to inaccuracies in future climate models. Key Points We used simulations of deforming temperate ice to show that the alignment of interstitial meltwater changes bulk seismic properties The amount of melt required to significantly modify seismic properties is at least 50% lower than previously reported Melt should be considered when using seismic and radar anisotropy to interpret viscous ice deformation and enhancement

Sea ice, one of the most dominant barriers to Arctic shipping, has decreased dramatically over the past four decades. Arctic maritime transport is hereupon growing in recent years. To produce a long-term assessment of trans-Arctic accessibility, we systematically revisit the daily Arctic navigability with a view to the combined effects of sea ice thickness and concentration throughout the period 1979–2020. The general trends of Navigable Windows (NW) in the Northeast Passage show that the number of navigable days is steadily growing and reached 89±16 days for Open Water (OW) ships and 163±19 days for Polar Class 6 (PC6) ships in the 2010s, despite high interannual and interdecadal variability in the NWs. More consecutive NWs have emerged annually for both OW ships and PC6 ships since 2005 because of the faster sea ice retreat. Since the 1980s, the number of simulated Arctic routes has continuously increased, and optimal navigability exists in these years of record-low sea ice extent (e.g., 2012 and 2020). Summertime navigability in the East Siberian and Laptev Seas, on the other hand, varies dramatically due to changing sea ice conditions. This systematic assessment of Arctic navigability provides a reference for better projecting the future trans-Arctic shipping routes.

The Arctic is warming at a faster rate compared to the globe on average, a phenomenon commonly referred to as Arctic amplification. Sea ice has been linked to Arctic amplification and has gathered attention recently due to the decline in summer sea ice extent. Data assimilation (DA) is the act of combining observations with prior forecasts to obtain a more accurate model state. Sea ice poses a unique challenge for DA because sea ice variables have bounded distributions, leading to non-Gaussian distributions. The non-Gaussian nature violates the Gaussian assumptions built into DA algorithms. This study presents different observing system simulation experiments (OSSEs), which will provide a data assimilating testing framework through experimental observation networks and synthetic observations. The OSSE framework will help determine the best data assimilation configuration for assimilating sea ice and snow observations. Findings indicate that assimilating both sea ice thickness and snow depth observations while omitting sea ice concentration observations produced the best sea ice and snow forecasts in our idealized experimental setup. A simplified DA experiment helped demonstrate that the DA solution is biased when assimilating sea ice concentration observations. The biased DA solution is related to the observation error distribution being a truncated normal distribution, and the assumed observation likelihood is normal for the DA method. Additional OSSEs show that using a non-Gaussian DA method does not alleviate the non-Gaussian effects of sea ice concentration observations, and assimilating sea ice surface temperatures has a positive impact on snow updates. Finally, it is shown that the perturbed sea ice model parameters used to create additional ensemble spread in the free forecasts lead to a year-long negative snow volume bias.

Arctic surface warming under greenhouse gas forcing peaks in winter and reaches its minimum during summer in both observations and model projections. Many mechanisms have been proposed to explain this seasonal asymmetry, but disentangling these processes remains a challenge in the interpretation of general circulation model (GCM) experiments. To isolate these mechanisms, we use an idealized single-column sea ice model (SCM) that captures the seasonal pattern of Arctic warming. SCM experiments demonstrate that as sea ice melts and exposes open ocean, the accompanying increase in effective surface heat capacity alone can produce the observed pattern of peak warming in early winter (shifting to late winter under increased forcing) by slowing the seasonal heating rate, thus delaying the phase and reducing the amplitude of the seasonal cycle of surface temperature. To investigate warming seasonality in more complex models, we perform GCM experiments that individually isolate sea ice albedo and thermodynamic effects under CO₂ forcing. These also show a key role for the effective heat capacity of sea ice in promoting seasonal asymmetry through suppressing summer warming, in addition to precluding summer climatological inversions and a positive summer lapse-rate feedback. Peak winter warming in GCM experiments is further supported by a positive winter lapse-rate feedback, due to cold initial surface temperatures and strong surface-trapped warming that are enabled by the albedo effects of sea ice alone. While many factors contribute to the seasonal pattern of Arctic warming, these results highlight changes in effective surface heat capacity as a central mechanism supporting this seasonality.

Ice shelf dynamics and morphology play an important role in the stability of floating bodies of ice by driving fracturing that can lead to calving, in turn impacting the ability of the ice shelf to buttress upstream grounded ice. Following a 2016 calving event at the Nansen Ice Shelf (NIS), East Antarctica, we collected airborne and ground-based radar data to map ice thickness across the shelf. We combine these data with published satellite-derived data to examine the spatial variations in ice shelf draft, the cause and effects of ice shelf strain rates, and the possibility that a suture zone may be channelizing ocean water and altering patterns of sub-ice-shelf melt and freeze-on. We also use our datasets to assess limitations that may arise from relying on hydrostatic-balance equations applied to ice surface elevation to determine ice draft morphology. We find that the Nansen Ice Shelf has a highly variable basal morphology driven primarily by the formation of basal fractures near the onset of the ice shelf suture zone. This morphology is reflected in the ice shelf strain rates but not in the calculated hydrostatic-balance thickness, which underestimates the scale of variability at the ice shelf base. Enhanced melt rates near the ice shelf terminus and in steep regions of the channelized suture zone, along with relatively thin ice in the suture zone, appear to represent vulnerable areas in the NIS. This morphology, combined with ice dynamics, induce strain that has led to the formation of transverse fractures within the suture zone, resulting in large-scale calving events. Similar transverse fractures at other Antarctic ice shelves may also be driven by highly variable morphology, and predicting their formation and evolution could aid projections of ice shelf stability.