Identifying the full suite of processes that drive the melting of Antarctic sea ice each summer is crucial to improving the currently-poor ability of contemporary models to accurately simulate the climatological retreat phase of the annual sea-ice cycle. This is critical to (1) understanding and attributing observed trends and recent abrupt changes in sea-ice coverage and (2) the more robust prediction of future sea-ice conditions and impacts. This paper identifies wave-driven processes that can accelerate the seasonal melting of sea ice both in the marginal ice zone (MIZ) and in open-water areas within the interior sea-ice zone (SIZ). It builds on the long-held view that seasonal Antarctic sea-ice ablation is primarily driven by ice-floe lateral and basal melting enhanced in the MIZ by wave breakup of ice floes, by demonstrating that ocean waves play important additional roles in generating surface and interior melting (termed “wave melting”) via three sets of processes: “wave flooding”, “wave pulverisation”, and “wave greening” (involving algal proliferation in wave-modified ice). Based on existing observations and simple one-dimensional modelling, these wave processes are estimated to reduce ice albedo by 0.38–0.64 compared to snow-covered ice, resulting in vertical melt-rate enhancements of 0.9–5.2 cm d−1 amplified by wave greening to 1.1–6.1 cm d−1. The study also identifies five positive feedback and sub-feedback mechanisms that likely accelerate the ice melting further. It addresses a gap in current climate and Earth system models, which account for wave effects on floe-size distributions but overlook these coupled wave-driven dynamic, thermodynamic and biological processes that may contribute to explaining why and how Antarctic sea ice can melt back so rapidly each summer. An intention of this foundational study is to stimulate further targeted investigation aimed at quantifying the role of wave melting in the annual sea-ice cycle – as well as the contribution of wave greening to primary production in the sea-ice zone and its role in key biogeochemical processes that feed back to climate. The work has implications for planetary albedo, global climate feedbacks, marine ecosystems, and the accuracy of future sea-ice and climate projections in an increasingly-stormy Southern Ocean, as well as in a changing Arctic.

Abstract Solar radiation is the key energy input to the ocean. In the Arctic Ocean and its peripheral seas, the distribution of solar radiation is strongly modulated by the presence of sea ice. In this study, we combined satellite and model products to investigate solar radiation partitioning between reflection to the atmosphere, absorption in the ice, and transmission to the ocean over 1984–2024. We present total annual solar heat partitioning, relative contributions to energy deposition from ice and open water, and trends in large‐scale partitioning. The Arctic exhibited a decreasing trend in albedo (0.019 decade−1) due to decreasing sea ice areal coverage and thickness. Consequently, solar transmittance into the ocean increased by 0.031 decade−1, resulting in an additional ∼300 MJ m−2 of heat input over 1984–2024. A brighter, warmer ocean contributes to Arctic Amplification and may alter the functioning of the Arctic marine ecosystem.

Delayed sea ice freeze-up and decreased sea ice extent in the Pacific Arctic region have altered light availability in marine waters, extending the ice-free season and increasing opportunities for photosynthetic activity and energy exchanges. This study investigates phytoplankton bloom progression during the fall using chlorophyll pigments and examines the impact phytoplankton have on heat distribution within the water column. Measurements of chlorophyll-a concentrations and its associated degradation product pheophytin were made in conjunction with optical measurements of light transmittance within the upper water column during the Synoptic Arctic Survey cruise in the Central Arctic Ocean and northeast Chukchi Sea in September-October 2022. Pheophytin proportions relative to chlorophyll-a generally increased over the course of the 2-month cruise, indicating an overall seasonal decline in biological production. However, renewed phytoplankton growth indicated by reduced pheophytin proportions was observed within the surface similar to 20 m of the water column on the Chukchi Shelf in late October. These subsurface blooms absorbed incoming solar radiation and enhanced ocean heating in the surface waters associated with the bloom while shading deeper depths from heating. Log-linear regressions of heating rates associated each 1 mu g L-1 increase of chlorophyll-a (at the observed chlorophyll-a maximum) with an approximate 15% decrease in heat input within the 10 m below the chlorophyll-a maximum depth. The altered vertical heat distribution caused by fall blooms trapping heat at the bloom depth can influence upper ocean stratification.

“Rotten” sea ice, ice in an advanced stage of melt, represents an important but understudied habitat in the rapidly changing Arctic. As Arctic warming accelerates, this late-season ice type will become more prevalent, yet little is known about its microbial inhabitants or their roles in Arctic marine biogeochemical cycles. We examined microbial communities (prokaryote and algal abundance, 16S and 18S rRNA gene and transcript sequencing) and biogeochemical properties of rotten sea ice and earlier-season ice near Utqiaġvik, Alaska, USA. Rotten ice was comparatively warm, isothermal, and largely drained of brine, with extensive, interconnected pore networks linked to melt ponds above and seawater below. Unlike earlier-season ice, fluids saturating rotten ice were vertically homogeneous in pH, dissolved inorganic carbon, prokaryote and phytoplankton abundance, and microbial community composition. However, particulate carbon and nitrogen exhibited strong vertical gradients, with the highest concentrations near the surface. Microbial communities in rotten ice were significantly different from those in earlier-season ice and varied between individual floes. These findings indicate that rotten ice constitutes a distinct microbial habitat and may serve as an important source of nutrient-rich particulate matter in the future Arctic Ocean during the summer melt season.

Light transmission through a sea ice cover has strong implications for the heat content of the upper ocean, the magnitude of bottom and lateral ice melt, and primary productivity in the ocean. Light transmittance in the vicinity of the Multidisciplinary Drifting Observatory for the Study of Arctic Climate (MOSAiC) Central Observatory was estimated by driving a two-stream radiative transfer model with physical property observations. Data include point and transect observations of snow depth, surface scattering layer thickness, ice thickness, and pond depth. The temporal evolution of light transmittance at specific sites and the spatial variability along transect lines were computed. Ponds transmitted 4–6 times as much solar energy per unit area as bare ice. On July 25, ponds covered about 18% of the area and contributed roughly 50% of the sunlight transmitted through the ice cover. Approximating the transmittance along a transect line using average values for the physical properties will always result in lower light transmittance than finding the average light transmittance using the full distribution of points. Transmitted solar energy calculated using the standard five ice thickness categories and three surface types used in the Los Alamos sea ice model CICE, the sea ice component of many weather and climate models, was only about 1 W m−2 less than using all the points along the transect. This minor difference suggests that the important processes and resulting feedbacks relating to solar transmittance can be represented in models that use five or more categories of ice thickness distributions.

Sea ice modulates the transfer of shortwave radiative energy fluxes within the Arctic atmosphere-sea-ice-ocean system. Understanding and predicting these fluxes comes with greatest uncertainties during the melt and freeze-up seasons, when the sea ice surface is strongly heterogeneous and changing rapidly. Then, the partitioning of solar radiative fluxes between atmosphere, ice, and ocean has greatest impacts on the surface energy budget, controlling sea ice melt and formation. Here, we investigated changes and impacts of sea ice surface variability by analyzing high-resolution red-green-blue aerial imagery obtained during the Multidisciplinary Observatory for the Study of Arctic Climate (MOSAiC) expedition in 2020. We used pixel brightness from processed aerial images as a proxy of surface albedo, because such data are frequently available and obtainable from commercial digital cameras. The results allowed quantification of fluxes on floe-scales and also revealed the seasonality of sea ice spatial heterogeneity, which was strongest in the middle of melt season driven by melt pond processes. On scales of 10 m x 10 m, a magnitude larger than the traditional single in-situ optical observations (although many are made over larger scales), distinct surface conditions, for example, individual melt ponds, resulted in differences of energy deposition into the ice by more than 600%. The effects of spatial variability were minimized by integrating over areas 200 m x 200 m and larger. We suggest considering these scales for future energy budget studies and airborne observations, because sufficient parts of different surface features are included. The concept of surface brightness and aerial photographs might help to bridge in-situ observations to even larger scales, including fractions of open water. It may also be used to upscale observations of under-ice light regimes by providing spatially continuous surface brightness that governs the light transmittance, thus to improve our understanding of the coupled system, including ecological functions.

AbstractAs Arctic sea ice and its overlying snow cover thin, more light penetrates into the ice and upper ocean, shifting the phenology of algal growth within the bottom of sea ice, with cascading impacts on higher trophic levels of the Arctic marine ecosystem. While field data or autonomous observatories provide direct measurements of the coupled sea ice‐algal system, they are limited in space and time. Satellite observations of key sea ice variables that control the amount of light penetrating through sea ice offer the possibility to map the under‐ice light field across the entire Arctic basin. This study provides the first satellite‐based estimates of potential sea ice‐associated algal bloom onset dates since the launch of CryoSat‐2 and explores how a changing snowpack may have shifted bloom onset timings over the last four decades.

The microstructure of the uppermost portions of a melting Arctic sea ice cover has a disproportionately large influence on how incident sunlight is reflected and absorbed in the ice/ocean system. The surface scattering layer (SSL) effectively backscatters solar radiation and keeps the surface albedo of melting ice relatively high compared to ice with the SSL manually removed. Measurements of albedo provide information on how incoming shortwave radiation is partitioned by the SSL and have been pivotal to improving climate model parameterizations. However, the relationship between the physical and optical properties of the SSL is still poorly constrained. Until now, radiative transfer models have been the only way to infer the microstructure of the SSL. During the MOSAiC expedition of 2019–2020, we took samples and, for the first time, directly measured the microstructure of the SSL on bare sea ice using X-ray micro-computed tomography. We show that the SSL has a highly anisotropic, coarse, and porous structure, with a small optical diameter and density at the surface, increasing with depth. As the melting surface ablates, the SSL regenerates, maintaining some aspects of its microstructure throughout the melt season. We used the microstructure measurements with a radiative transfer model to improve our understanding of the relationship between physical properties and optical properties at 850 nm wavelength. When the microstructure is used as model input, we see a 10–15% overestimation of the reflectance at 850 nm. This comparison suggests that either a) spatial variability at the meter scale is important for the two in situ optical measurements and therefore a larger sample size is needed to represent the microstructure or b) future work should investigate either i) using a ray-tracing approach instead of explicitly solving the radiative transfer equation or ii) using a more appropriate radiative transfer model.

The “surface scattering layer” (SSL) is the highly‐scattering, coarse‐grained ice layer that forms on the surface of melting, drained sea ice during spring and summer. Ice of sufficient thickness with an SSL has an observed persistent broadband albedo of ∼0.65, resulting in a strong influence on the regional solar partitioning. Experiments during the Multidisciplinary drifting Observatory for the Study of the Arctic Climate expedition showed that the SSL re‐forms in approximately 1 day following manual removal. Coincident spectral albedo measurements provide insight into the SSL evolution, where albedo increased on sunny days with higher solar insolation. Comparison with experiments in radiative transfer and global climate models show that the sea ice albedo is greatly impacted by the SSL thickness. The presence of SSL is a significant component of the ice‐albedo feedback, with an albedo impact of the same order as melt ponds. Changes in SSL and implications for Arctic sea ice within a warming climate are uncertain.

Novel observations of the seasonal evolution of an ice algal bloom on the Chukchi shelf were collected by two autonomous buoys deployed 180 km apart in first-year drifting sea ice. High attenuation of blue light in the bottom of the ice indicated considerable accumulation of ice algae biomass with derived Chlorophyll-a concentrations (Chl a) up to 184 mg m(-2). Differences in the magnitude and persistence of ice algae biomass under each buoy appear to have been driven by differences in snow thickness, as ice thickness was similar between the sites. Minimal snow cover (0.02 m) around one buoy was associated with algae growth beginning in mid-May and lasting 70 days. The second buoy had notably more snow (0.4 m), causing ice algae production to lag behind the first site by approximately 4 weeks. The delay in growth diminished the peak of ice algae Chl a and duration compared to the first site. Light attenuation through the ice was intense enough at both buoys to have a potentially inhibiting impact on water column phytoplankton Chl a. Modeling ice algae growth with observed light intensities determined that nutrients were the limiting resource at the low snow site. In contrast, the algae at the high snow site were light-limited and never nutrient-limited. These data point toward changes in ice algae phenology with an earlier and longer window for growth; and nutrients rather than light determining the longevity and magnitude of production.

During the Arctic melt season, relatively fresh meltwater layers can accumulate under sea ice as a result of snow and ice melt, far from terrestrial freshwater inputs. Such under-ice meltwater layers, sometimes referred to as under-ice melt ponds, have been suggested to play a role in the summer sea ice mass balance both by isolating the sea ice from saltier water below, and by driving formation of ‘false bottoms’ below the sea ice. Such layers form at the interface of the fresher under-ice layer and the colder, saltier seawater below. During the Multidisciplinary drifting Observatory for the Study of the Arctic Climate (MOSAiC) expedition in the Central Arctic, we observed the presence of under-ice meltwater layers and false bottoms throughout July 2020 at primarily first-year ice locations. Here, we examine the distribution, prevalence, and drivers of under-ice ponds and the resulting false bottoms during this period. The average thickness of observed false bottoms and freshwater equivalent of under-ice meltwater layers was 0.08 m, with false bottom ice comprised of 74–87% FYI melt and 13–26% snow melt. Additionally, we explore these results using a 1D model to understand the role of dynamic influences on decoupling the ice from the seawater below. The model comparison suggests that the ice-ocean friction velocity was likely exceptionally low, with implications for air-ice-ocean momentum transfer. Overall, the prevalence of false bottoms was similar to or higher than noted during other observational campaigns, indicating that these features may in fact be common in the Arctic during the melt season. These results have implications for the broader ice-ocean system, as under-ice meltwater layers and false bottoms provide a source of ice growth during the melt season, potentially reduce fluxes between the ice and the ocean, isolate sea ice primary producers from pelagic nutrient sources, and may alter light transmission to the ocean below.

Melt ponds on sea ice play an important role in the Arctic climate system. Their presence alters the partitioning of solar radiation: decreasing reflection, increasing absorption and transmission to the ice and ocean, and enhancing melt. The spatiotemporal properties of melt ponds thus modify ice albedo feedbacks and the mass balance of Arctic sea ice. The Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition presented a valuable opportunity to investigate the seasonal evolution of melt ponds through a rich array of atmosphere-ice-ocean measurements across spatial and temporal scales. In this study, we characterize the seasonal behavior and variability in the snow, surface scattering layer, and melt ponds from spring melt to autumn freeze-up using in situ surveys and auxiliary observations. We compare the results to satellite retrievals and output from two models: the Community Earth System Model (CESM2) and the Marginal Ice Zone Modeling and Assimilation System (MIZMAS). During the melt season, the maximum pond coverage and depth were 21% and 22 +/- 13 cm, respectively, with distribution and depth corresponding to surface roughness and ice thickness. Compared to observations, both models overestimate melt pond coverage in summer, with maximum values of approximately 41% (MIZMAS) and 51% (CESM2). This overestimation has important implications for accurately simulating albedo feedbacks. During the observed freeze-up, weather events, including rain on snow, caused high-frequency variability in snow depth, while pond coverage and depth remained relatively constant until continuous freezing ensued. Both models accurately simulate the abrupt cessation of melt ponds during freeze-up, but the dates of freeze-up differ. MIZMAS accurately simulates the observed date of freeze-up, while CESM2 simulates freeze-up oneto-two weeks earlier. This work demonstrates areas that warrant future observation-model synthesis for improving the representation of sea-ice processes and properties, which can aid accurate simulations of albedo feedbacks in a warming climate.

Melt ponds on sea ice play an important role in the Arctic climate system. Their presence alters the partitioning of solar radiation: decreasing reflection, increasing absorption and transmission to the ice and ocean, and enhancing melt. The spatiotemporal properties of melt ponds thus modify ice albedo feedbacks and the mass balance of Arctic sea ice. The Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition presented a valuable opportunity to investigate the seasonal evolution of melt ponds through a rich array of atmosphere-ice-ocean measurements across spatial and temporal scales. In this study, we characterize the seasonal behavior and variability in the snow, surface scattering layer, and melt ponds from spring melt to autumn freeze-up using in situ surveys and auxiliary observations. We compare the results to satellite retrievals and output from two models: the Community Earth System Model (CESM2) and the Marginal Ice Zone Modeling and Assimilation System (MIZMAS). During the melt season, the maximum pond coverage and depth were 21% and 22 ± 13 cm, respectively, with distribution and depth corresponding to surface roughness and ice thickness. Compared to observations, both models overestimate melt pond coverage in summer, with maximum values of approximately 41% (MIZMAS) and 51% (CESM2). This overestimation has important implications for accurately simulating albedo feedbacks. During the observed freeze-up, weather events, including rain on snow, caused high-frequency variability in snow depth, while pond coverage and depth remained relatively constant until continuous freezing ensued. Both models accurately simulate the abrupt cessation of melt ponds during freeze-up, but the dates of freeze-up differ. MIZMAS accurately simulates the observed date of freeze-up, while CESM2 simulates freeze-up one-to-two weeks earlier. This work demonstrates areas that warrant future observation-model synthesis for improving the representation of sea-ice processes and properties, which can aid accurate simulations of albedo feedbacks in a warming climate.

Abstract. The melting of sea ice floes from the edges (lateral melting) results in open water formation and subsequently increases absorption of solar shortwave energy. However, lateral melt plays a small role in the sea ice mass budget in both hemispheres in most climate models (Keen et al., 2020). This is likely influenced by simple parameterizations of this process in sea ice models that are constrained by limited observations. Here we use a coupled climate model (CESM2.0) to assess the sensitivity of modeled sea ice state to the lateral melt parameterization. The results show that sea ice is sensitive both to the parameters determining the effective lateral melt rate, as well as the nuances in how lateral melting is applied to the ice pack. Increasing the lateral melt rate within the range of reasonable values is largely compensated by decreases in the basal melt rate, but can still result in a significant decrease in sea ice concentration and thickness, particularly in the marginal ice zone. We suggest that it is important to consider the efficiency of melt processes at forming open water, which drives the majority of the ice-albedo feedback. Melt processes are more efficient at forming open water in thinner ice scenarios (as we are likely to see in the future), suggesting the importance of well representing thermodynamic evolution. Revisiting model parameterizations of lateral melting with observations will require finding new ways to represent important physical processes.

The Arctic marine ecosystem is shaped by the seasonality of the solar cycle, spanning from 24-h light at the sea surface in summer to 24-h darkness in winter. The amount of light available for under-ice ecosystems is the result of different physical and biological processes that affect its path through atmosphere, snow, sea ice and water. In this article, we review the present state of knowledge of the abiotic (clouds, sea ice, snow, suspended matter) and biotic (sea ice algae and phytoplankton) controls on the underwater light field. We focus on how the available light affects the seasonal cycle of primary production (sympagic and pelagic) and discuss the sensitivity of ecosystems to changes in the light field based on model simulations. Lastly, we discuss predicted future changes in under-ice light as a consequence of climate change and their potential ecological implications, with the aim of providing a guide for future research.

Model output data for Smith et al., "Effects of increasing the category resolution of the sea ice thickness distribution in a coupled climate model on Arctic and Antarctic sea ice", in review in Journal of Geophysical Research-Oceans, 2022. Details on CESM model settings and run setups can be found within the manuscript.

The magnitude, spectral composition, and variability of the Arctic sea ice surface albedo are key to understanding and numerically simulating Earth’s shortwave energy budget. Spectral and broadband albedos of Arctic sea ice were spatially and temporally sampled by on-ice observers along individual survey lines throughout the sunlit season (April–September, 2020) during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition. The seasonal evolution of albedo for the MOSAiC year was constructed from spatially averaged broadband albedo values for each line. Specific locations were identified as representative of individual ice surface types, including accumulated dry snow, melting snow, bare and melting ice, melting and refreezing ponded ice, and sediment-laden ice. The area-averaged seasonal progression of total albedo recorded during MOSAiC showed remarkable similarity to that recorded 22 years prior on multiyear sea ice during the Surface Heat Budget of the Arctic Ocean (SHEBA) expedition. In accord with these and other previous field efforts, the spectral albedo of relatively thick, snow-free, melting sea ice shows invariance across location, decade, and ice type. In particular, the albedo of snow-free, melting seasonal ice was indistinguishable from that of snow-free, melting second-year ice, suggesting that the highly scattering surface layer that forms on sea ice during the summer is robust and stabilizing. In contrast, the albedo of ponded ice was observed to be highly variable at visible wavelengths. Notable temporal changes in albedo were documented during melt and freeze onset, formation and deepening of melt ponds, and during melt evolution of sediment-laden ice. While model simulations show considerable agreement with the observed seasonal albedo progression, disparities suggest the need to improve how the albedo of both ponded ice and thin, melting ice are simulated.

Colwellia psychrerythraea is a marine psychrophilic bacterium known for its remarkable ability to maintain activity during long-term exposure to extreme subzero temperatures and correspondingly high salinities in sea ice. These microorganisms must have adaptations to both high salinity and low temperature to survive, be metabolically active, or grow in the ice. Here, we report on an experimental design that allowed us to monitor culturability, cell abundance, activity and proteomic signatures of C. psychrerythraea strain 34H (Cp34H) in subzero brines and supercooled sea water through long-term incubations under eight conditions with varying subzero temperatures, salinities and nutrient additions. Shotgun proteomics found novel metabolic strategies used to maintain culturability in response to each independent experimental variable, particularly in pathways regulating carbon, nitrogen and fatty acid metabolism. Statistical analysis of abundances of proteins uniquely identified in isolated conditions provide metabolism-specific protein biosignatures indicative of growth or survival in either increased salinity, decreased temperature, or nutrient limitation. Additionally, to aid in the search for extant life on other icy worlds, analysis of detected short peptides in -10°C incubations after 4 months identified over 500 potential biosignatures that could indicate the presence of terrestrial-like cold-active or halophilic metabolisms on other icy worlds.

On Arctic sea ice, the melt of snow and sea ice generate a summertime flux of fresh water to the upper ocean. The partitioning of this meltwater to storage in melt ponds and deposition in the ocean has consequences for the surface heat budget, the sea ice mass balance, and primary productivity. Synthesizing results from the 1997–1998 SHEBA field experiment, we calculate the sources and sinks of meltwater produced on a multiyear floe during summer melt. The total meltwater input to the system from snowmelt, ice melt, and precipitation from 1 June to 9 August was equivalent to a layer of water 80 cm thick over the ice-covered and open ocean. A total of 85 % of this meltwater was deposited in the ocean, and only 15 % of this meltwater was stored in ponds. The cumulative contributions of meltwater input to the ocean from drainage from the ice surface and bottom melting were roughly equal.