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Chapter 3 in Sea Ice: Its Physics, Chemistry, Biology, Geology and Societal Importance 

Abstract. Identifying the processes that drive the rapid climatological retreat phase of Antarctica’s annual sea-ice cycle is crucial to understanding, modelling and attributing observed trends and recent high variability in sea-ice extent, and to projecting future sea-ice conditions and impacts accurately. To date, the rapid annual retreat of Antarctic sea ice each spring–summer has been largely attributed to lateral and basal melting of ice floes, enhanced by wave-induced breakup of large floes. Here, based on observations and modelling, we propose that waves play important additional roles in generating previously-neglected surface and interior melting, by removing snow from small floes, flooding them, and pulverising them into slush. Results here show a resultant estimated reduction in albedo by 0.38–0.54, that increases melting by 0.9–5.2 cm day-1 at 60–70o S compared to a snow-covered floe of first-year ice, and depending on surface type, wave-flooding coverage, latitude and ice density. Rapid proliferation of algae within and on the high-light and high-nutrient environment of the wave-modified ice reduces the albedo by a further 0.1 to increase the melt-rate enhancement to 1.1–6.1 cm day-1. Melting is further accelerated by a wave-induced ice–albedo feedback mechanism, similar to that associated with Arctic melt ponds but involving seawater rather than freshwater. This positive feedback is strengthened by ice-algal greening. Floe thinning and weakening by wave-melting initiate additional dynamic–thermodynamic feedbacks by increasing the likelihood of both wave-flooding and flexural breakup, leading to further floe melting. Wave melting and the associated physical–biological feedbacks will likely increase in importance in a predicted stormier and warmer Southern Ocean, and will also become more prevalent in a changing Arctic. There are implications for global weather and climate, the health of the ocean and its ecosystems, fisheries, ice-shelf stability and sea-level rise, atmospheric and oceanic biogeochemistry, and human activities. 

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. 

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. This is likely influenced by the simple parameterization of lateral melting 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 in preindustrial and 2×CO2 runs. The runs explore the implications of how lateral melting is parameterized and structural changes in how it is applied. The results show that sea ice is sensitive both to the parameters determining the effective lateral melt rate and the nuances in how lateral melting is applied to the ice pack. Increasing the lateral melt rate is largely compensated for by decreases in the basal melt rate but still results in a significant decrease in sea ice concentration and thickness, particularly in the marginal ice zone. Our analysis suggests that this is tied to the increased efficiency of lateral melting at forming open water during the summer melt season, which drives the majority of the ice–albedo feedback. The more seasonal Southern Hemisphere ice cover undergoes larger relative reductions in sea ice concentration and thickness for the same relative increase in lateral melt rate, likely due to the hemispheric differences in the role of the sea-ice–upper-ocean coupling.Additionally, increasing the lateral melt rate under a 2×CO2 forcing, where sea ice is thinner, results in a smaller relative change in sea ice mean state but suggests that open-water-formation feedbacks are likely to steepen the decline to ice-free summer conditions.Overall, 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 accurately representing thermodynamic evolution. Revisiting model parameterizations of lateral melting with observations will require finding new ways to represent salient physical processes. 

Abstract. On Arctic sea ice, the melt of snow and sea ice generate asummertime flux of fresh water to the upper ocean. The partitioning of thismeltwater to storage in melt ponds and deposition in the ocean hasconsequences for the surface heat budget, the sea ice mass balance, andprimary productivity. Synthesizing results from the 1997–1998 SHEBA fieldexperiment, we calculate the sources and sinks of meltwater produced on amultiyear floe during summer melt. The total meltwater input to the systemfrom snowmelt, ice melt, and precipitation from 1 June to 9 August wasequivalent to a layer of water 80 cm thick over the ice-covered and openocean. 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 ofmeltwater input to the ocean from drainage from the ice surface and bottommelting were roughly equal. 

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. 

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. 

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.