The observed changes in physical properties of sea ice such as decreased thickness and increased melt pond cover severely impact the energy budget of Arctic sea ice. Increased light transmission leads to increased deposition of solar energy in the upper ocean and thus plays a crucial role for amount and timing of sea‐ice‐melt and under‐ice primary production. Recent developments in underwater technology provide new opportunities to study light transmission below the largely inaccessible underside of sea ice. We measured spectral under‐ice radiance and irradiance using the new Nereid Under‐Ice (NUI) underwater robotic vehicle, during a cruise of the R/V Polarstern to 83°N 6°W in the Arctic Ocean in July 2014. NUI is a next generation hybrid remotely operated vehicle (H‐ROV) designed for both remotely piloted and autonomous surveys underneath land‐fast and moving sea ice. Here we present results from one of the first comprehensive scientific dives of NUI employing its interdisciplinary sensor suite. We combine under‐ice optical measurements with three dimensional under‐ice topography (multibeam sonar) and aerial images of the surface conditions. We investigate the influence of spatially varying ice‐thickness and surface properties on the spatial variability of light transmittance during summer. Our results show that surface properties such as melt ponds dominate the spatial distribution of the under‐ice light field on small scales (<1000 m 2 ), while sea ice‐thickness is the most important predictor for light transmission on larger scales. In addition, we propose the use of an algorithm to obtain histograms of light transmission from distributions of sea ice thickness and surface albedo.

Year-round observations of the physical snow and ice properties and processes that govern the ice pack evolution and its interaction with the atmosphere and the ocean were conducted during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition of the research vessel Polarstern in the Arctic Ocean from October 2019 to September 2020. This work was embedded into the interdisciplinary design of the 5 MOSAiC teams, studying the atmosphere, the sea ice, the ocean, the ecosystem, and biogeochemical processes. The overall aim of the snow and sea ice observations during MOSAiC was to characterize the physical properties of the snow and ice cover comprehensively in the central Arctic over an entire annual cycle. This objective was achieved by detailed observations of physical properties and of energy and mass balance of snow and ice. By studying snow and sea ice dynamics over nested spatial scales from centimeters to tens of kilometers, the variability across scales can be considered. On-ice observations of in situ and remote sensing properties of the different surface types over all seasons will help to improve numerical process and climate models and to establish and validate novel satellite remote sensing methods; the linkages to accompanying airborne measurements, satellite observations, and results of numerical models are discussed. We found large spatial variabilities of snow metamorphism and thermal regimes impacting sea ice growth. We conclude that the highly variable snow cover needs to be considered in more detail (in observations, remote sensing, and models) to better understand snow-related feedback processes. The ice pack revealed rapid transformations and motions along the drift in all seasons. The number of coupled ice–ocean interface processes observed in detail are expected to guide upcoming research with respect to the changing Arctic sea ice.

Light transmission through sea ice is a critical process for energy partitioning at the polar atmosphere‐ice‐ocean boundary. Transmission of sunlight strongly impacts sea ice melting by absorption, as well as heat deposition, and primary productivity in the upper ocean. While earlier observations relied on a limited number of point observations, the recent years have seen an increase in spatially distributed light measurements underneath sea ice using remotely operated vehicles covering a wide range of ice conditions. These measurements allow us to reconstruct the seasonal evolution of the spatial variability in light transmission. Here we present measurements of sea ice light transmittance distributions from 6 years of Arctic under‐ice remotely operated vehicle operations. The data set covers the entire melt period of Central Arctic sea ice. Data are combined into a pseudo time series describing the seasonal evolution of the spatial variability of sea ice optical properties from spring to autumn freezeup. In spring, snowmelt increases light transmission continuously, until a secondary mode originating from translucent melt ponds appears in the histograms of light transmittance. This secondary mode persists long into autumn, before snowfall reduces overall light levels again. Comparison to several autonomous time series measurements from single locations confirms the detected general patterns of the seasonal evolution of light transmittance variability. This also includes characteristic spectral features caused by biological processes at the ice underside. The results allow for the evaluation of three different light transmittance parameterizations, implying that light transmission in current ice‐ocean models may not be accurately represented on large scales throughout all seasons while ice thickness alone is a poor predictor of light transmittance.

Abstract. Arctic sea ice has not only decreased in volume during the last decades, but has also changed in its physical properties towards a thinner and more seasonal ice cover. These changes strongly impact the energy budget, and might affect the ice-associated ecosystems. In this study, we quantify solar shortwave fluxes through sea ice for the entire Arctic during all seasons. To focus on sea-ice-related processes, we exclude fluxes through open water, scaling linearly with sea ice concentration. We present a new parameterization of light transmittance through sea ice for all seasons as a function of variable sea ice properties. The maximum monthly mean solar heat flux under the ice of 30 × 10 5 Jm −2 occurs in June, enough heat to melt 0.3 m of sea ice. Furthermore, our results suggest that 96 % of the annual solar heat input through sea ice occurs during only a 4-month period from May to August. Applying the new parameterization to remote sensing and reanalysis data from 1979 to 2011, we find an increase in transmitted light of 1.5 % yr −1 for all regions. This corresponds to an increase in potential sea ice bottom melt of 63 % over the 33-year study period. Sensitivity studies reveal that the results depend strongly on the timing of melt onset and the correct classification of ice types. Assuming 2 weeks earlier melt onset, the annual transmitted solar radiation to the upper ocean increases by 20 %. Continuing the observed transition from a mixed multi-year/first-year sea ice cover to a seasonal ice cover results in an increase in light transmittance by an additional 18 %.

An improved understanding of the temporal variability and the spatial distribution of snowmelt on Antarctic sea ice is crucial to better quantify atmosphere-ice-ocean interactions, in particular sea-ice mass and energy budgets. It is therefore important to understand the mechanisms that drive snowmelt, both at different times of the year and in different regions around Antarctica. In this study, we combine diurnal brightness temperature differences (dT B (37 GHz)) and ratios (T B (19 GHz)/T B (37 GHz)) to detect and classify snowmelt processes. We distinguish temporary snowmelt from continuous snowmelt to characterize dominant melt patterns for different Antarctic sea-ice regions from 1988/1989 to 2014/2015. Our results indicate four characteristic melt types. On average, 38.9 6 6.0% of all detected melt events are diurnal freeze-thaw cycles in the surface snow layer, characteristic of temporary melt (Type A). Less than 2% reveal immediate continuous snowmelt throughout the snowpack, i.e., strong melt over a period of several days (Type B). In 11.7 6 4.0%, Type A and B take place consecutively (Type C), and for 47.8 6 6.8% no surface melt is observed at all (Type D). Continuous snowmelt is primarily observed in the outflow of the Weddell Gyre and in the northern Ross Sea, usually 17 days after the onset of temporary melt. Comparisons with Snow Buoy data suggest that also the onset of continuous snowmelt does not translate into changes in snow depth for a longer period but might rather affect the internal stratigraphy and density structure of the snowpack. Considering the entire data set, the timing of snowmelt processes does not show significant temporal trends.