Description: The overarching goal of the remotely operated vehicle (ROV) operations during MOSAiC was to provide access to the underside of sea ice for a variety of interdisciplinary science objectives throughout an entire year. The M500 ROV was equipped with a large variety of sensors and operated at several sites within the MOSAiC central observatory. Despite logistical and technological challenges, over the full year we accomplished a total of ~60 days of operations with over 300 hours of scientific dive time. 3D ice bottom geometry was mapped in high resolution using an acoustic multibeam sonar covering a 300 m circle around the access hole complementing other ice mass balance measurements on transects, by autonomous systems, airborne laser scanning and from classical ablation stakes. Various camera systems enabled us to document features of sea ice growth and decay. From early March onwards, with the sun rising again, a main focus was the investigation of the spatial variability in ice optical properties. Light transmittance was measured with several hyperspectral radiometers under marked survey areas, including various ice types such as first-year ice, second-year ice, pressure ridges, and leads. Optical surveys were coordinated with surface albedo measurements, vertical snow profiles and aerial photography. The ROV also supported ecosystem research by deploying sediment traps underneath pressure ridges, sampling algal communities at the ice bottom and in ridge cavities with a suction sampler as well as the regular towed under-ice zooplankton and phytoplankton nets. Ice algal coverage was further investigated using an underwater hyperspectral imaging system, while the ROV video cameras enabled the observation of fish and seals living in ridge cavities. The ROV also carried further oceanographic sensors providing vertical and horizontal transect measurements of small-scale bio-physical water column properties such as chlorophyll content, nutrients, optical properties, temperature, salinity and dissolved oxygen. Here we present first highlights from the year-long operations: the discovery of platelet ice under Arctic winter sea ice during polar night and the extensive time series of multibeam derived ice draft maps, which allow together with airborne laser scanner data a full 3D documentation of ice geometry.

Description: During the 2018 Multidisciplinary Arctic Program‐Last Ice in the Lincoln Sea, we sampled 45 multiyear ice (MYI) and 34 first‐year ice (FYI) cores, combined with snow depth, ice thickness, and transmittance surveys from adjacent level FYI and undeformed MYI. FYI sites show a decoupling between bottom‐ice chlorophyll a (chl a) and snow depth; however, MYI showed a significant correlation between ice‐algal chl a biomass and snow depth. Topographic control of the snow cover resulted in greater spatiotemporal variability of the snow over the level FYI, and consequently transmittance, compared to MYI with an undulating surface. The coupled patterns of snow depth, transmittance, and chl a indicate that MYI provides an environment with more stable light conditions for ice algal growth. The importance of sea ice surface topography for ice algal habitat underpins the potential ecological changes associated with projected increased ice dynamics and deformation.

Description: As the annual expanse of Arctic summer ice‐cover steadily decreases, concomitant biogeochemical and ecological changes in this region are likely to occur. Because the Central Arctic Ocean is often nutrient and light limited, it is essential to understand how environmental changes will affect productivity, phytoplankton species composition, and ensuing changes in biogeochemistry in the region. During the transition from late summer to early autumn, water column sampling of various biogeochemical parameters was conducted along an ice‐floe drift station near the North Pole. Our results show that as the upper water column stratification weakened during the late summer–early autumn transition, nutrient concentrations, particulate dimethylsulfoniopropionate (DMSPp) levels, photosynthetic efficiency, and biological productivity, as estimated by ΔO2/Ar ratios, all decreased. Chemotaxonomic (CHEMTAX) analysis of phytoplankton pigments revealed a taxonomically diverse picoautotrophic community, with chlorophyll (Chl) c3‐containing flagellates and the prasinophyte, Pyramimonas spp., as the most abundant groups, comprising ~ 30% and 20% of the total Chl a (TChl a) biomass, respectively. In contrast to previous studies, the picoprasinophyte, Micromonas spp., represented only 5% to 10% of the TChl a biomass. Of the nine taxonomic groups identified, DMSPp was most closely associated with Pyramimonas spp., a Chl b‐containing species not usually considered a high DMSP producer. As the extent and duration of open, ice‐free waters in the Central Arctic Ocean progressively increases, we suggest that enhanced light transmission could potentially expand the ecological niche of Pyramimonas spp. in the region.

Description: Light transmission through Arctic sea ice and snow has an important impact on energy partitioning at the atmosphere-ice-ocean interface and the ice-associated ecosystem. Thus, it is crucial to understand which parameters determine the temporal and spatial variation of sea ice transmission. Ice and snow imprint characteristic features on the spectral shape of transmitted light. Here, we aim to use these spectral features to retrieve snow depth from hyperspectral under-ice light measurements. Transmitted spectral radiance was measured underneath a 100 m long transect on level landfast First-Year-Ice (FYI) using a remotely operated vehicle (ROV). Measurements took place off the northern coast of Ellesmere Island close to the Canadian Forces Station Alert in May 2018. Co-located measurements of ice and snow thickness were acquired with an electromagnetic induction device, a Magna-Probe and a terrestrial laser scanner. The small variation in FYI thickness allows separating the spectral effect of snow depth on transmitted radiance spectra. We retrieve snow depth from spectral transflectance data using an inverse algorithm based on normalized difference indices (NDI). We further fit multiplicative exponential functions to the measured spectra to retrieve wavelength-dependent extinction coefficients of sea ice and snow. Fitted values of broadband bulk extinction coefficients range from 1.8 to 3.5 m-1 for sea ice and from 7.4 to 17.2 m-1 for snow. Mean differences in fitted/calculated and measured modal snow depths are 6 cm for the multiplicative exponential functions and 5 cm using NDIs. 41% of the fitted snow depths lie within 5 cm of the measured snow depths using the multiplicative exponential functions and 42% for the NDI-method. The accuracy of snow depth retrieved from our optical approaches is limited to +/-5 cm, as the variation of snow depth within the optical sensor footprint is between 2.5 and 5.0 cm. Our results show how this optical approach allows to derive large-scale snow depth information from under-ice optical spectra e.g. during autonomous long-range under-ice missions, despite its limited spatial resolution and absolute accuracy.

Description: The radiative transfer of short-wave solar radiation through the sea ice cover of the polar oceans is a crucial aspect of energy partitioning at the atmosphere-ice-ocean interface. A detailed understanding of how sunlight is reflected, absorbed and transmitted by the sea ice cover is needed for an accurate representation of critical processes in climate and ecosystem models, such as the ice-albedo feedback. Due to the challenges associated with ice internal measurements, most information about radiative transfer in sea ice has been gained by optical measurements above and below the sea ice. To improve our understanding of radiative transfer processes within the ice itself, we developed an innovative, chain-type instrument equipped with up to 64 multispectral light sensors that can be frozen into the ice. Here we present the results of a first prototype deployment at the North Pole in fall of 2018, as well as recently acquired data from the MOSAiC drift expedition in spring and summer 2020. We discuss the advantages, application, and limits of the device and provide first new insights into the spatiotemporal aspect of radiative transfer within the sea ice itself. In particular, we investigate how measured attenuation coefficients relate to the optical properties of the ice pack, and show that sideward planar irradiance measurements are equivalent to measurements of total scalar irradiance. We also show how this light sensor chain can be used for assessment of the temporal evolution in ice algal biomass and water column properties.

Description: Light transmittance through Arctic sea ice has an important impact on both the ocean heat content and the ice associated ecosystem. Thus, it is crucial to investigate the optical properties of sea ice to assess the role of the surface energy budget and its change due to climate change. Measurements of spectral transmittance can be used to investigate the influence of surface and ice properties regulating radiative transfer, especially on a larger horizontal scale. Here, we concentrate on categorizing snow and sea ice based on spectral transmittance data. Transmitted radiance and irradiance are measured at the underside of sea ice using a remotely operated vehicle (ROV). The scientific payload also includes CTD, fluorometer, pH-, nitrate-, oxygen-, attenuation sensor, upward-looking single-beam sonar, and periodically a surface and under ice trawl for assessing the spatio-temporal variability of sea ice algae. Thus, data for all disciplines in sea ice research can be recorded. The main benefits using the ROV compared to point measurements are the larger spatial coverage in comparably short times and the undisturbed sampling even under very thin sea ice, with parameters all collected during the same time. Snow depth is derived from a combination of terrestrial laser scanner data and manual measurements, while ice draft is measured using the single-beam sonar. Here, we present first data from the Last Ice campaign off Alert in May 2018. This region is dominated by sea ice with a larger thickness due to dynamic thickening. We investigated different ice regimes, such as First Year Ice with a continuous thickness of about 1.5 m and structured Multi Year Ice with thicknesses up to 6 m over the duration of four weeks to study the differences between various ice types.

Description: Progress report on the work of FRAM Task 3.1 for the bi-annual FRAM workshop.

Description: Sea ice and its snow cover play a key role within the climate and ecosystem. Due to global environmental changes which are amplified in the Arctic Ocean, its sea-ice cover will primarily consist of thin and young sea ice with a reduction in extent. In particular, the area where snow accumulates reduces and the fraction of melt-pond covered sea ice and of openings in the sea-ice cover such as leads increase. Those changes of the surface conditions strongly influence the partitioning of solar radiation. The main objective of this dissertation was to establish relationships between the surface conditions that are observed and expected to dominate in the future Arctic and under-ice radiation. A deeper and broader knowledge of such relationships is especially necessary in spring and autumn during which the under-ice radiation can have significant impacts on the annual energy budget. To achieve that, field measurements collected using a variety of instruments during three campaigns for three different sea-ice types, locations, and seasons were analysed and interpreted. A main result was to derive a new parametrization for snow depth retrieval from spectral under iceradiation measurements. This was successfully achieved with an accuracy of approximately 5 cm for two ice types, in two locations, during two seasons. In contrast to the established theory that melt ponds act as bright windows to the underlying ocean, it was possible to document and analyse cases where a thicker snow cover accumulated on melt ponds compared to on adjacent bare ice. This resulted, surprisingly, in lower levels of under-ice radiation underneath the melt ponds than underneath bare ice. New analyses of relationships between thermodynamics and optics of a refreezing lead and thin ice suggest that radiative transfer in thin ice is often not accurately accounted for using bulk formulations, as they are applicable for thicker ice. The initial states of the lead’s opening and refreezing need to be treated separately and cannot generally be considered windows into the ocean. This dissertation extended our knowledge of the relationships between snow and surface conditions and under-ice radiation. The results point towards impacts on sea-ice energy balance, ocean heat content, thermodynamic ice growth, and ice-and ocean-associated ecosystem activity.

Description: Light transmittance through Arctic sea ice and snow has an important impact on both the ocean heat content and the ice-associated ecosystem. The partitioning of the radiation is a key factor of the mass and energy balance of Arctic sea ice. It is therefore crucial to measure sea ice transmittance and understand which parameters determine its variation on temporal and spatial scales. Ice and snow imprint characteristic features in the spectral shape of transmitted light. Transmitted spectral irradiance was recorded at the underside of levelled landfast First-Year-Ice (FYI) in a refrozen lead using a hyper-spectral radiometer mounted on a remotely operated vehicle (ROV) during the Last Ice Area campaign off Alert in the Lincoln Sea in May 2018. The main benefits of using the ROV are large spatial coverage in comparably short survey times and non-destructive measurements under sea ice. Snow depth was obtained using a Magna Probe and a Terrestrial Laser Scanner measured the surface topography. The total ice thickness was recorded with a ground-based electromagnetic induction sounding device whereas an upward-looking single-beam sonar also mounted on the ROV recorded ice draft. This unique co-located data set enables to categorize groups of spectral transmittances. Due to the relatively constant FYI thickness it was possible to separate the spectral effect of snow depth on the light transmittance. Further we discuss how to retrieve snow depth and ice thickness based only on spectral transmittance data by developing a new observation-based inverse algorithm. Three methods are envisioned: First, to fit a multiplicative exponential function to the spectra which includes wavelength-dependent extinction coefficients of snow and sea ice. Second, to follow a statistical approach using normalized difference indices (NDIs) to construct spectral correlation coefficients between the NDIs with snow depth and ice thickness. Third, to generate synthetic spectra from snow depth and ice thickness using the radiative transfer model AccuRT and compare those with the observed spectra. Expected results are accurate snow depth and sea ice thickness (as well as melt pond depth and coverage).