Modelling the early-Holocene Laurentide Ice Sheet collapse and abrupt climate change: implications for the 8.2 ka event

Recent research suggested that the deglaciation of an ice saddle connecting three ice domes around Hudson Bay ˜8.5 ka produced a large meltwater pulse. The resulting freshwater input to the North Atlantic was proposed as having caused the most pronounced climate change event of the Holocene, the 8.2 ka event. However, modelling experiments focussing on this saddle collapse meltwater and its climatic impact have not yet been carried out. This thesis aims to establish whether such a meltwater pulse could have forced the 8.2 ka event, and if so, to better constrain the pulse through climate and ice sheet modelling. A series of HadCM3 general circulation model -simulations was performed using idealised freshwater forcing scenarios designed to represent the centennial-length saddle collapse meltwater flux. The simulations demonstrated that the saddle collapse meltwaterwas likely the primary cause of the 8.2 ka event. An appropriate model setup for simulating early-Holocene Laurentide Ice Sheet evolution was then developed using the BISICLES ice sheet model, and an ensemble of simulations of the period 10–7.5 ka was run. An ice saddle collapse is simulated as part of the deglaciation, and the resulting meltwater pulse is in agreement with the timing of North Atlantic surface freshening signals, but is longer and less pronounced than the forcing used in the HadCM3 scenarios that best matched the climate-proxy data. The findings suggest that the BISICLES model setup simulates a dynamically realistic meltwater pulse, but there is a mismatch between the simulated pulse and the forcing necessary for reproducing the 8.2 ka event with HadCM3. Future work should further develop the BISICLES model setup as outlined in the thesis in order to refine the constraints of the meltwater pulse. This could allow for using the 8.2 ka event for assessing the sensitivity of general circulation models to ocean circulation perturbations

The MOSAiC ROV Program: One Year of Comprehensive Under-Ice Observations

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

Relation between sea ice freeboard and draft and its seasonal evolution in the Central Arctic

Relating the sea-ice surface to the under-ice topography is a timely scientific effort in the Arctic. This relation is crucial for estimating the ice thickness distribution for large‐scale modelling, for assessing the mechanical force that ships need to overcome, for risk evaluation of offshore structures, for determining roughness characteristics to derive wind and water drag coefficients for dynamics modelling, for sound scattering, and for the confinement of under-ice oil spills. Existing relations are based on numerical modelling assuming estimates of snow depth, snow density, and ice density or are based on field observations confined to specific areas and short time periods. MOSAiC provided the first year-long, high-resolution dataset of sea-ice draft derived from a multibeam echosounder. In combination with co-located freeboard estimates from airborne mapping of the surface, we construct the 3D sea-ice topography to study the evolution of sea-ice geometry both at the surface and underside. We can obtain direct and high precision relations between draft and freeboard on an almost weekly basis for an ice floe continuously drifting from the North Pole to Fram Strait during winter, spring, and summer. A precise evaluation of total ice thickness, ice density, freeboard, draft and their respective relations on small scales is crucial information to future satellite remote sensing ice thickness retrievals, a key asset of climate monitoring in the Arctic

Non-invasive geophysical investigation and thermodynamic analysis of a palsa in Lapland, northwest Finland

Non-invasive geophysical prospecting and a thermodynamic model were used to examine the structure, depth and lateral extent of the frozen core of a palsa near Lake Peerajärvi, in northwest Finland. A simple thermodynamic model verified that the current climatic conditions in the study area allow sustainable palsa development. A ground penetrating radar (GPR) survey of the palsa under both winter and summer conditions revealed its internal structure and the size of its frozen core. GPR imaging in summer detected the upper peat/core boundary, and imaging in winter detected a deep reflector that probably represents the lower core boundary. This indicates that only a combined summer and winter GPR survey completely reveals the lateral and vertical extent of the frozen core of the palsa. The core underlies the active layer at a depth of ~0.6 m and extends to about 4 m depth. Its lateral extent is ~15 m x ~30 m. The presence of the frozen core could also be traced as minima in surface temperature and ground conductivity measurements. These field methods and thermodynamic models can be utilized in studies of climate impact on Arctic wetlands.Peer reviewe

Interdisciplinary observations of the under-ice environment using a remotely operated vehicle

Improving our understanding of the climate and ecosystem of the sea-ice covered Arctic Ocean was a key objective during MOSAiC. We aimed for a better understanding of the linkages of physical and biological processes at the interface between sea ice and ocean. To enhance the quantification of these linkages, year-round observations of physical, biological, and chemical parameters are needed. We operated a remotely operated vehicle (ROV) equipped with an interdisciplinary sensor platform to simultaneously measure these parameters underneath the drifting sea ice. These observations were made synchronous in time and place enabling a description of their spatial and temporal variability. Overall, we completed more than 80 surveys covering all seasons and various sea ice and surface conditions. We focused on optical parameters, sea-ice bottom topography, and upper ocean physical and biological oceanography. In addition, visual documentation of the under-ice environment was performed, nets for zooplankton were towed, and the ROV was used for instrument deployment and maintenance. Here, we present all ROV sensor data, allowing for a comprehensive picture of the under-ice environment. We are inviting discussions on further collaboration in data analyses and usage, in particular co-location and merging with other datasets from MOSAiC and other (also future) projects

Snow-related variability of spectral light transmittance of Arctic First-Year-Ice in the Lincoln Sea

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)

SIOS’s Earth observation and remote sensing activities toward building an efficient regional observing system in Svalbard

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Platelet ice under Arctic pack ice in winter

The formation of platelet ice is well known to occur under Antarctic sea ice, where subice platelet layers form from supercooled ice shelf water. In the Arctic, however, platelet ice formation has not been extensively observed, and its formation and morphology currently remain enigmatic. Here, we present the first comprehensive, long‐term in situ observations of a decimeter thick subice platelet layer under free‐drifting pack ice of the Central Arctic in winter. Observations carried out with a remotely operated underwater vehicle (ROV) during the midwinter leg of the MOSAiC drift expedition provide clear evidence of the growth of platelet ice layers from supercooled water present in the ocean mixed layer. This platelet formation takes place under all ice types present during the surveys. Oceanographic data from autonomous observing platforms lead us to the conclusion that platelet ice formation is a widespread but yet overlooked feature of Arctic winter sea ice growth