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Automated sea ice charting from Synthetic Aperture Radar (SAR) has been researched for more than a decade and still, we are not close to unlocking the full potential of automated solutions in terms of resolution and accuracy. The central complications arise from ground truth data not being readily available in the polar regions. In this paper, we build a dataset from 20 near coincident X-Band SAR acquisitions and as many Airborne Laser Scanner (ALS) measurements from the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC), between October and May. This dataset is then used to assess the accuracy and robustness of five machine learning based approaches, by deriving classes from the freeboard, surface roughness (standard deviation at 0.5 m correlation length) and reflectance. It is shown that there is only a weak correllation of the radar backscatter and the sea ice topography. Accuracies between 40 % and 69 % percent and robustnesses between 68 % and 85 % give a realistic insight into modern classifiers' performance across a range of ice conditions over 8 months. It also marks the first time algorithms are trained entirely with labels from coincident measurements, allowing for a probabilistic class retrieval. The results show that segmentation models able to learn from the class distribution significantly perform pixel-wise classification approaches.

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.

Oral presentation at the 2nd MOSAiC science conference showing the MOSAiC airborne laser scanner product overview and first results of seasonal surface roughness

The SIN’XS project is a three-year activity (May 2022 – May 2025) funded by ESA in the frame of the Polar Science Cluster.In light of rapid changes of the Arctic and Antarctic sea ice cover, continued and improved observations, understanding, and predictions of its thickness are particularly important for a range of fields from climate studies to offshore operations in ice. Systematic and accurate ice thickness observations are now available from several satellite missions. However, they differ in used processing algorithms and assumptions, temporal and spatial coverage and resolution, and applicability to stakeholder needs like modelling and assimilation, numerical weather prediction, and ship routing. These differences between products have so far complicated the consistent use of the various data products and there is little consensus about Arctic and Antarctic Sea ice volume variability and change. The Sea Ice-thickness product iNter-comparison eXerciSe (SIN’XS) will identify some of these gaps by carrying out in-depth intercomparisons of a wide range of satellite ice thickness products from altimetry and other methods, in close collaboration with an international community of scientific and operational sea ice experts, and in partnership with the WMO Global Cryosphere Watch (GCW).It will develop joint protocols for the intercomparison of ice thickness products and their validation, based on established approaches from the QA4EO project and by further developing a framework for Fiducial Reference Measurements (FRMs). SIN’XS will develop an online system to engage the community with data submission and to support scientific analysis of the data sets and intercomparisons., The 28th IUGG General Assembly (IUGG2023) (Berlin 2023)

The porosity of sea ice is a crucial property for understanding processes and feedback mechanisms of the polar-climate system, as it strongly affects the physical, ecological, and biogeochemical properties of sea ice. Sea ice porosity is also closely related to surface flooding and the solid fraction of platelet ice in Antarctica.A direct method for measuring sea ice porosity is electromagnetic (EM) induction sounding, which can be applied on the ground or from airborne platforms. We present advancements in data collection, calibration, and inversion procedures. In this study, we modified the Phyton EMagPy API for fast and adaptable inversion of sea ice surveys and use inverted EM data to study the porosity of sea ice in the Arctic and Antarctic.Over Arctic summer sea, we retrieve the macro-scale porosity of rotten ice and the salinity and depth evolution of melt ponds. The salinity and porosity evolution could be reproduced with varying success, but the addition of several layers in the inversion improved the thickness information compared to a single-layer subsurface model, affecting ice mass balance.For high-resolution EM data over Antarctic fast ice we retrieve the thickness and solid fraction of a variable sub-ice platelet layer below the solid sea ice. The inverted thicknesses of sea ice and the platelet layer as well as their conductivities are in good agreement with independent, coincident in-situ drill hole and CTD measurements., The 28th IUGG General Assembly (IUGG2023) (Berlin 2023)

Background In 2019, the German Multiple Sclerosis (MS) Society was certified as a provider for ?Funktionstraining? (FT). FT is an exercise training program developed for people with disabilities or people at risk of disability, takes place weekly and is led by a qualified FT-therapist. It is prescribed by a physician (between 12 and 24 months) and is part of outpatient medical rehabilitation. Due to the COVID-19 pandemic, the tele-rehabilitation concept ‘Funktionstraining-online’ (FT-online) was developed for pwMS. This study examines the FT-online from a participants' point of view within an online survey. Methods We developed an online questionnaire that included data of sample characteristics, participants' experiences with FT-online in terms of usability and training content. Further, the survey captured the quality of FT-online and the FT-therapist and compared carefully FT-online with face-to-face training. The standardised questionnaires Self-Efficacy Scale - Short Form (ASKU), the Multiple Sclerosis Questionnaire for Physiotherapists MSQPT and the Fatigue-Questionnaire (WeiMuS) were included. The 103 interviewed people with MS (pwMS) participated in FT-online at least for three months. Results Data analyses are in process. The response rate was 75% (n = 78). The analysed sample is 53.4±8.1 years old with a disease duration of 18±8.7 years (male=7, female=71). Preliminary results in the ASKU certify a low self-efficacy in the sample (2.25 ±0.67). Qualitative results show the advantages for FT-online in the independence of mobility and infrastructure, flexibility, compatibility within job and family, group feeling in times of social distancing and an increase in quality of life. The disadvantages described by the sample are mainly technical problems and lack of socialising. 35% (n = 27) participants experienced both: FT-online and face-to-face. 44.4% (n = 12) of this sample prefer FT-online, 33.3% (n = 9) prefer the face-to-face training course and 22.2% (n = 6) rate both kinds of training equal. Conclusions The implementation of FT-online was an important step to ensure the exercise-related physical activity in pwMS during the COVID-19 pandemic. The descriptive analyses show high potential for FT-online training in pwMS. We are aware of the bias in current data, because of the pandemic situation both the free choice of FT-offers and the pandemic circumstances held influence in study outcomes. First results lead to the conclusion that FT-online may be beneficial for a broad range of persons with neurologic diseases, movement disorders and fatigue episodes and should be considered for future medical rehabilitation.

Sea-ice thickness is a key factor and indicator in understanding the impact of the global climate change. Deriving basin-wide sea-ice thickness estimates from satellite laser and radar altimetry relies on freeboard measurements. The freeboard-to-thickness conversion in turn requires information of snow mass and the density of the sea-ice layer that have unknown spatio-temporal variabilities and trends directly translating into the uncertainty of decadal sea-ice thickness data records. In addition, inter-mission biases arise from, e.g., different sensor types and frequencies as well as varying footprint sizes affected by surface roughness across regions and seasons. Therefore, carrying out validation and inter-calibration studies is crucial for reliable and continuous observation of the Earth’s cryosphere. To achieve this, it is beneficial to have simultaneous measurements of freeboard, snow depth, and sea-ice thickness, which provide reference data for both direct satellite observations and geophysical target parameters. Here, we present Alfred Wegener Institute’s (AWI) IceBird program, which is a series of fixed-wing aircraft campaigns to measure Arctic sea ice and to monitor its change. During two late-winter campaigns in the western Arctic Ocean in 2017 and 2019, we have carried out surveys with the unique scientific instrument configuration including an airborne laser scanner (ALS) for surface topography and freeboard measurements, a tethered electromagnetic induction sounding instrument (EM-Bird) for total (snow+ice) thickness measurements, and an ultrawideband frequency-modulated continuous-wave microwave radar to measure snow thickness. Therefore, we are able to observe all three bounding interfaces in the sea-ice–snow system in high resolution along survey tracks on regional scales. During the ship-based drift expedition Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) between October 2019 and September 2020, helicopter surveys were carried out in high spatio-temporal resolution throughout the year, including the polar night, to measure freeboard and roughness with the ALS both in local grid pattern and in larger scale. Coincident EM-Bird ice thickness data and information from snow measurements on the ground will help linking these parameters and monitor them and their effect on satellite retrievals for a full seasonal cycle. The individual parameters are important for describing and monitoring the state of the Arctic sea ice and validating retrievals from satellite data, but combined they offer further possibilities to characterise sea ice. By assuming isostatic equilibrium, we are able to estimate up-to-date bulk density values for different sea-ice types from the IceBird data and to derive a parametrisation of sea-ice bulk density based on sea-ice freeboard. These data allow us to explore spatio-temporal variations in sea-ice parameters observable from space and to evaluate the validity of the freeboard-to-thickness conversion in satellite altimetry through comparison against dedicated satellite overpasses and orbit collections.

An integrated sensor platform including an inertial navigation system (INS) and a commercial airborne laser scanner (ALS) among other sensor was mounted in the cargo compartment in one of the Polarstern helicopters during MOSAiC. ALS data was acquired from more than 60 flights between October 2019 and September 2020 with a range of survey types intended to map changes of the sea ice surface during the full annual cycle at high spatial resolution and coverage. Here, we provide an overview of the collected data, the challenge of achieving centimeter elevation accuracy with a helicopter platform at high polar latitudes as well as the content and specifications of ALS data products. The high spatial resolution and repeated coverage of the larger area around Polarstern allow studying various surface features (e.g. pressure ridges, floes, melt ponds, snow drifts, etc.), their seasonal evolution, and their impact on atmosphere and ocean. Finally, we outline methods for planned applications, such as identifying individual floes and surface types using both measured freeboard and surface reflectance. Collocated helicopter-based optical and infrared imagery allow analyzing sea ice properties in further applications and to upscale comparable in-situ observations.