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

The sea ice surface temperature is important to understand the Arctic winter heat budget. We conducted 35 helicopter flights with an infrared camera in winter 2019/2020 during the Multidisciplinary Drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition. The flights were performed from a local, 5 to 10 km scale up to a regional, 20 to 40 km scale. The infrared camera recorded thermal infrared brightness temperatures, which we converted to surface temperatures. More than 150000 images from all flights can be investigated individually. As an advanced data product, we created surface temperature maps for every flight with a 1 m resolution. We corrected image gradients, applied an ice drift correction, georeferenced all pixels, and corrected the surface temperature by its natural temporal drift, which results in time-fixed surface temperature maps for a consistent analysis of one flight. The temporal and spatial variability of sea ice characteristics is an important contribution to an increased understanding of the Arctic heat budget and, in particular, for the validation of satellite products.

The quantification of the sea ice mass balance as the marine part of the cryosphere by satellite observations depend on sea ice thickness data records for the entire ice-covered oceans. The challenges to this task are numerous. Sea ice itself is a highly dynamic medium with a significant variability at meter scale and a strong seasonal cycle which significantly impacts it remote sensing signature. Satellite sensors must therefore provide precise observations at high spatial resolution to observe the full spread of the sea ice thickness distribution and its governing processes such as the dynamic deformation. Average thickness values for larger areas are sufficient for mass balance estimates, however, available methods such as satellite altimetry and passive microwave remote sensing rely on indirect methods and auxiliary information and are often not able to provide information with an acceptable uncertainty for certain or thickness categories or during the presence of surface melt. In addition, suitable satellite sensors in orbits that enabling sea ice thickness retrieval in the inner Arctic Ocean have been in service only until recently in comparison to satellites capable of observing sea ice area. Thus, the assessment of the sea ice mass balance for longer time series is often based on reanalysis models and not Earth Observation data. The sea ice community also traditionally expresses the total sea ice budget volume and not mass. We will therefore present an available sea ice volume data record that is derived by data fusion of CryoSat-2 radar altimeter and SMOS L-Band passive microwave-based sea ice thickness information. Both methods have a complementary sensitivity to different thickness classes and optimal interpolation is employed for gap-less sea ice thickness information in the northern hemisphere since November 2010. The data record is generated for the ESA funded MOS & CryoSat-2 Sea Ice Data Product Processing and Dissemination Service (CS2SMOS-PDS). We discuss the characteristics of the data set and provide an overview of intended evolutions of the data set, specifically improvements to the spatial resolutions, a potential extension to the southern hemisphere and the addition of other available satellite sensors to the optimal interpolation. Within the context of the mass balance of the cryosphere we will share our thoughts on the significance of the CryoSat-2/SMOS based sea ice volume time series for climate applications in the context of its comparable short temporal and how this information can be presented more consistently to other components of the cryosphere.

The sea ice on the oceans in the Arctic and Antarctic is a relatively thin blanket that significantly influences the exchange between the ocean and the atmosphere. The sea ice thickness is a major parameter, which is of great importance for diagnosis and prediction. Determining seasonal and interannual variations in sea ice thickness was the primary objective of ESA's CryoSat Earth Explorer mission. ESA's second Earth Explorer mission, SMOS, provides L-band brightness temperature data that can also be used to infer the thickness of the sea ice, although that was not its primary objective. Both missions complement each other strongly in terms of spatiotemporal sampling and their sensitivity to different ice thickness regimes. In order to further improve the synergistic use of low-frequency radiometric data for sea ice applications, it is imperative to better characterize the uncertainties and covariances associated with the retrieval. A key factor is a thorough understanding of the physical processes that determine the emissivity of sea ice in order to improve the forward model used for retrieval. A thermodynamic model is used to estimate the vertical temperature profile through the snow and sea ice. Therefore, additional meteorological data such as from atmospheric reanalyses and parameterizations of snow and sea ice properties must be taken into account. Natural sea ice is not a homogeneous medium of uniform sea ice and snow thickness, but can only be described by statistical distribution functions on different spatial scales. Thin ice and open water in leads within the compact pack ice also have a significant influence on the brightness temperature measured by SMOS. In order to take all these effects into account, the forward model or the observation operator must be of the appropriate complexity. The inversion to determine the geophysical sea ice parameters can be optimized with a-priori information and parameterizations as well as with information from other satellite sensors. The presentation will focus on a review of the current retrieval method used to generate the AWI-ESA level 3 and level 4 Sea Ice Thickness products and the way forward to improve the emissivity model and to define a common basis metrics validation to assess algorithms evolution considering that in-situ validation data is only sparsely available.

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.

The SIN’XS project, led by NOVELTIS in collaboration with AWI, LEGOS and UCL, is a three-year activity (May 2022 – May 2025) funded by ESA in the frame of the Polar Science Cluster, with the objective to foster collaborative research and interdisciplinary networking actions. 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, using established approaches from the GEO/CEOS Quality Assurance framework for Earth Observation (QA4EO) 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 and impact assessment of the data sets and intercomparisons. In this poster, we will present the main objectives, the tools and the first outcomes of the project.

In the polar oceans in winter, fractures and leads are the hotspots of exchange between the ocean and atmosphere which are otherwise well separated by sea ice. By altering the heat, gas, and momentum fluxes they play a crucial role in atmospheric, ecological, and oceanic processes. At the same time, leads represent a part of the present state of strain of the ice cover, opening up the possibility to study ice rheology. The transient nature of leads and their narrow appearance has set limits to the detection of leads from satellites. Different approaches using active and passive sensors from the microwave and infrared spectrum are employed so far to observe leads by means of satellite data. They make use of the strong contrast between leads and the surrounding ice pack in (i) surface temperature, (ii) microwave backscatter, (iii) emission or (iv) a change in ice drift speed. With the increasing availability of high-resolution SAR data for the Arctic, we explored the potential to use SAR derived sea ice deformation to estimate lead fractions. We calculated sea ice drift and divergence with a spatial resolution of 1.4 km from daily Sentinel-1 scenes. We obtained the divergence-based lead fraction of a region by summing up all positive divergence pixels multiplied by the respective time step length. We derived a second lead fraction product from the deformation fields that calculates the position of linear kinematic features (LKFs) first. The advantage is a skilled noise reduction, and a tracking algorithm of the deformation zones. We compared divergence- and LKF-based lead fractions to several other established lead fraction products in the Transpolar Drift along the drift track of the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) between October 2019 to April 2020. We used lead fractions from helicopter-borne infrared surveys at a grid resolution of 5 m, classified Sentinel-1 (SAR) scenes at 80 m, MODIS (thermal infrared) at 1 km, AMSR2 (passive microwaves) at 3.25 km, and CryoSat-2 (altimeter in Ku-band) at 12.5 km. Since the methods rely on different physical properties of the water and ice in leads and are affected by different constraints, derived mean lead fractions vary by 1-2 magnitudes between the products. For example, infrared, SAR and microwave radiometer-based algorithms do not only detect open-water leads but also leads with thin ice up to a certain thickness, which differs between the products. Common lead events were identified across products. The time series mostly indicated a phase of increased lead activity during freeze-up in autumn 2019 and spring 2020. We used the different lead fraction time series to estimate new ice formation in the leads and compared the results to ice thickness and oceanographic measurements obtained during the MOSAiC campaign. Results yield lower and upper bounds for ice formation and brine expulsion in and from leads. Due to the wide range of lead fractions obtained from different methods, we conclude that the specific lead fraction product must be chosen depending on research question. Divergence- and LKF-based lead fractions provide valuable information in addition to established lead fraction products at high spatial resolution and independent of cloud coverage.

The Copernicus Polar Ice and Snow Topography Altimeter(CRISTAL) mission, planned to be launched in 2027 will incorporate a dual Ku/Ka-band interferometric altimeter with specific transmission pulse sequences designed to enhance the performances over sea and land ice. The open burst mode will enable the generation of Fully Focussed products over sea ice with snow depth retrievals derived from the Ku/Ka range differences instead of taking them from external auxiliary data. In the same way, as in CryoSat-2, the closed burst interferometric mode over land ice will allow the generation of swath elevations for the full Greenland and Antarctica, improving the current coverage of the CryoSat-2swath products that are only produced in the ice margins. At this stage of the mission design, phase B2/C/D, the expected performances need to be evaluated against the requirements to verify the effectiveness of the mission configuration and assess its compliance. In this framework, an end-to-end validation environment has been designed. It is composed of the System and InstrumentSimulator (SIS), the Ground Processor Prototype (GPP), and the Performance assessment tool (PAT). Following the validation plan defined during the first stage of the project, the SIS will be in charge of generating datasets for the different scenarios that are foreseen to be of interest for the mission performance assessment (e.g. point targets, sea ice with different snow properties, ice sheet with small slope and uniform snow and ice characteristics, glaciers with different size, slope, and orientations, ocean tracks with different SWH and wind conditions, river and lakes for specific size and geometry). The GPP will process the simulated data using different processing chains to ensure compliance with the functional and performance requirements. It is composed among others of Level1 Calibration chains, Level1 Low Rate chains(LR-RMC, LR Over-Sampled, and the conventional LR), Level1Delay Doppler chain, Level1 Fully Focussed chain, Level2retrackers module (compilation of different retrackers tailored for the different thematic surfaces), Level2Geophysical corrections and retrievals (translating the information from the retrackers into sea ice, land ice, ocean and inland waters measurements). The PAT is in charge of closing the end-to-end chain: it will cross-check each of the geophysical parameters generated by the GPP against the corresponding requirement, starting from the knowledge of the simulated parameters, assessing and validating the end to end performance chain. This presentation will give an overview of the expected performances of the CRISTAL mission based on the end-to-end validation activity carried out in this project.

Sentinel-3 is an Earth observation satellite series developed by the European Space Agency as part of the Copernicus Programme. It currently consists of 2 satellites: Sentinel-3A and Sentinel-3B, launched respectively on 16 February 2016 and 25 April 2018. Among the on-board instruments, the satellites carry a radar altimeter to provide operational topography measurements of the Earth’s surface. Over sea-ice, the main objective of the Sentinel-3 constellation is to provide accurate measurements of the sea-ice sea surface height and the sea-ice radar freeboard. Compared to previous missions embarking conventional pulse limited altimeters, Sentinel-3 is measuring the surface topography with an enhanced spatial resolution, thanks to the on-board SAR Radar ALtimeter (SRAL), exploiting the delay-Doppler capabilities. To further improve the performances of the Sentinel-3 Altimetry products, ESA and the Sentinel-3 LAND Mission Performance Cluster (MPC) recently developed specialized delay-Doppler and Level-2 processing chains over (1) Inland Waters, (2) Sea-Ice, and (3) Land Ice areas. The objective is to provide new dedicated “thematic products” to the users for the three surfaces mentioned. Over sea-ice the T-IPF will include new algorithms, in particular the hamming window and the zero-padding processing. Thanks to the hamming window, the waveforms measured over specular surfaces are cleaned from spurious energy spread by the azimuth impulse response. The zero-padding provides a better sampling of the radar waveforms, notably valuable in case of specular energy returns. The operational production of these thematic products will start by Fall 2022. To ensure the missions requirements are met, the Sentinel-3 LAND MPC is also in charge of the qualification and the monitoring of the instrument, and core products performances. In this poster, the Sea Ice the Expert Support Laboratories (ESL) of the MPC present a first performance assessment of the Sea Ice thematic products. The analyses include exhaustive inter-comparison with CryoSat-2, showing that the two missions provide similar estimated freeboard measurements. The quality step-up provided by the Sea Ice thematic products, and highlighted in this poster, is a first and major milestone. From now on, the Sentinel-3 Land Thematic Products will independently evolve, to better meet and fulfil the requirements of the Sea Ice community. A Full Mission Reprocessing (FMR) is planned early 2023, to produce fully homogeneous S3A and S3B Sea Ice thematic datasets. A Full Mission Reprocessing (FMR) is planned early 2023, to produce fully homogeneous S3A and S3B Sea Ice thematic datasets.

The research vessel ‘Polarstern’, moored to an ice floe, completed a year long drift with Arctic pack ice in the autumn of 2020. During that expedition, named MOSAiC, a comprehensive data set of airborne laser scanner (ALS) and spaceborne X-band SAR images in the area of the research vessel was acquired. With successful fusion of these two measurements, we can extrapolate sea ice features from the ALS data to the entire SAR scene using a convolutional neural network (CNN). From two preliminary scenes of ALS data we are able to show this for classes of sea ice roughness. This will be the basis for more comprehensive research, once the complete data set is available.

Moored upward-looking Acoustic Doppler Current Profilers (ADCPs) can be used to observe sea ice draft. While previous studies relied on the availability of auxiliary pressure sensors to measure the instrument depth of the ADCP, we present an adaptive approach that infers instrument depth from the ADCPs default bottom track (BT) mode measurements of error velocity and range. We demonstrate that this method can be used to obtain daily mean sea ice draft time series with an estimated uncertainty of 0.1 m. The ADCP-derived ice draft time series are validated with data from adjacent Upward-Looking Sonar (ULS) moorings in the Laptev Sea. This new approach provides a low-cost opportunity to derive daily mean ice draft time series accessing existing ADCP data. Applying this method to ADCP data from the sparsely-sampled Laptev Sea allows an extension of mooring-based in situ ice draft measurements from 2 to about 13 years. The Laptev Sea is an important region for net ice production and a major contributor to the Transpolar Drift System. Recent studies show that sea ice area and volume exports from the Laptev Sea are increasing. This increased export accelerates summer sea ice retreat in the Laptev Sea and has far-reaching consequences for the entire Arctic sea ice balance. The newly acquired Laptev Sea ice draft data archive is used to analyse seasonal and interannual changes in sea ice thickness from 2003 to 2016. In addition, it provides unique data for the comparison with sea ice thickness data records derived from ENVISAT, CryoSat-2 and SMOS satellite measurements in an area where large-scale validation data sets are currently unavailable.

In February and March 2018 a unique polynya of open water had opened in the Wandel Sea north of Greenland due to unusually strong southerly winds. The polynya subsequently refroze and the area of the growing young ice strongly decreased by ice convergence due to northerly winds, constituting a natural, well-constrained, full-scale ice deformation experiment. We have carried out an airborne electromagnetic ice thickness survey of the young ice one month after the polynya began to close. It showed a thickness distribution with a modal ice thickness of 1 m and mean thickness of 2 m, representative of the contributions of thermodynamic and dynamic growth in the one month since the ice had begun to grow. We used time series of Sentinel 1 SAR images to back-track the surveyed young ice to its location of initial formation. Results showed that the area of young ice approximately halved between the time of its formation and the time of the ice thickness survey. This is in good qualitative agreement with the result of the thickness survey, showing that its mean thickness was twice its modal thickness, i.e. mean ice thickness doubled while the region's area halved. These results and the SAR observed deformation processes provide valuable information for improving representation of ice rheology and thickness redistribution in sea ice models.

The snow layer on sea ice has high importance for polar climate as it affects heat, radiation, and fresh-water budgets. Additionally, snow loading is a critical parameter for the sea-ice freeboard-to-thickness conversion for satellite radar and laser altimeters. Despite its importance, there is a lack of snow observations spanning different spatial and temporal scales, thus introducing a significant source of uncertainty to altimetric sea-ice thickness retrievals. The ultra-wideband microwave radar (UWBM) Snow Radar, a 2–18 GHz airborne frequency-modulated continuous-wave (FMCW) radar developed by the Center for Remote Sensing of Ice Sheets (CReSIS) at the University of Kansas, can accurately detect the air/snow and snow/ice interfaces to measure snow thickness. Since 2009, an airborne Snow Radar has been operated onboard NASA’s Operation IceBridge (OIB) campaigns. In 2017, the UWBM Snow Radar was operated for the first time on an Alfred Wegener Institute (AWI) research aircraft, together with an airborne laser scanner for surface topography and freeboard measurements and an electromagnetic induction sounding instrument (EM Bird) to measure total ice thickness. The AWI airborne surveys operate at a low survey altitude (60 m a.g.l.) and slow aircraft speed, enabling fine-resolution mapping of the snow layer. Furthermore, the unique instrument setup on board the AWI research aircraft and the concurrent measurements of snow freeboard, total sea-ice thickness and snow depth allow us to directly investigate the freeboard-to-thickness conversion on regional scales for the first time. Here, we evaluate the performance of the radar installation and present radar-derived snow depth retrieved with a wavelet technique from recent airborne campaigns, PAMARCMiP2017 and IceBird winter 2019, over Arctic sea ice in the Greenland, Lincoln, Beaufort and Chukchi Seas and the central Arctic Ocean in March–April of the respective years.

The second Data Science Symposium at AWI gathered several data science related talks from AWI, GEOMAR and HZG.

The retrieval of Arctic sea ice thickness is one of the major objectives of the European CryoSat-2 radar altimeter mission and the 7-year long period of operation has produced an unprecedented record of monthly sea ice thickness information. We present CryoSat-2 results that show changes and variability of Arctic sea ice for the period 2010 to 2018. CryoSat-2, however, was designed to observe thick perennial sea ice, while retrieving thin seasonal sea ice accurately is more challenging. We have therefore developed a method of completing and improving Arctic sea ice thickness information by merging complementary satellite retrievals. The European SMOS satellite can detect thin sea ice, whereas its companion CryoSat-2 lacks sensitivity. Using these satellite missions together overcomes several issues of single-mission retrievals and provides a more accurate and comprehensive view on the state of Arctic sea-ice thickness at higher temporal resolution. Nevertheless, stand-alone CryoSat-2 observations can be used as reference data for the exploitation of older radar altimetry data sets over sea ice. In order to observe trends in sea ice thickness, it is required to minimize inter-mission biases between subsequent satellite missions. A climate data record of sea ice thickness derived from satellite radar altimetry has been developed for both hemispheres, based on the 15-year (2002-2017) monthly retrievals from Envisat and CryoSat-2 and calibrated in the 2010-2012 overlap period.

The retrieval of Arctic sea ice thickness is one of the major objectives of the European CryoSat-2 radar altimeter mission and the 7-year long period of operation has produced an unprecedented record of monthly sea ice thickness information. We present CryoSat-2 results that show changes and variability of Arctic sea ice from the winter season 2010/2011 until fall 2017. CryoSat-2, however, was designed to observe thick perennial sea ice, while an accurate retrieval of thin seasonal sea ice is more challenging. We have therefore developed a method of completing and improving Arctic sea ice thickness information within the ESA SMOS+ Sea Ice project by merging CryoSat-2 and SMOS sea ice thickness retrievals. Using these satellite missions together overcomes several issues of single-mission retrievals and provides a more accurate and comprehensive view on the state of Arctic sea-ice thickness at higher temporal resolution. However, stand-alone CryoSat-2 observations can be used as reference data for the exploitation of older pulse-limited radar altimetry data sets over sea ice. In order to observe trends in sea ice thickness, it is required to minimize inter-mission biases between subsequent satellite missions. Within the ESA Climate Change Initiative (CCI) on Sea Ice, a climate data record of sea ice thickness derived from satellite radar altimetry has been developed for both hemispheres, based on the 15-year (2002-2017) monthly retrievals from Envisat and CryoSat-2 and calibrated in the 2010-2012 overlap period. The next step in promoting the utilization of sea ice thickness information from radar altimetry is to provide products by a service that meets the requirements for climate applications and operational systems. This task will be pursued within a Copernicus Climate Change Service project (C3S). This framework also aims to include additional sensors such as onboard Sentinel-3 and we will show first results of Sentinel-3 Arctic sea-ice thickness. These developments are the base for preserving the continuity of the sea ice thickness data record and the transformation from research oriented products into an operational service.

More observations of snow depth on sea ice are urgently needed for various applications in polar and climate research. Large-scale and seasonal snow depth products are required for many in-situ, remote sensing, and numerical modelling applications. We developed a new buoy type to obtain time series of snow depth and air temperature on Arctic and Antarctic sea ice. The buoy is based on four sonic ranging sensors, and transmits the data via Iridium satellites. The buoy concept and design are based on low unit costs and easy deployment. Snow buoys proved to be most valuable when co-deployed with other buoy types. Near real time data sharing into international networks for a large user community: GTS, buoy programs.

There is an increasing public interest in sea ice information from both Polar Regions, which requires up-to-date background information and data sets at different levels for various target groups. In order to serve this interest and need, seaiceportal.de (originally: meereisportal.de) was developed as a comprehensive German knowledge platform on sea ice and its snow cover in the Arctic and Antarctic. It was launched in April 2013. Since then, the content and selection of data sets increased and the data portal received increasing attention, also from the international science community. Meanwhile, we are providing near-real time and archive data of many key parameters of sea ice and its snow cover. The data sets result from measurements acquired by various platforms as well as numerical simulations. Satellite observations of sea ice concentration, freeboard, thickness and drift are available as gridded data sets. Sea ice and snow temperatures and thickness as well as atmospheric parameters are available from autonomous platforms (buoys). Additional ship observations, ice station measurements, and mooring time series are compiled as data collections over the last decade. In parallel, we are continuously extending our meta-data and uncertainty information for all data sets. In addition to the data portal, seaiceportal.de provides general comprehensive background information on sea ice and snow as well as expert statements on recent observations and developments. This content is mostly in German in order to complement the various existing international sites for the German speaking public. We will present the portal, its content and function, but we are also asking for direct user feedback.

Sea ice physicists from the Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research (AWI), are anticipating that the sea ice cover in the Arctic Ocean this summer may shrink to the record low of 2012. The scientists made this projection after evaluating current satellite data about the thickness of the ice cover. The data show that the arctic sea ice was already extraordinarily thin in the summer of 2015. Comparably little new ice formed during the past winter.

More observations of snow depth on sea ice are urgently needed for various applications in polar and climate research. Large-scale and seasonal snow depth products are required for many in-situ, remote sensing, and numerical modelling applications. We developed a new buoy type to obtain time series of snow depth (and air temperature) on Arctic and Antarctic sea ice. The buoy is based on four sonic ranging sensors, and transmits the data via Iridium satellites. The buoy concept and design are based on low unit costs and easy deployment. Snow buoys proved to be most valuable when co-deployed with other buoy types. Near real time data sharing into international networks for a large user community: GTS, buoy programs

The snow cover on sea ice received more and more attention in recent sea ice studies and model simulations, because its physical properties dominate many sea ice and upper ocean processes. In particular; the temporal and spatial distribution of snow depth is of crucial importance for the energy and mass budgets of sea ice, as well as for the interaction with the atmosphere and the oceanic freshwater budget. Snow depth is also a crucial parameter for sea ice thickness retrieval algorithms from satellite altimetry data. Recent time series of Arctic sea ice volume only use monthly snow depth climatology, which cannot take into account annual changes of the snow depth and its properties. For Antarctic sea ice, no such climatology is available. With a few exceptions, snow depth on sea ice is determined from manual in-situ measurements with very limited coverage of space and time. Hence the need for more consistent observational data sets of snow depth on sea ice is frequently highlighted. Here, we present time series measurements of snow depths on Antarctic and Arctic sea ice, recorded by an innovative and affordable platform. This Snow Buoy is optimized to autonomously monitor the evolution of snow depth on sea ice and will allow new insights into its seasonality. In addition, the instruments report air temperature and atmospheric pressure directly into different international networks, e.g. the Global Telecommunication System (GTS) and the International Arctic Buoy Programme (IABP). We introduce the Snow Buoy concept together with technical specifications and results on data quality, reliability, and performance of the units. We highlight the findings from four buoys, which simultaneously drifted through the Weddell Sea for more than 1.5 years, revealing unique information on characteristic regional and seasonal differences. Finally, results from seven snow buoys co-deployed on Arctic sea ice throughout the winter season 2015/16 suggest the great importance of local effects, weather events, and potential influences of dynamic sea ice processes on snow accumulation.

There is an increasing public interest in sea ice information from both Polar Regions, which requires up-to-date background information and data sets at different levels for various target groups. In order to serve this interest and need, seaiceportal.de (originally: meereisportal.de) was developed as a comprehensive German knowledge platform on sea ice and its snow cover in the Arctic and Antarctic. It was launched in April 2013. Since then, the content and selection of data sets increased and the data portal received increasing attention, also from the international science community. Meanwhile, we are providing near-real time and archive data of many key parameters of sea ice and its snow cover. The data sets result from measurements acquired by various platforms as well as numerical simulations. Satellite observations of sea ice concentration, freeboard, thickness and drift are available as gridded data sets. Sea ice and snow temperatures and thickness as well as atmospheric parameters are available from autonomous platforms (buoys). Additional ship observations, ice station measurements, and mooring time series are compiled as data collections over the last decade. In parallel, we are continuously extending our meta-data and uncertainty information for all data sets. In addition to the data portal, seaiceportal.de provides general comprehensive background information on sea ice and snow as well as expert statements on recent observations and developments. This content is mostly in German in order to complement the various existing international sites for the German speaking public. We will present the portal, its content and function, but we are also asking for direct user feedback.

Snow on sea ice is a relevant polar climate parameter related to ocean-atmospheric interactions and surface albedo. It also remains an important factor for sea-ice thickness products retrieved from Ku-band satellite radar altimeters like Envisat or CryoSat-2, which is currently on its mission and the subject of many recent studies. Such satellites sense the height of the sea-ice surface above the sea level, which is called sea-ice freeboard. By assuming hydrostatic equilibrium and that the main scattering horizon is given by the snow-ice interface, the freeboard can be transformed into sea-ice thickness. Therefore, information about the snow load on hemispherical scale is crucial. Due to the lack of sufficient satellite products, only climatological values are used in current studies. Since such values do not represent the high variability of snow distribution in the Arctic, they can be a substantial contributor to the total sea-ice thickness uncertainty budget. Secondly, recent studies suggest that the snow layer cannot be considered as homogenous, but possibly rather featuring a complex stratigraphy due to wind compaction and/or ice lenses. Therefore, the Ku-band radar signal can be scattered at internal layers, causing a shift of the main scattering horizon towards the snow surface. This alters the freeboard and thickness retrieval as the assumption that the main scattering horizon is given by the snow-ice interface is no longer valid and introduces a bias. Here, we present estimates for the impact of snow depth uncertainties and snow properties on CryoSat-2 sea-ice thickness retrievals. We therefore compare CryoSat-2 freeboard measurements with field data from ice mass-balance buoys and aircraft campaigns from the CryoSat Validation Experiment. This unique validation dataset includes airborne laser scanner and radar altimeter measurements in spring coincident to CryoSat-2 overflights, and allows us to evaluate how the main scattering horizon is altered by the presence of a complex snow stratigraphy.

In Antarctica, ice crystals (platelets) form and grow in supercooled waters below ice shelves. These platelets rise, accumulate beneath nearby sea ice, and subsequently form a several meter thick, porous sub-ice platelet layer. This special ice type is a unique habitat, influences sea-ice mass and energy balance, and its volume can be interpreted as an indicator of the health of an ice shelf. Although progress has been made in determining and understanding its spatio-temporal variability based on point measurements, an investigation of this phenomenon on a larger scale remains a challenge due to logistical constraints and a lack of suitable methodology. In the present study, we applied a lateral constrained Marquardt-Levenberg inversion to a unique multi-frequency electromagnetic (EM) induction sounding dataset obtained on the ice-shelf influenced fast-ice regime of Atka Bay, eastern Weddell Sea. We adapted the inversion algorithm to incorporate a sensor specific signal bias, and confirmed the reliability of the algorithm by performing a sensitivity study using synthetic data. We inverted the field data for sea-ice and platelet-layer thickness and electrical conductivity, and calculated ice-volume fractions within the platelet layer using Archie’s Law. The thickness results agreed well with drillhole validation datasets within the uncertainty range, and the ice-volume fraction yielded results comparable to other studies. Both parameters together enable an estimation of the total ice volume within the platelet layer, which was found to be comparable to the volume of landfast sea ice in this region, and corresponded to more than a quarter of the annual basal melt volume of the nearby Ekström Ice Shelf. Our findings show that multi-frequency EM induction sounding is a suitable approach to efficiently map sea-ice and platelet-layer properties, with important implications for research into ocean/ice-shelf/sea-ice interactions. However, a successful application of this technique requires a break with traditional EM sensor calibration strategies due to the need of absolute calibration with respect to a physical forward model.

The significant loss of Arctic sea ice during the last decades shows the sensitivity of the sea-ice system to changes in global climate. To distinguish between natural variability and the impact of global warming, an understanding of processes and feedbacks is necessary, and for that, consistent and comprehensive measurements of the most important sea-ice properties are required. While sea-ice concentration is observed routinely year-round since the beginning of the satellite era, strategies to investigate the sea-ice thickness distribution have been developed only recently. These are crucially required for an examination of sea-ice mass changes. Presently, ice thickness observations are mainly based on freeboard measurements by means of satellite laser and radar altimetry. To contribute to the interpretation of these sea-ice thickness products, available airborne thickness and freeboard data were collected within the Sea Ice Downstream Services for Arctic and Antarctic Users and Stakeholders (SIDARUS) EU-Project, and have been analyzed with respect to their usability for the validation of the large-scale satellite products. One major challenge in comparing satellite and airborne measurements is the different footprint area of these methods. Therefore, statistical parameters like the variability of freeboard within the common footprint areas have been analyzed from measurements made during the PAMARCMIP 2011 campaign in order to determine the differences between point measurements and areal averages. It turned out that mean freeboard is less dependent of the freeboard areas than the modal values are. Furthermore, differences in modal and mean values for the range of chosen footprint areas have been related to their dependency on different ice characteristics and length scales of freeboard and thickness profiles. Also for this comparison, mean values are found to be more representative, as the results are mostly independent from the footprint but depend more on the length scales. However, there was no length scale that was representative for all the observed regions. Finally, results will be used for the interpretation of the comparison between freeboard and sea-ice thickness data derived from different data sources using laser and radar altimetry.

The sea-ice thickness distribution is one of the most important sea-ice properties, but also one of the less frequently observed ones so far. Satellite retrievals of Antarctic sea-ice thickness are currently limited to laser and radar altimetry observations of snow freeboard with large uncertainties, and electromagnetic measurements have been obtained only sporadically. For the investigation of the variability and changes in the sea-ice thickness distribution over the last decades, data are mainly available from very basic methods such as drilling or ship-based observations following the Antarctic Sea Ice Processes and Climate (ASPeCt) protocol. Thereby it is an advantage that those data also include information on the snow-depth and partly on the sea-ice freeboard distribution, which are as sparse as information on the sea-ice thickness distribution, in particular during winter conditions. The most recent data based on those methods were obtained during austral winter 2013, when various sea-ice parameters were measured in the Weddell Sea as part of the Antarctic Winter Ecosystem Climate Study (AWECS). Here, we present first results of the sea-ice thickness, freeboard and snow-depth distribution obtained by drill-hole measurements from this expedition. The new data set is compared with results from three previous winter campaigns done in 1989, 1992 and 2006 in the Weddell Sea in order to determine the long-term variability of sea-ice thickness, snow depth and freeboard. A challenge in comparing all those data is that measurement sites are based only on individual floes, which are expected to be representative for an entire region. In addition, sampling rates differ between the considered field experiments. Therefore, drill-hole thicknesses are cross-correlated with ground-based EM-measurements in order to identify for the newest data set, how representative the chosen study areas have been for the respective sea-ice floes and which consequences different measurement spacing has for the comparison of data from different years.

The understanding and predictability of the observed decline of Arctic sea ice depends on the knowledge of its mass balance in a warming environment. While sea ice extent is monitored by passive microwave sensors for decades, only recently its volume is measured by basin-scale sea ice thickness observations of satellite altimetry missions. The current sea ice thickness sensor is SIRAL, a synthetic aperture radar altimeter on-board ESAs CryoSat-2. Altimetry missions measure freeboard, the height of the ice surface above the local water level, which can be converted into sea ice thickness. The conversion is very sensitive to errors in the freeboard retrieval and uncertainties in input parameters for the freeboard-tothickness conversion. Snow on Arctic sea ice plays a crucial role, since its regional variable physical parameters control the penetration of the Ku-Band radar waves and snow depth is required for the sea ice thickness retrieval algorithm, but not measured Arctic-wide. We present Arctic sea ice freeboard and thickness maps from CryoSat-2. The results are compared to available airborne validation datasets, which have been collected in an international validation program (CryoVEx). Sea ice thickness datasets obtained by airborne electromagnetic inductions sounding are available in Arctic spring of 2011 and 2012 and late summer of 2012 to quantify the uncertainties of the CryoSat-2 Arctic sea ice thickness data product of the Alfred Wegener Institute. Compared to the Arctic, only few validation datasets exist for CryoSat-2 sea ice data in the southern Ocean. We present the layout and first results of CryoSat-2 validation campaigns in the Weddell and Bellingshausen Seas between June and October 2013. The complicated snow properties of Antarctic sea ice may increase the uncertainty of CryoSat-2 sea ice thickness data, however sea ice volume estimates in the southern hemisphere are needed as well to understand the contrasting increase of Antarctic sea ice area.

The polar oceans' sea ice cover is a challenging geophysical target to map. Current state of practice helicopter-electromagnetic (HEM) ice thickness mapping is limited to 1D interpretation due to common procedures and systems that are mainly sensitive to layered structures. We present a new generation Multi-sensor, Airborne Sea Ice Explorer (MAiSIE) to overcome these limitations. As the actual sea ice structure is 3D and in parts heterogeneous, errors up to 50% are observed due to the common 1D approximation. With MAiSIE we present a new EM concept based on one multi frequency transmitter loop and a three component receiver coil triplet without bucking The small weight frees additional payload to include a line scanner (lidar) and high accuracy INS/dGPS. The 3D surface topography from the scanner with the EM data at from 500 Hz to 8 kHz, in x, y, and z direction, will increase the accuracy of HEM derived pressure ridge geometry significantly. Experience from two field campaigns shows the proof-of-concept with acceptable sensor drift and receiver sensitivity. The preliminary 20 ppm noise level @ 4.1 kHz is sufficient to map level ice thickness with 10 cm precision for sensor altitudes below 13 m.

The significant loss of Arctic sea ice during the last decades shows the sensitivity of the sea ice system to changes in the global climate. To distinguish between natural variability and the impact of global warming, an understanding of processes and feedbacks is necessary and for that, consistent and comprehensive measurements of the most important sea ice properties are required. While sea ice concentration is observed routinely year-round since the beginning of the satellite era, strategies to investigate the sea ice thickness distribution, crucially needed for an investigation of ice mass changes, has only recently been developed. To contribute to the interpretation of the remotely sensed sea ice thickness products, which are mainly based on freeboard determination from altimeter measurements, available airborne sea ice thickness and freeboard data have been collected within the Sea Ice Downstream Services for Arctic and Antarctic Users and Stakeholders (SIDARUS) EU-Project, and have been analyzed with respect to their usability for validation of the large scale satellite products. Thus, statistical parameters like the variability of freeboards within the common footprint areas of satellites have been analyzed from measurements made during the PAMARCMIP 2011 campaign to determine the differences between point measurements and areal averages. Also, impacts on the deviated sea ice thicknesses have been studied by means of a cross validation of freeboard-based sea ice thicknesses with airborne thickness measurements with electromagnetic induction sounding. Finally, since during the PAMARCMIP campaign few flights were performed in conjunction with CryoSat-2 overpasses, the airborne-based freeboards can finally be used for a comparison with satellite-derived data.

The only remote sensing technique capable of obtain- ing sea-ice thickness on basin-scale are satellite altime- ter missions, such as the 2010 launched CryoSat-2. It is equipped with a Ku-Band radar altimeter, which mea- sures the height of the ice surface above the sea level. This method requires highly accurate range measure- ments. During the CryoSat Validation Experiment (Cry- oVEx) 2011 in the Lincoln Sea, Cryosat-2 underpasses were accomplished with two aircraft, which carried an airborne laser-scanner, a radar altimeter and an electro- magnetic induction device for direct sea-ice thickness re- trieval. Both aircraft flew in close formation at the same time of a CryoSat-2 overpass. This is a study about the comparison of the sea-ice freeboard and thickness dis- tribution of airborne validation and CryoSat-2 measure- ments within the multi-year sea-ice region of the Lincoln Sea in spring, with respect to the penetration of the Ku- Band signal into the snow.

Sea ice thickness on basin-scale is an important variable in the polar climate system, however datasets are sparse. The only remote sensing technique capable of obtaining sea ice thickness on that scale are satellite altimeter missions, such as the ICESat and CryoSat-2. The CryoSat-2 satellite was launched in 2010 and is equipped with the Ku-Band radar altimeter SIRAL. CryoSat-2 is part of the ESA’s Living Planet Programme and was especially developed for the observation of changes in the cryosphere. This includes especially the determination of variations in sea ice thickness in the Arctic Ocean. For that purpose it is essential to validate the Cryosat-2 products. The CryoSat Validation Experiment (CryoVEx) combines field and airborne measurements in the Arctic and Antarctica in order to validate CryoSat measurements. Here we report the results from the first combined aircraft and satellite data acquisition over sea ice in the Arctic Ocean. The aircraft was equipped with ASIRAS, an airborne radar altimeter, which was built to simulate the SIRAL sensor on CryoSat-2. During the CryoVEx 2011 campaign in the Lincoln Sea several Cryosat-2 underpasses were accomplished with two aircraft. One aircraft was equipped with ASIRAS and an airborne laser scanner; the second aircraft carried an electromagnetic induction device for direct sea ice thickness retrieval and an airborne laser scanner as well. Both aircraft flew in close formation at the same time of a CryoSat-2 overpass. This is a presentation about the results from comparing sea ice freeboard distribution of laser and radar altimeter measurements with the CryoSat-2 product within the multi-year sea ice region of the Lincoln Sea in spring, with respect to the penetration of the Ku-Band signal into the snow and the effect of surface roughness on the radar range retrieval.

The polar oceans’ sea ice cover is an unconventional and challenging geophysical target to map. Current state of ractice helicopter-electromagnetic (HEM) ice thickness apping is limited to 1D interpretation due to common rocedures and systems that are mainly sensitive to layered tructures. We present a new generation Multi-sensor, irborne Sea Ice Explorer (MAiSIE) to overcome these imitations. As the actual sea ice structure is 3D and in parts heterogeneous, errors up to 50% are observed due to the common 1D approximation. By virtue of 3D finite element modeling, we find that more than one frequency is needed, ideally in the range 1 – 5 kHz, to improve thickness estimates of grounded pressure ridges, a common 3D sea ice structure. With MAiSIE we present a new electromagnetic (EM) concept based on one multi frequency transmitter loop and a three component receiver coil triplet, with active digital bucking (no bucking coil). The comparably small weight of the EM components frees enough additional payload to include three laser devices including a line scanner and high accuracy INS/dGPS. Integrating the high resolution 3D ice surface topography from the laser scanner with the EM data at frequencies from 600 Hz to 10 kHz, expressed as normalized secondary fields in x, y, and z direction, increases the accuracy of HEM derived pressure ridge geometry significantly.