Description: Sea ice is an integral part of the climate system of the high latitude regions. Up to now, control of its occurrence and extent, especially its interannual and long-term variability, has proved difficult to isolate or quantify, especially in the data devoid regions of the Southern Ocean. The consequences of climate change induced, for example, by the continued increase of greenhouse gases, on the occurrence of sea ice, is even less certain, although the theory at least suggests that sea ice extent changes could be expected to have a positive feedback role, i.e. that reduced ice extent could be expected to enhance warming at high latitudes. The interaction of sea ice with the polar ocean and atmosphere can be summerized as follows: - The snow covered sea ice reflects the solar illumination much stronger compared to open water areas. Therefore, changes in the horizontal coverage of sea ice (ice concentration) would be related to changes of the surface reflectivity. In the polar winter, sea ice isolates the ocean from the cold polar atmosphere and reduces the heat transfer by one or two orders. Both has a strong impact on the radiation balance. - Sea ice growth and melting has a signinficant influence on the circulation of the oceans. The formation of sea ice increases the water density of the ocean boundary layer due to rejection of brine. This results in an unstable stratification of the ocean layer and deep water formation can occure. The opposite behaviour can be observed when sea ice melts. The additional freshwater causes the ocean to form a stable boundary layer.

Description: This dataset comprises quality-checked sea-ice concentration at 1 km spatial resolution from Sentinel-2 imagery. 83 Sentinel-2 scenes distributed over the East Siberian, Laptev, Kara, Barents and Beaufort Seas as well as the Fram Strait between February and May 2019 are analysed. For each scene, we investigated histograms of the Level 1C (L1C) reflectance of band 4 (665 nm) at 10 m resolution and manually identified two thresholds for each scene to separate it into water, thin ice and thick ice. We use the classified water/thin-ice/thick-ice images to create two sea-ice concentration datasets at 1 km spatial resolution: One which contains the thin ice (sic_thin in the netCDF files) and one which contains the thick ice (sic_thick in the netCDF files). To this end, we average the images over 100x100 pixels and interpret the ratio of sea-ice pixels within these 100x100 pixel windows as sea-ice concentration. The total sea-ice concentration can be obtained as the sum of sic_thin and sic_thick. The ice thickness of thin-ice pixels is likely below 50 cm. The data are gridded using a Transverse Mercator projection. Details about the projection can be found in the netCDF metadata. Details about the dataset are presented in https://doi.org/10.3390/rs12193183.

Description: IMBs are autonomous instruments able to continuously monitor the growth and melt of sea ice and its snow cover at a single point on an ice floe. Complementing field expeditions, remote sensing observations and modelling studies, this in-situ data is crucial to assess the mass balance and seasonal evolution of sea ice and snow in the polar oceans. Established subtypes of IMBs combine coarse-resolution temperature profiles through air, snow, ice and ocean with ultrasonic pingers to detect snow accumulation and ice thermodynamic growth. Recent technological advancements enable the use of high-resolution temperature chains, which are also able to identify the surrounding medium through a „heating cycle“. The temperature change during this heating cycle provides additional information on the internal properties and processes of the ice. However, a unified data processing technique to reliably and accurately determine sea ice thickness and snow depth from this kind of data is still missing, and an unambiguous interpretation remains a challenge. Following the need to improve techniques for remotely measuring sea ice mass balance, an international IMB working group has recently been established. The main goals are 1) to coordinate IMB deployments, 2) to enhance current IMB data processing and –interpretation techniques, and 3) to provide standardized IMB data products to a broader community. We present results from an intercomparison study, which compares different techniques of IMB data processing, with a focus on the automatic calculation of sea ice thickness and snow depth in selected IMB datasets from the Arctic and Antarctic. The results of a number of existing algorithms are evaluated, and validated against reference datasets from manual inspection and co-deployed instruments. Finally, recommendations with respect to the manifold challenges of IMB data processing and -interpretation are highlighted.

Description: Research on improving the prediction skill of climate models requires refining the quality of observational data used for initializing and tuning the models. This is especially true in the polar regions where uncertainties about the interactions between sea ice, ocean, and atmosphere are driving ongoing monitoring efforts. The Copernicus Imaging Microwave Radiometer (CIMR) is an European Space Agency (ESA) candidate mission which promises to offer high resolution, low uncertainty observation capabilities at the 1.4, 6.9, 10.65, 18.7, and 36.5 GHz frequencies. To assess the potential impact of CIMR for sea ice parameter retrieval, a comparison is made between retrievals based on present AMSR2 observations and a retrieval using future CIMR equivalent observations over a data set of validated sea ice concentration (SIC) values. An optimal estimation retrieval method (OEM) is used which can use input from different channel combinations to retrieve seven geophysical parameters (sea ice concentration, multi-year ice fraction, ice surface temperature, columnar water vapor, liquid water path, over ocean wind speed, and sea surface temperature). An advantage of CIMR over existing radiometers is that it would provide higher spatial resolution observations at the lower frequency channels (6.9, 10.65, and 18.7 GHz) which are less sensitive to atmospheric influence. This enables the passive microwave based retrieval of SIC and other surface parameters with higher resolution and lower uncertainty than is currently possible. An information content analysis expands the comparison between AMSR2 and CIMR to all retrievable surface and atmospheric parameters. This analysis quantifies the contributions to the observed signal and highlights the differences between different input channel combinations. The higher resolution of the low frequency CIMR channels allow for unprecedented detail to be achieved in Arctic passive microwave sea ice retrievals. The presence of 1.4 GHz channels on board CIMR opens up the possibility for thin sea ice thickness (SIT) retrieval. A combination of collocated AMSR2 and SMOS observations is used to simulate a full CIMR suite of measurements, and the OEM is modified to include SIT as a retrieval parameter. The output from different retrieval configurations is compared with an operational SIT product. The CIMR instrument can provide increased accuracy for SIC retrieval at very high resolutions with a combination of the 18.7 and 36.5 GHz channels while also maintaining sensitivity for atmospheric water vapor retrieval. In combination with the 1.4 GHz channels, SIT can be added as an eighth retrieval parameter with performance on par with existing operational products.