Description: Raw data (horizontal and Vertical polarization voltages) of the mobile L-band radiometer, called ARIEL from BALAMIS Company. This raw data can be converted to Brightness Temperature, which can be used to measure ice thickness during the MOSAiC expedition legs PS122/4 and PS122/5. The files contains the horizontal and Vertical polarization voltages measured with the ARIEL radiometer during July and August 2020. The label of each columns are: 1 - On-board computer time stamp [hhmmss] 2 - Internal hot load [Volts] 3 - Antenna polarization 1 [Volts] (V-pol) 4 - Antenna polarization 2 [Volts] (H-pol) 5 - Internal cold load [Volts] 6 - Internal temperature [Celsius] 7 - Heater for temperature stabilization power [%] 8 - IR photodiode reading [Celsius] 9 - GPS time stamps [hhmmss] 10 - GPS latitude 11 - GPS longitude 12 - GPS altitude 13 - GPS connected flag 14 - Ethernet cable connected flag

Description: The data contains brightness temperature data measured by ARIEL at 1.4GHz, during the MOSAIC expedition, in particular from July to September 2022 (LEG4 and LEG5). The ARIEL radiometer is a dual polarization (H & V) total power radiometer with internal calibration. The central frequency is 1.41 GHz, with a bandwidth of 20 MHz. The system has a 2x1 patch antenna, with a beam width of 36 ◦ at 3 dB at the azimuth direction and 70 ◦ at 3 dB at the elevation angle. The radiometric accuracy of ARIEL is 1.06 K at 1 Hz sampling frequency, with the capability to measure at higher sampling rates (up to 10 Hz) at the expenses of the radiometric accuracy. A co-located thermal infrared photodiode to measure the surface temperature and a GPS receiver complete the sensor equipment. Calibration is performed with a hot load and a cold load. To adapt the ARIEL instrument to the harsh and cold conditions of the Arctic, two adaptions were required to increase the internal thermal resistance by adding isolating material and to apply conformal coating to protect the electronics against humidity. The ARIEL accuracy was 2.3 K (instead of 1 K, due to a software error on the sampling rate). This light (7 kg) and small radiometer (40 cm x 60 cm x 20 cm) is ideal for frequent manoeuvres. The radiometer was mounted on a wooden sledge to measure microwave emission at 40 ◦ incidence angle with respect to nadir. A calibration procedure for the radiometers is needed to convert the measured voltages to brightness temperatures. The calibration of the ARIEL was done pointing the radiometer to cold and hot targets. The cold target is the cold sky (approx. temperature of 6 K (from Le Vine and Skou (2006)), while the hot target was absorber material at the instrument frequency stored into a big box (which represent an emissivity of 1). The calibration routines were performed every few days (3-5 days). After filtering the outliers, the data was smoothed to further reduce the noise. A sliding window of 20 samples was applied, which has proven to work better with ARIEL data, reducing standard deviation and therefore the noise of the measurements (Fabregat (2021)). Moreover, since the radiometer was over a moving ice cap, the position with respect to the Polarstern is computed, in addition to the GPS position, to simplify the collocation with other instrument measurements. We used a Python code provided by Dr. Stefan Hendricks (AWI) to compute this relative position (Gitlab reference: https://gitlab.awi.de/floenavi-crs).

Description: Leads play an important role in the exchange of heat, gases, vapour, and particles between seawater and the atmosphere in ice-covered polar oceans. In summer, these processes can be modified significantly by the formation of a meltwater layer at the surface, yet we know little about the dynamics of meltwater layer formation and persistence. During the drift campaign of the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC), we examined how variation in lead width, re-freezing, and mixing events affected the vertical structure of lead waters during late summer in the central Arctic. At the beginning of the 4-week survey period, a meltwater layer occupied the surface 0.8 m of the lead, and temperature and salinity showed strong vertical gradients. Stable oxygen isotopes indicate that the meltwater consisted mainly of sea ice meltwater rather than snow meltwater. During the first half of the survey period (before freezing), the meltwater layer thickness decreased rapidly as lead width increased and stretched the layer horizontally. During the latter half of the survey period (after freezing of the lead surface), stratification weakened and the meltwater layer became thinner before disappearing completely due to surface ice formation and mixing processes. Removal of meltwater during surface ice formation explained about 43% of the reduction in thickness of the meltwater layer. The remaining approximate 57% could be explained by mixing within the water column initiated by disturbance of the lower boundary of the meltwater layer through wind-induced ice floe drift. These results indicate that rapid, dynamic changes to lead water structure can have potentially significant effects on the exchange of physical and biogeochemical components throughout the atmosphere–lead–underlying seawater system.

Description: We present a comprehensive review of the current status of remotely sensed and in situ sea ice, ocean, and land parameters acquired over the Arctic and Antarctic and identify current data gaps through comparison with the portfolio of products provided by Copernicus services. While we include several land parameters, the focus of our review is on the marine sector. The analysis is facilitated by the outputs of the KEPLER H2020 project. This project developed a road map for Copernicus to deliver an improved European capacity for monitoring and forecasting of the Polar Regions, including recommendations and lessons learnt, and the role citizen science can play in supporting Copernicus’ capabilities and giving users ownership in the system. In addition to summarising this information we also provide an assessment of future satellite missions (in particular the Copernicus Sentinel Expansion Missions), in terms of the potential enhancements they can provide for environmental monitoring and integration/assimilation into modelling/forecast products. We identify possible synergies between parameters obtained from different satellite missions to increase the information content and the robustness of specific data products considering the end-users requirements, in particular maritime safety. We analyse the potential of new variables and new techniques relevant for assimilation into simulations and forecasts of environmental conditions and changes in the Polar Regions at various spatial and temporal scales. This work concludes with several specific recommendations to the EU for improving the satellite-based monitoring of the Polar Regions.