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: Capability for sea surface salinity observation was an important gap in ocean remote sensing in the last few decades of the 20th century. New technological developments during the 1990s at the European Space Agency led to the proposal of SMOS (Soil Moisture and Ocean Salinity), an Earth explorer opportunity mission based on the use of a microwave interferometric radiometer, MIRAS (Microwave Imaging Radiometer with Aperture Synthesis). SMOS, the first satellite ever addressing the observation of ocean salinity from space, was successfully launched in November 2009. The determination of salinity from the MIRAS radiometric measurements at 1.4 GHz is a complex procedure that requires high performance from the instrument and accurate modelling of several physical processes that impact on the microwave emission of the ocean’s surface. This paper introduces SMOS in the ocean remote sensing context, and summarizes the MIRAS principles of operation and the SMOS salinity retrieval approach. It describes the Spanish SMOS high-level data processing centre (CP34) and the SMOS Barcelona Expert Centre on Radiometric Calibration and Ocean Salinity (SMOS-BEC), and presents a preliminary validation of global sea surface salinity maps operationally produced by CP34.

Description: The global navigation satellite system (GNSS) Transpolar Earth Reflectometry exploriNg system (G-TERN) was proposed in response to ESA's Earth Explorer 9 revised call by a team of 33 multi-disciplinary scientists. The primary objective of the mission is to quantify at high spatio-temporal resolution crucial characteristics, processes and interactions between sea ice, and other Earth system components in order to advance the understanding and prediction of climate change and its impacts on the environment and society. The objective is articulated through three key questions. 1) In a rapidly changing Arctic regime and under the resilient Antarctic sea ice trend, how will highly dynamic forcings and couplings between the various components of the ocean, atmosphere, and cryosphere modify or influence the processes governing the characteristics of the sea ice cover (ice production, growth, deformation, and melt)? 2) What are the impacts of extreme events and feedback mechanisms on sea ice evolution? 3) What are the effects of the cryosphere behaviors, either rapidly changing or resiliently stable, on the global oceanic and atmospheric circulation and mid-latitude extreme events? To contribute answering these questions, G-TERN will measure key parameters of the sea ice, the oceans, and the atmosphere with frequent and dense coverage over polar areas, becoming a “dynamic mapper”of the ice conditions, the ice production, and the loss in multiple time and space scales, and surrounding environment. Over polar areas, the G-TERN will measure sea ice surface elevation (〈;10 cm precision), roughness, and polarimetry aspects at 30-km resolution and 3-days full coverage. G-TERN will implement the interferometric GNSS reflectometry concept, from a single satellite in near-polar orbit with capability for 12 simultaneous observations. Unlike currently orbiting GNSS reflectometry missions, the G-TERN uses the full GNSS available bandwidth to improve its ranging measurements. The lifetime would be 2025-2030 or optimally 2025-2035, covering key stages of the transition toward a nearly ice-free Arctic Ocean in summer. This paper describes the mission objectives, it reviews its measurement techniques, summarizes the suggested implementation, and finally, it estimates the expected performance.

Description: A simplified parallel version of the Soil Moisture and Ocean Salinity (SMOS) Level 2 Ocean Salinity (L2OS) processor is used to assess the optimal configuration of both the SMOS cost function and the corresponding minimization scheme for sea surface salinity (SSS) and wind speed (U10) retrievals. For such a purpose, both realistically simulated brightness temperatures (TBs) and a post-launch derived semi-empirical forward model are used. This study confirms the effectiveness of the L2OS configuration for SSS retrieval and provides the optimal configuration for U10 retrieval. A revised cost function formulation, where the observational term has more weight than the background one, is further assessed, which leads to smaller retrieval errors.

Description: Published

Description: 855-873

Description: 4A. Oceanografia e clima

Description: JCR Journal

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.