Contribution of satellite sea surface salinity to the estimation of liquid freshwater content in the Beaufort Sea

13 pages, 7 figures, 2 tables.-- Code availability: Underlying research code can be accessed at https://github.com/martaumbert/Ocean-Science-2024 (De Andrés et al., 2024).-- Data availability: Underlying research data are available at https://doi.org/10.6084/m9.figshare.c.7084813.v1 (Umbert, 2024)The hydrography of the Arctic Ocean has experienced profound changes over the last 2 decades. The sea ice extent has declined by more than 10 % per decade, and its liquid freshwater content has increased mainly due to glaciers and sea ice melting. Further, new satellite retrievals of sea surface salinity (SSS) in the Arctic might contribute to better characterizing the freshwater changes in cold regions. Ocean salinity and freshwater content are intimately related such that an increase (decrease) in one entails a decrease (increase) in the other. In this work, we evaluate the freshwater content in the Beaufort Gyre using surface salinity measurements from the satellite radiometric mission Soil Moisture and Ocean Salinity (SMOS) and TOPAZ4b reanalysis salinity at depth, estimating the freshwater content from 2011 to 2019 and validating the results with in situ measurements. The results highlight the underestimation of the freshwater content using reanalysis data in the Beaufort Sea and a clear improvement in the freshwater content estimation when adding satellite sea surface salinity measurements in the mixed layer. The improvements are significant, with up to a 70 % reduction in bias in areas near the ice melting. Our research demonstrates how remotely sensed salinity can assist us in better monitoring the changes in the Arctic freshwater content and understanding key processes related to salinity variations that cause density differences with potential to influence the global circulation system that regulates Earth's climateThis project was funded by Marie Skłodowska-Curie grant agreement no. 840374. Eva De Andrés is funded by Margarita Salas grant no. UP2021-035 under the NextGenerationEU program and supported by the MCIN/AEI project PID2020-113051RB-C31. We also received funding from the AEI with the ARCTIC-MON project (PID2021-125324OB-I00) and from the ESA Arctic+ Salinity project (AO/1-9158/18/I-BG) and Arctic+ SSS CCN (4000125590/18/I-BG). This research was supported by the European Union's Horizon 2020 research and innovation program under grant agreement no. 101003826 via the project “CRiceS – Climate Relevant interactions and feedbacks: the key role of sea ice and Snow in the polar and global climate system”With the institutional support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S)Peer reviewe

Improved BEC SMOS Arctic Sea Surface Salinity product v3.1

17 pages, 13 figures, 1 table.-- Data availability: The product (Martínez et al., 2019) is freely distributed on the BEC (Barcelona Expert Center) web page (http://bec.icm.csic.es/, last access: 25 January 2022) with the DOI number https://doi.org/10.20350/digitalCSIC/12620 (Martínez et al., 2019) and on the Digital CSIC server: https://digital.csic.es/handle/10261/219679 (last access: 25 January 2022). Data can be downloaded from the FTP service: http://bec.icm.csic.es/bec-ftp-service/ (last access: 25 January 2022). The maps are distributed in the standard grid EASE-Grid 2.0, which has a spatial resolution of 25 km. In addition to the product validated in this work (L3 with temporal resolution of 9 d), L3 products having a temporal resolution of 3 and 18 d and the L2 product are available. These Arctic SSS products cover the period from 2011 to 2019.-- This work represents a contribution to the CSIC Thematic Interdisciplinary Platform PTI Teledetect and PolarCSIC. Argo data were collected and made freely available by the International Argo program and the national programs that contribute to it (https://argo.ucsd.edu, https://www.ocean-ops.org, last access: 25 January 2022). The Argo program is part of the Global Ocean Observing SystemMeasuring salinity from space is challenging since the sensitivity of the brightness temperature (TB) to sea surface salinity (SSS) is low (about 0.5 K psu−1), while the SSS range in the open ocean is narrow (about 5 psu, if river discharge areas are not considered). This translates into a high accuracy requirement of the radiometer (about 2–3 K). Moreover, the sensitivity of the TB to SSS at cold waters is even lower (0.3 K psu−1), making the retrieval of the SSS in the cold waters even more challenging. Due to this limitation, the ESA launched a specific initiative in 2019, the Arctic+Salinity project (AO/1-9158/18/I-BG), to produce an enhanced Arctic SSS product with better quality and resolution than the available products. This paper presents the methodologies used to produce the new enhanced Arctic SMOS SSS product (Martínez et al., 2019) . The product consists of 9 d averaged maps in an EASE 2.0 grid of 25 km. The product is freely distributed from the Barcelona Expert Center (BEC, http://bec.icm.csic.es/, last access: 25 January 2022) with the DOI number https://doi.org/10.20350/digitalCSIC/12620 (Martínez et al., 2019). The major change in this new product is its improvement of the effective spatial resolution that permits better monitoring of the mesoscale structures (larger than 50 km), which benefits the river discharge monitoringThis work has been carried out as part of the ESA Arctic+Salinity project (AO/1-9158/18/I-BG), which permitted the production of the database, and the Ministry of Economy and Competitiveness, Spain, through the National R&D Plan under L-BAND project ESP2017-89463-C3-1-R. [...] With the funding support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S), of the Spanish Research Agency (AEI)Peer reviewe

Results analysis and validation - D5.3

This deliverable describes the validation processes followed to assess the performance of the algorithms and protocols for the operator governed opportunistic networking as defined in the OneFIT Project. Therefore, this document includes the description of the set-up of the different validation platforms, the design of the test plans for each one of them, and the analysis of the results obtained from the tests. A per-scenario approach rather than a per-platform approach has been followed, so an additional analysis has been performed, gathering the results related to each scenario, in order to validate the premises stated to each one of them. The OneFIT concept has been therefore validated for all foreseen business scenarios