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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 climate. [ABSTRACT FROM AUTHOR]

The hydrography of the Arctic Ocean has experienced profound changes over the last two decades. The sea-ice extent has declined 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 in the Arctic might contribute to better characterizing the freshwater changes in cold regions. That is because ocean salinity and freshwater content are intimately related such that an increase/decrease of one entails a decrease/increase of 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 reanalysis salinity at depth. We estimate the freshwater content from 2011 to 2019 in the Beaufort Gyre and validate 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 above the mixed layer. The improvements are significant, especially in areas close to ice melting. Our research demonstrates how remotely sensed salinity can assist us in better monitoring the changes in the Arctic freshwater content and improving our understanding of a key process that is creating subtle density differences that have the potential to change the global circulation system that regulates Earth's Climate. [ABSTRACT FROM AUTHOR]

In the Arctic, the sea surface salinity (SSS) plays a key role in processes related to water mixing and sea ice. However, the lack of salinity observations causes large uncertainties in Arctic Ocean forecasts and reanalysis. Recently the Soil Moisture and Ocean Salinity (SMOS) satellite mission was used by the Barcelona Expert Centre to develop an Arctic SSS product. In this study, we evaluate the impact of assimilating this data in a coupled ocean–ice data assimilation system. Using the deterministic ensemble Kalman filter from July to December 2016, two assimilation runs respectively assimilated two successive versions of the SMOS SSS product on top of a pre-existing reanalysis run. The runs were validated against independent in situ salinity profiles in the Arctic. The results show that the biases and the root-mean-squared differences (RMSD) of SSS are reduced by 10 % to 50 % depending on the area and highlight the importance of assimilating satellite salinity data. The time series of freshwater content (FWC) further shows that its seasonal cycle can be adjusted by assimilation of the SSS products, which is encouraging of the assimilation of SSS in a long-time reanalysis to better reproduce the Arctic water cycle. [ABSTRACT FROM AUTHOR]

In the Arctic, the sea surface salinity (SSS) plays a key role in processes related to water mixing and sea ice. However, the lack of salinity observations causes large uncertainties in Arctic Ocean forecasts and reanalysis. Recently the Soil Moisture and Ocean Salinity (SMOS) satellite mission was used by the Barcelona Expert Centre to propose an Arctic SSS product. In this study, we evaluate the impact of assimilating this data in a coupled ocean-ice data assimilation system. Using the Ensemble Kalman filter from July to December 2016, two assimilation runs assimilated two successive versions of the SMOS SSS product, on top of a pre-existing reanalysis run. The runs were validated against independent in situ salinity profiles in the Arctic. The results show that the biases and the Root Mean Squared Differences (RMSD) of SSS are reduced by 10% to 50% depending on areas and put the latest product to its advantage. The time series of Freshwater Content (FWC) further show that its seasonal cycle can be adjusted by assimilation of the SSS products, which is encouraging for its use in a long-time reanalysis to monitor the Arctic water cycle. [ABSTRACT FROM AUTHOR]

Measuring 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 (0.3Kpsu-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. 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 10.20350/digitalCSIC/12620. 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 monitoring. [ABSTRACT FROM AUTHOR]

Measuring 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), 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), making the retrieval of the SSS in the cold waters even more challenging. Due to this limitation, 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., 2020) . The product consists of 9-day 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/) with the DOI number: 10.20350/digitalCSIC/12620. 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 discharges monitoring. [ABSTRACT FROM AUTHOR]

In the Arctic, the sea surface salinity (SSS) plays a key role in processes related to water mixing and sea ice. However, the lack of salinity observations causes large uncertainties in Arctic Ocean forecasts and reanalysis. Recently the Soil Moisture and Ocean Salinity (SMOS) satellite mission was used by the Barcelona Expert Centre to propose an Arctic SSS product. In this study, we evaluate the impact of assimilating this data in a coupled ocean-ice data assimilation system. Using the Ensemble Kalman filter from July to December 2016, two assimilation runs assimilated two successive versions of the SMOS SSS product, on top of a pre-existing reanalysis run. The runs were validated against independent in situ salinity profiles in the Arctic. The results show that the biases and the Root Mean Squared Differences (RMSD) of SSS are reduced by 10% to 50% depending on areas and put the latest product to its advantage. The time series of Freshwater Content (FWC) further show that its seasonal cycle can be adjusted by assimilation of the SSS products, which is encouraging for its use in a long-time reanalysis to monitor the Arctic water cycle. [ABSTRACT FROM AUTHOR]

Recently two gridded sea surface salinity (SSS) products that cover the Arctic Ocean have been derived from the European Space Agency (ESA)'s Soil Moisture and Ocean Salinity (SMOS) mission: one developed by the Barcelona Expert Centre (BEC) and the other developed by the Ocean Salinity Expertise Center of the Centre Aval de Traitement des Données SMOS at IFREMER (The French Research Institute for Exploitation of the Sea) (CEC). The uncertainties of these two SSS products are quantified during the period of 2011–2013 against other SSS products: one data assimilative regional reanalysis; one data-driven reprocessing in the framework of the Copernicus Marine Environment Monitoring Services (CMEMS); two climatologies – the 2013 World Ocean Atlas (WOA) and the Polar science center Hydrographic Climatology (PHC); and in situ datasets, both assimilated and independent. The CMEMS reanalysis comes from the TOPAZ4 system, which assimilates a large set of ocean and sea-ice observations using an ensemble Kalman filter (EnKF). Another CMEMS product is the Multi-OBservations reprocessing (MOB), a multivariate objective analysis combining in situ data with satellite SSS. The monthly root mean squared deviations (RMSD) of both SMOS products, compared to the TOPAZ4 reanalysis, reach 1.5 psu in the Arctic summer, while in the winter months the BEC SSS is closer to TOPAZ4 with a deviation of 0.5 psu. The comparison of CEC satellite SSS against in situ data shows Atlantic Water that is too fresh in the Barents Sea, the Nordic Seas, and in the northern North Atlantic Ocean, consistent with the abnormally fresh deviations from TOPAZ4. When compared to independent in situ data in the Beaufort Sea, the BEC product shows the smallest bias (< 0.1 psu) in summer and the smallest RMSD (1.8 psu). The results also show that all six SSS products share a common challenge: representing freshwater masses (< 24 psu) in the central Arctic. Along the Norwegian coast and at the southwestern coast of Greenland, the BEC SSS shows smaller errors than TOPAZ4 and indicates the potential value of assimilating the satellite-derived salinity in this system. [ABSTRACT FROM AUTHOR]