Assimilation of sea surface salinities from SMOS in an Arctic coupled ocean and sea ice reanalysis

• Published in: Ocean Science
• Main Authors: Xie, Jiping, Raj, Roshin P., Bertino, Laurent, Martínez, Justino, Gabarró, Carolina, Catany, Rafael
• Other Authors: European Space Agency, Norwegian Research Council, Agencia Estatal de Investigación (España)
• Format: Article in Journal/Newspaper
• Language: English
• Published: European Geosciences Union 2023
• Subjects: Arctic; Arctic Ocean; Sea ice
• Online Access: http://hdl.handle.net/10261/304509; https://doi.org/10.5194/os-19-269-2023

Special issue Data assimilation techniques and applications in coastal and open seas.--19 pages, 11 figures, 2 tables.-- Data availability: All the in situ observations for validation in this study are open access, as indicated in Sect. 3. The model results from Exp0 are the released TOPAZ reanalysis, which is freely available from CMEMS (http://marine.copernicus.eu, last access: November 2021) or https://doi.org/10.11582/2022.00043 (Xie, 2022). The other assimilation experiments can be provided freely upon personal communication 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 This research has been supported by the European Space Agency Arctic+Salinity project (AO/1-9158/18/I-BG) and the Norges Forskningsråd (grant no. 325241) With the institutional support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S) Peer ...