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Ocean Science An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/os-2018-113
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/os-2018-113
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 22 Oct 2018

Research article | 22 Oct 2018

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Ocean Science (OS).

Data assimilation of SMOS observations into the Mercator Ocean operational system: focus on the Nino 2015 event

Benoît Tranchant1, Elisabeth Remy2, Eric Greiner1, and Olivier Legalloudec2 Benoît Tranchant et al.
  • 1Collecte Localisation Satellites, Ramonville Saint-Agne, 31520, France
  • 2Mercator-Océan, Ramonville Saint-Agne, 31520, France

Abstract. Monitoring Sea Surface Salinity (SSS) is important for understanding and forecasting the ocean circulation. It is even crucial in the context of the acceleration of the water cycle. Until recently, SSS was one of the less observed essential ocean variables. Only sparse in situ observations, most often closer to 5 meters deep than the surface, were available to estimate the SSS. The recent satellite missions of ESA's SMOS, NASA's Aquarius, and now SMAP have made possible for the first time to measure SSS from space.

The SSS drivers can be quite different than the temperature ones. The model SSS can suffer from significant errors coming not only from the ocean dynamical model but also the atmospheric precipitation and evaporation as well as ice melting and river runoff. Satellite SSS can bring a valuable additional constraint to control the model salinity.

In the framework of the SMOS Nino 2015 ESA project (https://www.godae-oceanview.org/projects/smos-nino15/), the impact of satellite SSS data assimilation is assessed with the Met Office and Mercator Ocean global ocean analysis and forecasting systems with a focus on the Tropical Pacific region. This article presents the analysis of an Observing System Experiment (OSE) conducted with the 1/4° resolution Mercator Ocean analysis and forecasting system. SSS data assimilation constrains the model SSS to be closer to the observations in a coherent way with the other data sets already routinely assimilated in an operational context. Globally, the SMOS SSS assimilation has a positive impact in salinity over the top 30 meters. Comparisons to independent data sets show a small but positive impact. The sea surface height (SSH) has also been impacted by implying a reinforcement of TIWs during the El-Niño 2015/16 event. Finally, this study helped us to progress in the understanding of the biases and errors that can degrade the SMOS SSS performance.

Benoît Tranchant et al.
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This work deals with the use of Sea Surface Salinity measurements from space in the context of operational oceanography. The salinity plays an important role in the ocean-atmosphere coupling, especially when a El-Nino event occurs in the Tropical Pacific. However, it is still difficult to use such data in ocean models due to a large extent to large scales biases. This study shows that with recent data treatment improvements it is possible to have positive impact on weekly forecast.
This work deals with the use of Sea Surface Salinity measurements from space in the context of...
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