Assessing the Impact of the Assimilation of SWOT Observations in a Global High-Resolution Analysis and Forecasting System Part 1: Methods

Type Article
Date 2021-07
Language English
Author(s) Benkiran Mounir1, Ruggiero Giovanni1, Greiner Eric2, Le Traon Pierre-Yves1, 3, Remy Elisabeth1, Lellouche Jean-Michel1, Bourdallé-Badie Romain1, Drillet Yann1, Tchonang Babette1
Affiliation(s) 1 : Mercator Ocean International, Ramonville-Saint-Agne, France
2 : Collecte Localisation Satellites, Ramonville-Saint-Agne, France
3 : Laboratoire Géodynamique et Enregistrements Sédimentaires, Institut Français de Recherche pour l’Exploitation de la Mer, Plouzané, France
Source Frontiers In Marine Science (2296-7745) (Frontiers Media), 2021-07 , Vol. 8 , P. 691955 (19p.)
DOI 10.3389/fmars.2021.691955
WOS© Times Cited 3
Keyword(s) data assimilation, satellite altimetry, OSSE (Observing System Simulation Experiment), SWOT (Surface Water Ocean Topography), forecasting system
Abstract

The future Surface Water Ocean Topography (SWOT) mission due to be launched in 2022 will extend the capability of existing nadir altimeters to enable two-dimensional mapping at a much higher effective resolution. A significant challenge will be to assimilate this kind of data in high-resolution models. In this context, Observing System Simulation Experiments (OSSEs) have been performed to assess the impact of SWOT on the Mercator Ocean and Copernicus Marine Environment Monitoring Service (CMEMS) global, high-resolution analysis and forecasting system. This paper focusses on the design of these OSSEs, in terms of simulated observations and assimilation systems (ocean model and data assimilation schemes). The main results are discussed in a companion paper. Two main updates of the current Mercator Ocean data assimilation scheme have been made to improve the assimilation of information from SWOT data. The first one is related to a different parametrisation of the model error covariance, and the second to the use of a four-dimensional (4D) version of the data assimilation scheme. These improvements are described in detail and their contribution is quantified. The Nature Run (NR) used to represent the “truth ocean” is validated by comparing it with altimeter observations, and is then used to simulate pseudo-observations required for the OSSEs. Finally, the design of the OSSEs is evaluated by ensuring that the differences between the assimilation system and the NR are statistically consistent with the misfits between real ocean observations and real-time operational systems.

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Supplementary Figure 1 | Spatial distribution of Standard deviation of Sea Level Anomaly (SLA) error: (A) G12, (B) OSSE system, and (C) Scatter diagram between G12 and OSSE Standard deviation of ... 2 MB Open access
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How to cite 

Benkiran Mounir, Ruggiero Giovanni, Greiner Eric, Le Traon Pierre-Yves, Remy Elisabeth, Lellouche Jean-Michel, Bourdallé-Badie Romain, Drillet Yann, Tchonang Babette (2021). Assessing the Impact of the Assimilation of SWOT Observations in a Global High-Resolution Analysis and Forecasting System Part 1: Methods. Frontiers In Marine Science, 8, 691955 (19p.). Publisher's official version : https://doi.org/10.3389/fmars.2021.691955 , Open Access version : https://archimer.ifremer.fr/doc/00706/81787/