Preprints
https://doi.org/10.5194/egusphere-2022-1399
https://doi.org/10.5194/egusphere-2022-1399
20 Dec 2022
 | 20 Dec 2022

Producing SWOT measurements with a multiscale data assimilation system during the prelaunch field campaign

Zhijin Li, Matthew R. Archer, Jinbo Wang, and Lee-Lueng Fu

Abstract. A data assimilation system for a high-resolution model has been developed to address the opportunities and challenges posed by the upcoming Surface Water and Ocean Topography (SWOT) satellite mission. This developed system is based on a three-dimensional variational data assimilation scheme (3DVAR), which is computationally highly efficient and thus can be applied to a very high-resolution model. A crucial consideration of the system is to use a multiscale data assimilation approach (MSDA) to first assimilate routinely available observations, including conventional satellite altimetry, sea surface temperature (SST) and salinity (SSS), and temperature/salinity vertical profiles, to constrain large scales and large mesoscales. High-resolution (dense) observations and future SWOT measurements can then be effectively and seamlessly assimilated to constrain the smaller scales. The 3DVAR is extended to assimilate observations over a time interval, which specifically enhances the efficacy of the assimilation of satellite along-track altimetry observations, which are limited by large repeat time intervals. Using this system, a reanalysis dataset was produced for the SWOT pre-launch field campaign that took place in the California Current System from September through December, 2019. An evaluation of this system with assimilated and withheld data demonstrates its ability to effectively utilize both routine and campaign observations to produce sea surface heights with the accuracy close to that required by SWOT. These results suggest a promising avenue for data assimilation development in the SWOT altimetry era, which will need the capability of jointly assimilating existing routine observations with SWOT measurements to resolve small-scale ocean processes.

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Zhijin Li, Matthew R. Archer, Jinbo Wang, and Lee-Lueng Fu

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2022-1399', Anonymous Referee #1, 17 Feb 2023
    • AC1: 'Reply on RC1', Zhijin Li, 09 Apr 2023
    • AC3: 'Reply on RC1', Zhijin Li, 09 Apr 2023
    • AC4: 'Reply on RC1', Zhijin Li, 09 Apr 2023
  • RC2: 'Comment on egusphere-2022-1399', Anonymous Referee #2, 17 Mar 2023
    • AC2: 'Reply on RC2', Zhijin Li, 09 Apr 2023

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2022-1399', Anonymous Referee #1, 17 Feb 2023
    • AC1: 'Reply on RC1', Zhijin Li, 09 Apr 2023
    • AC3: 'Reply on RC1', Zhijin Li, 09 Apr 2023
    • AC4: 'Reply on RC1', Zhijin Li, 09 Apr 2023
  • RC2: 'Comment on egusphere-2022-1399', Anonymous Referee #2, 17 Mar 2023
    • AC2: 'Reply on RC2', Zhijin Li, 09 Apr 2023
Zhijin Li, Matthew R. Archer, Jinbo Wang, and Lee-Lueng Fu
Zhijin Li, Matthew R. Archer, Jinbo Wang, and Lee-Lueng Fu

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Short summary
The Surface Water and Ocean Topography (SWOT) satellite mission will carry a new-generation altimeter to measure sea surface height in two-dimensions at unprecedented spatial resolution. An integration of SWOT measurements into an oceanic numerical model will improve our oceanic prediction in spatial resolution and accuracy. It has been demonstrated that the methodology used is ready to integrate SWOT measurements into the model, and the result may be used to interpret SWOT measurements.