An assessment of the data assimilation system developed for the SWOT satellite mission

Matthew Archer (JPL, United States)

CoAuthors

Matthew Archer (JPL, United States); Zhijin Li (JPL, United States); Jinbo Wang (JPL, United States); Lee-Lueng Fu (JPL, United States)

Event: 2020 Ocean Surface Topography Science Team Meeting (virtual)

Session: Science III: Mesoscale and sub-mesoscale oceanography

Presentation type: Type Forum

When the Surface Water and Ocean Topography (SWOT) satellite launches in 2022, an in-situ field campaign is planned to reconstruct the ground truth for instrument calibration and validation (CalVal). It is demonstrably difficult to capture the sea surface height (SSH) features that are the focus of SWOT, with both short temporal (< 20 days) and spatial scales (15 – 150 km). Therefore, a critical component of the SWOT CalVal will be a multi-scale data assimilation (DA) system coupled to a primitive equation numerical model that can reconstruct: (1) the 2D sea surface height over the SWOT swaths, and (2) the 3D dynamical (velocity) fields. Here we present a strategic evaluation of the DA system that demonstrates its performance based on independent in-situ observations taken during the 2019-2020 pre-launch field campaign.
 
Matthew Archer
JPL
United States
matthew.robert.archer@gmail.com