Formulation and demonstration of an extended-3DVAR multi-scale data assimilation system for the SWOT altimetry era

Abstract. A state-of-the-art 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. A new ‘extended’ three-dimensional variational data assimilation scheme (extended-3DVAR) is formulated to assimilate observations over a time interval, and integrated using a multi-scale approach (hereafter MSDA). The new MSDA scheme specifically enhances the efficacy of the assimilation of satellite along-track altimetry observations, which are limited by large repeat time intervals. This developed system is computationally highly efficient, and thus can be applied to a very high-resolution model. A crucial consideration of the system is first to assimilate routinely available observations, including satellite altimetry, sea surface temperature (SST) 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. 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. These results suggest a promising avenue for data assimilation development in the SWOT altimetry era, which will require the capability to efficiently assimilate large-volume datasets resolving small-scale ocean processes.