Data Assimilation Development in Support of the SWOT Satellite Mission

Abstract:

A data assimilation system for a high-resolution model with tides has been developed in support of the Surface Water Ocean Topography (SWOT) satellite mission. This system is being used to conduct (1) Observing System Simulation Experiments (OSSEs) for optimizing the design of the post-launch field campaign, (2) reanalysis as a ground truth for SWOT calibration and validation (Cal/Val), and (3) assimilation of the future SWOT observations. A multiscale data assimilation (MSDA) algorithm is implemented and integrated with a four dimensional formulation. In this MSDA formulation, the routinely available observations, including satellite altimetry, sea surface temperature (SST) and salinity (SSS) and temperature/salinity vertical profiles, are assimilated to constrain the large-scale and mesoscale fields to provide an accurate background for assimilation of high-resolution and dense observations from in-situ CalVal system and/or SWOT observations to constrain the smaller scales. This system has produced a reanalysis for the SWOT pre-launch field campaign that took place at the SWOT Cal/Val site in the California Current System, from September–December 2019. The reanalysis dataset has been evaluated against assimilated and independent observations, and demonstrates that this system is capable of producing an ocean state estimate that meets baseline requirements for the SWOT CalVal.