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An Observing System Simulation Experiment for Ocean State Estimation to Assess the Performance of the SWOT Mission: Part 1—A Twin Experiment
Author(s) -
Li Zhijin,
Wang Jinbo,
Fu LeeLueng
Publication year - 2019
Publication title -
journal of geophysical research: oceans
Language(s) - English
Resource type - Journals
eISSN - 2169-9291
pISSN - 2169-9275
DOI - 10.1029/2018jc014869
Subject(s) - swot analysis , sea surface height , remote sensing , sea surface temperature , environmental science , data assimilation , ocean surface topography , ocean observations , meteorology , satellite , sea state , geology , climatology , geography , engineering , aerospace engineering , marketing , business
The Surface Water Ocean Topography (SWOT) satellite mission is planned for launch in 2021. It will use the technique of radar interferometry to measure sea surface height over a 120‐km‐wide swath with a 20‐km gap around the satellite's nadir track. The oceanographic objectives of the mission are to study ocean circulation at scales down to 15 km. To prepare for the evaluation of the mission's performance, we are undertaking a series of studies to explore the efficacy of an assimilative high‐resolution modeling system for estimating the state of the ocean based on independent observations from both spaceborne and in situ measurements. The system is based on the heritage of a multiscale approach to data assimilation by the Regional Ocean Modeling System. Observing System Simulation Experiments were first conducted in the setup of an identical twin experiment to assess the system's performance near the calibration/validation site of SWOT off the coast of California. The system was applied to a nested model domain with 1‐km resolution. Simulated satellite observations of SSH, sea surface temperature, salinity, in situ observations of upper ocean temperature, and salinity by profiling floats and a dedicated notional array of station‐keeping gliders were assimilated by the system. The results indicate that such an observing system can accurately estimate the state of the ocean, and in particular SSH for the evaluation of SWOT performance.