Abstract's details
Joint estimation of balanced motions and internal tides from future wide-swath altimetry
CoAuthors
Event: 2022 Ocean Surface Topography Science Team Meeting
Session: Science III: Mesoscale and sub-mesoscale oceanography
Presentation type: Type Oral
Contribution: PDF file
Abstract:
For more than 25 years, altimetry has allowed the study of near-global sea surface height (SSH) at scales longer than 150 km and drastically transformed our understanding of mesoscale processes in the oceans. But the scales resolved by nadir (along-track) altimetry are limited by the 100-300 km spacing between one dimensional satellite ground tracks. Even by merging several nadir measurements, the space time resolution of the resulting 2D SSH maps does not allow to conveniently characterize and study small mesoscale (<150km) motions. Still, recent studies, based on numerical models, have highlighted the impacts of short-mesoscale and submesoscale processes on ocean dynamics.
The Surface Water and Ocean Topography (SWOT) mission is expected to provide Sea Surface Height (SSH) measurements resolving scales of a few tens of kilometers. Over a large fraction of the globe, the SSH signal at scales <100km is essentially a superposition of a component due to balanced motions (BMs) and another component due to internal tides (ITs). These two classes of motions are associated with different dynamical processes and therefore impact the ocean kinetic energy budget differently. To make the best use of the future SWOT SSH observations, BMs and ITs will need to be separated. However, the main difficulty to separate the signals lies in the strong interactions between BMs and ITs, generating non-stationary ITs that cannot be estimated by conventional statistical methods.
In that context, we introduce a dynamical method that process altimetric observations to simultaneously estimate the SSH signatures of BMs and ITs on two-dimensional regular grids. The method, based on original data assimilation techniques, uses simple dynamical model, each specific to the mapping of one component: a quasi-geostrophic model for BMs, and a linear shallow-water model for ITs. A particular effort is made to perform the inversions in well-chosen reduced-order basis.
The algorithm is tested with Observation System Simulation Experiments (OSSE), where the true state of the ocean is provided by the MITgcm global LLC4320 simulation. We focus on a realistic observational scenario in the California Current System during the SWOT’s fast sampling phase. The proposed algorithm is able to map and separate a large amount of the variance of BMs and ITs. Importantly, in addition to the reconstruction of stationary ITs, the algorithm estimates the amplitude and phase of nonstationary ITs, which is very encouraging for the process of future SWOT data.
The Surface Water and Ocean Topography (SWOT) mission is expected to provide Sea Surface Height (SSH) measurements resolving scales of a few tens of kilometers. Over a large fraction of the globe, the SSH signal at scales <100km is essentially a superposition of a component due to balanced motions (BMs) and another component due to internal tides (ITs). These two classes of motions are associated with different dynamical processes and therefore impact the ocean kinetic energy budget differently. To make the best use of the future SWOT SSH observations, BMs and ITs will need to be separated. However, the main difficulty to separate the signals lies in the strong interactions between BMs and ITs, generating non-stationary ITs that cannot be estimated by conventional statistical methods.
In that context, we introduce a dynamical method that process altimetric observations to simultaneously estimate the SSH signatures of BMs and ITs on two-dimensional regular grids. The method, based on original data assimilation techniques, uses simple dynamical model, each specific to the mapping of one component: a quasi-geostrophic model for BMs, and a linear shallow-water model for ITs. A particular effort is made to perform the inversions in well-chosen reduced-order basis.
The algorithm is tested with Observation System Simulation Experiments (OSSE), where the true state of the ocean is provided by the MITgcm global LLC4320 simulation. We focus on a realistic observational scenario in the California Current System during the SWOT’s fast sampling phase. The proposed algorithm is able to map and separate a large amount of the variance of BMs and ITs. Importantly, in addition to the reconstruction of stationary ITs, the algorithm estimates the amplitude and phase of nonstationary ITs, which is very encouraging for the process of future SWOT data.