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- W4384656490 abstract "Near Inertial Oscillations (NIOs) are ocean oscillations forced by intermittent winds. They are most energetic at mid-latitudes, particularly in regions of atmospheric storm tracks. Wind-driven, large-scale NIOs are quickly scattered by ocean mesoscale eddies (with sizes ranging from 100 to 400 km), causing a significant portion of the NIO energy to propagate into the ocean interior. This kinetic energy pathway illustrates that the wind energy input to NIO, estimated at 5 TeraWatts, is critical for maintaining deep ocean stratification and thus closing the total kinetic energy budget, as emphasized by numerous modelling studies. However, this wind energy input to NIO remains poorly observed on a global scale. A remote sensing approach, which observes winds and ocean currents co-located in time and space with high resolution, is necessary to capture the intermittent air-sea coupling. The current satellite observations do not meet these requirements. This study assesses the potential of a new satellite mission concept, Ocean DYnamics and Surface Exchange with the Atmosphere (ODYSEA), to recover wind-forced NIOs from co-located winds and currents. To do this, we use an Observation System Simulation Experiment (OSSE) based on hourly observations of ocean surface currents and surface winds from five surface moorings covering latitudes from 15∘ to 50∘. ODYSEA wind and current observations are expected to have a spatial resolution of 10 km with about 12-hour sampling frequency in mid-latitudes. Results show that NIOs can be recovered with high accuracy using the ODYSEA spatial and temporal resolution, only if observations are made in a wide-swath of 1,800 km. A narrower swath (1,000 km) may lead to significant aliasing." @default.
- W4384656490 created "2023-07-19" @default.
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- W4384656490 date "2023-07-18" @default.
- W4384656490 modified "2023-09-23" @default.
- W4384656490 title "Increasing the Observability of Near Inertial Oscillations by a Future ODYSEA Satellite Mission" @default.
- W4384656490 doi "https://doi.org/10.20944/preprints202307.1187.v1" @default.
- W4384656490 hasPublicationYear "2023" @default.
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