Abstract's details
Use of new baroclinic tide models to improve the correction of internal tides in SWOT data
Event: 2025 SWOT Science Team Meeting
Session: Oceanography: Tides and Inertia-Gravity Waves
Presentation type: Poster
Altimeter measurements are corrected from several geophysical parameters in order to isolate the oceanic variability and the tide correction is one of the most critical. Global ocean and loading tide models GOT and FES are used in present altimeter GDRs to remove the barotropic tide component, and the internal tides signatures can also be partly corrected with specific models since a few years.
Internal tides (IT) have a surface signature of several cm with wavelengths about 50-250 km for the first mode and smaller for higher modes. With the new higher resolution missions giving access to ocean small scale variability, the correction of these small-scale signals becomes mandatory for many applications.
As demonstrated in previous studies, using global IT models to correct the stationary IT signal allows a significant altimeter variance reduction on ocean regions where internal tides are generating and propagating (Zaron, 2019; Ubelmann, 2021, Carrere et al. 2021), although non-stationary IT signal due to seasonal variability of the ocean conditions and the interactions with mesoscales and other ocean waves is more difficult to estimate.
The new Surface Water and Ocean Topography (SWOT) altimetry mission launched at the end of 2022 is an opportunity to access ocean variability at a scale extending to 15-30 km and to better understand high-frequency dynamic processes such as the internal tide (IT). The analysis of SWOT 2-dimensions observations during the Calval (1-day orbit) has allowed producing a new specific IT solution for SWOT in the Amazon area (Tchilibou et al 2025). The present study proposes an evaluation of some new global IT models for the removal of the stationary IT variability in SWOT and nadir altimeter measurements. We have studied several new IT models: HRET14 and HRET22 (Zaron 2024), ZHAO30yr (Zhao 2025) and MIOST-IT24 (Tchilibou et al. 2025). Results are presented here and they indicate an improvement of the recent models which permit reducing further the residual sea level variance on ocean regions impacted by IT.
Internal tides (IT) have a surface signature of several cm with wavelengths about 50-250 km for the first mode and smaller for higher modes. With the new higher resolution missions giving access to ocean small scale variability, the correction of these small-scale signals becomes mandatory for many applications.
As demonstrated in previous studies, using global IT models to correct the stationary IT signal allows a significant altimeter variance reduction on ocean regions where internal tides are generating and propagating (Zaron, 2019; Ubelmann, 2021, Carrere et al. 2021), although non-stationary IT signal due to seasonal variability of the ocean conditions and the interactions with mesoscales and other ocean waves is more difficult to estimate.
The new Surface Water and Ocean Topography (SWOT) altimetry mission launched at the end of 2022 is an opportunity to access ocean variability at a scale extending to 15-30 km and to better understand high-frequency dynamic processes such as the internal tide (IT). The analysis of SWOT 2-dimensions observations during the Calval (1-day orbit) has allowed producing a new specific IT solution for SWOT in the Amazon area (Tchilibou et al 2025). The present study proposes an evaluation of some new global IT models for the removal of the stationary IT variability in SWOT and nadir altimeter measurements. We have studied several new IT models: HRET14 and HRET22 (Zaron 2024), ZHAO30yr (Zhao 2025) and MIOST-IT24 (Tchilibou et al. 2025). Results are presented here and they indicate an improvement of the recent models which permit reducing further the residual sea level variance on ocean regions impacted by IT.
Contribution: ST2025OS5-Use_of_new_baroclinic_tide_models_to_improve_the_correction_of_internal_tides_in_SWOT_data.pdf (pdf, 624 ko)
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