Abstract
The aim of this study is to assess the capacity of the Surface Water Ocean Topography (SWOT) satellite to resolve fine scale oceanic surface features in the western Mediterranean. Using as input the Sea Surface Height (SSH) fields from a high-resolution Ocean General Circulation Model (OGCM), the SWOT Simulator for Ocean Science generates SWOT-like outputs along a swath and the nadir following the orbit ground tracks. Given the characteristic temporal and spatial scales of fine scale features in the region, we examine temporal and spatial resolution of the SWOT outputs by comparing them with the original model data which are interpolated onto the SWOT grid. To further assess the satellite’s performance, we derive the absolute geostrophic velocity and relative vorticity. We find that instrument noise and geophysical error mask the whole signal of the pseudo-SWOT derived dynamical variables. We therefore address the impact of removal of satellite noise from the pseudo-SWOT data using a Laplacian diffusion filter, and then focus on the spatial scales that are resolved within a swath after this filtering. To investigate sensitivity to different filtering parameters, we calculate spatial spectra and root mean square errors. Our numerical experiments show that noise patterns dominate the spectral content of the pseudo-SWOT fields at wavelengths below 60 km. Application of the Laplacian diffusion filter allows recovery of the spectral signature within a swath down to the 40–60 km wavelength range. Consequently, with the help of this filter, we are able to improve the observation of fine scale oceanic features in pseudo-SWOT data, and in the estimation of associated derived variables such as velocity and vorticity.
Highlights
The Surface Water and Ocean Topography (SWOT) satellite mission is a joint mission by the National Aeronautics and Space Administration (NASA) and the Centre National d’Études Spatiales (CNES), with contributions from the UK and Canadian Space Agencies [1]
There are periods of time with a higher temporal sampling. This is due to a longer revisit time so that SWOT fulfills its hydrological objectives by providing coverage of the bulk of the global land surface [7]
If we look at the signal to noise ratio (SNR), we find that below 50 km wavelength the energy of the noise is significant with respect to that of the signal (SNR values below 15 dB at wavelengths smaller than 47.6 km, i.e., the energy of the noise accounts for more than 15% of the energy of the signal for these scales)
Summary
The Surface Water and Ocean Topography (SWOT) satellite mission is a joint mission by the National Aeronautics and Space Administration (NASA) and the Centre National d’Études Spatiales (CNES), with contributions from the UK and Canadian Space Agencies [1]. The satellite’s launch is planned for 2021 [2] It will provide water elevation maps for oceanographic and hydrological purposes [3,4]. SWOT will have a 21-day repeat cycle and the revisit time will vary from approximately 10 days at the equator to two days at the poles [5,6] This implies temporal variability in spatial coverage as the number of observations per repeat cycle will increase with latitude. There are periods of time with a higher temporal sampling This is due to a longer revisit time so that SWOT fulfills its hydrological objectives by providing coverage of the bulk of the global land surface [7]. As SWOT aims for global coverage, i.e., high spatial resolution, we lose in temporal resolution (SWOT’s repeat cycle will be longer than, for example, the 10-day repeat cycle of the Jason altimeter satellites [8])
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