A modeling study of the oceanic mesoscale to submesoscale predictability with potential application to future wide-swath altimetry observations

The proposed SWOT mission for wide swath altimetry will offer a new challenge for observing and monitoring the dynamics of the ocean mesoscale down to 20-30km reaching the submesoscale range. However, the small lengthscales are associated with small timescales as well, so the 22-day repeat period of SWOT (necessary to map the entire ocean) may be too long to capture the complete time evolution of all signals. This is an issue not faced by the existing conventional altimetry designed to observe the large-scale variability. The benefits of using numerical models to address the issue are explored in this study. We investigate the capability of numerical models to mitigate the effects of time gaps between observations by using a scale-dependent metric of predictability. Ensemble experiments with uncertainties introduced to the model's initial condition as well as forcing are conducted to evaluate the predictability of the mesoscale to submesoscale processes in the wavelength domain. In the framework of the study, it is demonstrated that high-resolution regional models are able to significantly extend the predictability of small scales to mitigate the impact of observation gaps. In these conditions, the SWOT mission will provide strong constraints for the detection and monitoring of the small scale eddies and fronts.