Baptiste Mourre (Instituto Mediterráneo de Estudios Avanzados (IMEDEA (CSIC-UIB)), Esporles, Spain, Spain); Nikolaos Zarokanellos (Balearic Islands Coastal Observing and Forecasting System (SOCIB), Palma, Spain, Spain); Emma Reyes (Balearic Islands Coastal Observing and Forecasting System (SOCIB), Palma, Spain, Spain); Joaquín Tintoré (1) Balearic Islands Coastal Observing and Forecasting System (SOCIB), Palma, Spain 2) Instituto Mediterráneo de Estudios Avanzados (IMEDEA (CSIC-UIB)), Esporles, Spain, Spain)

Traditionally, ocean data assimilation (DA) systems have been constrained to broader, mesoscale structures due to limited observational resolution. However, the advent of very high-resolution satellite missions, such as Surface Water Ocean Topography (SWOT) and Sentinel-6A, open the door to enable the assimilation of critically important smaller-scale features. This abstract details recent advancements in Western Mediterranean Operational Forecasting (WMOP) DA component, including the integration of Sentinel-6A Sea Level Anomaly (SLA) altimeter data. WMOP, based on the ROMS numerical model, uses an Ensemble Optimal Interpolation (EnOI) DA scheme to incorporate a diverse range of multi-platform observations, which was initially designed to constrain the mesoscale fields. Its operational configuration features a 2 km horizontal resolution and 32 sigma vertical layers, delivering 3-hourly and daily forecasts. To investigate the impact of assimilating smaller-scale features on ocean state estimation, we conducted an Observing System Experiment (OSE) in the Balearic Sea in the Western Mediterranean. We performed five distinct DA simulations using: (i) a free control run without data assimilation; (ii) a run assimilating a comprehensive suite of conventional observations including satellite SLA, sea surface temperature (SST), high-frequency radar surface currents (HFR), and temperature/salinity (T/S) profiles from Argo floats and moorings; (iii) a run specifically 1 Hz (~7 km) SLA; (iv) a run focusing on assimilation of 5 Hz (~1km) and 20 Hz (~0.3km) SLA observations; and (v) a run implementing a nested, multi-scale assimilation system combining both mesoscale and submesoscale SLA data. The performance of each setup focused on the surface and subsurface was evaluated by assessing its ability to represent small-scale features using independent high-resolution SWOT and in-situ observations from gliders. Preliminary results from the assimilation experiments described in (ii) indicate that incorporating high-resolution SLA data into WMOP does not yet significantly enhance submesoscale forecast skill. However, experiments currently underway, specifically employing a multi-scale assimilation system (Experiment v) will be analyzed to evaluate their capacity to reduce SLA variance errors at smaller spatial scales and to enhance model performance. Recent publications highlight the transformative potential of high-resolution altimetry in coastal ocean forecasting, offering critical insights for future developments aimed at improving the accuracy of submesoscale predictions.

FOCCUS is funded by the European Union (Grant Agreement No. 101133911). Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the European Health and Digital Executive Agency (HaDEA). Neither the European Union nor the granting authority can be held responsible for them.