# Ocean Currents Reconstruction from a Combination of
## 1 Introduction
Within the Copernicus Marine Environment Monitoring Service (CMEMS), this is done through an optimal interpolation method that is able to efficiently account for along-track correlated errors after adjusting inter-sensor biases [3]. Nevertheless, only the largest mesoscale circulation features can be accurately resolved with this approach. Nowadays, the highest effective spatial-temporal resolutions (i.e., that almost fully resolved scales) of the altimetry gridded products attain around \(\simeq\)100 km and \(\simeq\)10 days, respectively [3; 17; 18; 19; 20; 21]. These resolutions are not satisfying for capturing the variety of processes acting at the ocean surface, whose spatial-temporal scales span over several orders of magnitude (eventually reaching also a few meters and hours, [22] and references therein), with drawbacks for several socio-economic applications in the marine context (e.g., safe navigation, ship routing, and environmental management). The altimeter-derived currents can be improved via several techniques, e.g., developing new algorithms for the 2D mapping of the along-track altimeter measurements based on dynamical assumptions [23; 24] or through the blending of altimeter-derived and in situ measured currents [25]. Relying on past achievements of Piterbarg [26] (PIT09), some studies took advantage of satellite-derived ocean surface tracers data to optimize the altimeter-derived geostrophic currents in both regional and global scale applications [27; 28; 29; 30; 31]. The main idea is that remotely sensed distributions of ocean tracers (as surface temperature, salinity, or chlorophyll-a concentration) are linked to ocean currents' advection, so that improved ocean currents' estimates can be derived by optimally merging high spatio-temporal tracer image sequences with lower resolution altimeter data. Until the present date, the technique has been extensively used to combine the altimeter-derived geostrophic currents and higher resolution satellite SST data. Extracting dynamical information from the satellite SST spatial-temporal derivatives, the altimeter-derived geostrophic currents were improved up to 35% locally, although some degradations with respect to the altimeter system were observed at high latitudes (larger than \(\pm 50^{\circ}\)), mainly because of lower SST product accuracy in those areas. In the present study, relying on the same technique initially developed by [PERSON] et al. [27], we explore the feasibility of using ocean-colour based estimates of the Chl surface as an alternative surface tracer with respect to the SST. Past and recent studies [32; 33] have indeed shown that ocean colour data can provide valuable information on the ocean surface circulation, allowing for tracking mesoscale to submesoscale features. In case of homogeneous SST distributions, ocean colour data can also provide a good alternative to SST in recognizing and tracking surface-intensified circulation features, as shown by [PERSON] et al. [34] in the Gulf of Mexico. Unlike SST, Chl concentration variations in space and time are driven by both biological and physical processes (and their eventual interactions, e.g., [35]), which contribute to its variability over different spatial-temporal scales with respect to the sea temperature. As an example, phytoplankton growth is clearly modulated by light and nutrient availability and also limited by grazing, so that combined physical/biological processes may significantly affect its concentration in the surface layer (e.g., turbulent mixing, photo-adaptation, nutrient upwelling, remineralisation). Here, we run an Observing System Simulation Experiment (OSSE) to test the applicability of the PIT09 method (optimal reconstruction hereinafter) in preparation of the eventual future applications to satellite-derived data. We rely on the CMEMS physical and biogeochemical regional forecast models for the Mediterranean Sea (detailed in Section 2).