**Marta Umbert 1,2,\*, Sebastien Guimbard 3, Joaquim Ballabrera Poy 1,2 and Antonio Turiel 1,2**


Received: 27 February 2020; Accepted: 29 March 2020; Published: 3 April 2020

**Abstract:** The similarity of mesoscale and submesoscale features observed in different ocean scalars indicates that they undergo some common non-linear processes. As a result of quasi-2D turbulence, complicated patterns of filaments, meanders, and eddies are recognized in remote sensing images. A data fusion method used to improve the quality of one ocean variable using another variable as a template is used here as an extrapolation technique to improve the coverage of daily Aqua MODIS Level-3 chlorophyll maps by using MODIS SST maps as a template. The local correspondence of SST and Chl-a multifractal singularities is granted due to the existence of a common cascade process which makes it possible to use SST data to infer Chl-a concentration where data are lacking. The quality of the inference of Level-4 Chl-a maps is assessed by simulating artificial clouds and comparing reconstructed and original data.

**Keywords:** remote sensing; ocean color; data fusion; data merging; physical oceanography; singularity analysis
