Improved Multifractal Fusion Method to Blend SMOS Sea Surface Salinity Based on Semiparametric Weight Function

Abstract

AbstractThe multifractal fusion method has proved to be an effective algorithm to mitigate the noise of the sea surface salinity (SSS) of Soil Moisture Ocean Salinity (SMOS) mission. However, the traditional nonparametric weight function used in this method is unable to fully capture the dynamic evolution of the oceanic environment. Considering the multiscale, nonuniform, anisotropic, and flow-dependent nature of the ocean, a prototype with the so-called flexible circle (FLC) weight function or flexible ellipse (FLE) weight function with a set of predefined parameters is proposed in this paper. The improved weight functions could draw dynamic information from the sea surface temperature, Rossby radius of deformation, and surface geostrophic flow to improve the quality of the remotely sensed SSS. The validation against the in situ data indicates that the improved weight functions perform better than the traditional one with a reduced root-mean-square (RMS) and standard deviation (STD) of the differences with respect to EN 4.2.0 profiles (from 0.50 and 0.46 to 0.42 and 0.38 for FLC and 0.39 and 0.36 for FLE in the global ocean). In particular, the FLE scheme could highlight the variation of the strong currents without affecting the computational efficiency. Furthermore, this paper discusses the influences of the error distribution on the fusion results and underlines the importance of error-based adaptions for further improvements.