A neural network to retrieve the mesoscale instantaneous latent heat flux over oceans from SSM/I observations

The turbulent latent and sensible heat fluxes are necessary to study heat budget of the upper ocean or initialize ocean general circulation models. In order to retrieve the latent heat flux from satellite observations authors mostly use a bulk approximation of the flux whose parameters are derived from different instrument. In this paper, an approach based on artificial neural networks is proposed and compared to the bulk method on a global data set and 3 local data sets.