Satellite remote sensing has emerged as an essential and necessary observing system to acquire global information about the state of the ocean. Complemented with in situ observing networks, ultimate goals are to to make accurate estimates of selected key sets of geophysical variables, with the intention of either making operational predictions across time and spatial boundaries, or advancing fundamental knowledge through development of empirical relationships and theoretical models.
Challenges appear as unlimited as the variety of upper ocean dynamics and boundary layer meteorological conditions with their broad range of spatial and temporal scales across the globe.
To face these challenges, efforts must take place to more consistently enforce an ever-increasing quality, quantity, duration and integration of ocean observations. All these efforts are thus critically calling for improved methodologies to better structure, explore and exploit this wealth of information.
During the last decade, the ocean community witnessed worldwide the launch of over 30 new ocean-related satellite missions. Plans for new satellites, to improve the spatial-temporal sampling, are already laid well into the foreseeable future, and today, we are already talking Petabytes of data to download, analyze, transform into accessible information. Increasing computer power and understandings of relevant physical processes are also rapidly evolving, and contribute to advances in model accuracy and resolution refinement. The different satellite sensors can only be combined to provide the required high spatio-temporal sampling using physically or statistically based merging approaches.
A prerequisite for such combined analysis is to be able to separate, in each remote sensing dataset, the geophysical signal and the sensor specific signal. Building on this first data processing, among promising applications are the emulation of high resolution analysis (in contrast with classical data assimilation framework) and determination of physical processes (surface quasi geostrophy or ageostrophy for the upper ocean circulation).
We will highlight these applications with two case studies to assess surface currents using Synthetic Aperture Radar (SAR), Sun Glitter, Sea Surface Temperature (SST) and altimetry. Two different approaches will be explored: (i) a physical one for the sub-meso scale oceanic frontal structures and (ii) a statistical one for the meso scale circulation using latent regression and hidden Markov models.