The analysis of potential fields, and especially of the Earth's gravity and magnetic fields, is becoming increasingly important for the geosciences as a whole. New and ongoing satellite missions are continuing to provide us with ever improving accuracy and nearly global, time-dependent coverage. The gravitational field, respectively the geoid, plays an important role in climate research, as a record of and reference for the observation of mass transport. The study of the Earth's magnetic field and its temporal variations is yielding new insights into the behavior of its internal and external sources. Both gravity and magnetic data furthermore constitute primary sources of information also for the global characterization of other planets. With this vast quantity of data and the richness of research topics that can be addressed with it, there continues to be a need to develop new methods of analysis, at the global and local scales, and especially on their interface, where high- and low resolution data are to be jointly represented and interpreted, and where global/local contributions to noise/signal need to be differentiated. Global fields have traditionally been modeled in the spherical harmonics basis; local observations typically in a Cartesian space-based or Fourier framework. For over two decades now, methods that combine global with local sensitivity, often in a multiresolution setting, have been developed as alternatives: these include wavelets, radial basis functions, Slepian functions, splines, spherical cap harmonics, etc. With these, a growing range of problems can be addressed, but many further developments, including particular aspects of their algorithmic implementation, or the explicit search for sparsity in the modeling domain are awaiting further study. The purpose of this session is to provide a forum for exchange on the current state-of-the-art on these research topics, whether related to forward or inverse modeling, theoretical, computational, or observational studies.
Besides monitoring the variations of the Earth’s gravity and magnetic fields, space geodetic techniques deliver time series describing, e.g., changes of the surface geometry, sea level change variations or fluctuations in the Earth's orientation. Analysis methods have to be applied to these geodetic time series for a better understanding of the relations between the elements of the Earth’s system and their geophysical causes. Contributions to time frequency analysis and representation to display reliably the features of the temporal or spatial variability of signals existing in various geodetic data, as well as in the geophysical models are highly appreciated. We further solicit papers on different prediction techniques e.g. least-squares, neural networks, Kalman filter or uni- or multivariate autoregressive methods to forecast Earth Orientation Parameters, which are needed for real-time transformation between celestial and terrestrial reference frames.