The analysis of the Earth's gravity and magnetic fields is becoming increasingly important in geosciences. Modern satellite missions are continuing to provide data with ever improving accuracy and nearly global, time-dependent coverage. The gravitational field 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. Hence, there continues to be a need to develop new methods of analysis, at the global and local scales, and especially on their interface. For over two decades now, methods that combine global with local sensitivity, often in a multiresolution setting, have been developed: these include wavelets, radial basis functions, Slepian functions, splines, spherical cap harmonics, etc. One purpose of this session is to provide a forum for exchange of research projects, whether related to forward or inverse modeling, theoretical, computational, or observational studies.
Besides monitoring the variations of the gravity and magnetic fields, space geodetic techniques deliver time series describing changes of the surface geometry, sea level change variations or fluctuations in the Earth's orientation. However, geodetic observation systems usually measure the integral effect. Thus, analysis methods have to be applied to the geodetic time series for a better understanding of the relations between and within the components of the system Earth. The combination of data from various space geodetic and remote sensing techniques may allow for separating the integral measurements into individual contributions of the Earth system components. Presentations to time frequency analysis, to the detection of features of the temporal or spatial variability of signals existing in geodetic data and in geophysical models, as well as to the investigations on signal separation techniques, e.g. EOF, 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.