Data Driven Approaches for the Prediction of Earth's Effective Angular Momentum Functions
Mostafa Kiani Shahvandi, Junyang Gou, Matthias Schartner, Benedikt Soja
Abstract
Effective Angular Momentum (EAM) functions and their predictions are essential geophysical information in describing the changes in earth's orientation. We present the frame-work for the prediction of EAM functions developed at the Chair of Space Geodesy at ETH Zurich. The framework functioning and its underlying methods are explained. In addition, the comparative prediction performance of the methods of the framework with respect to the ones provided by the German Research Centre for Geosciences GFZ is analyzed. The best-performing method is a linear recursive forecasting approach. It manages to improve the EAM predictions between 18 to 64%. The highest improvement could be obtained for the Atmospheric Angular Momentum (AAM) components, with an average improvement of > 50%.