Kalman filter framework for a regional mass change model from GRACE satellite gravity

authored by: Viviana Wöhnke, Annette Eicker, Matthias Weigelt, Marvin Reich, Andreas Güntner, Andreas Kvas, Torsten Mayer-Gürr
Abstract: In this study a regional modelling framework for water mass changes is developed. The approach can introduce geodetic observation types of varying temporal and spatial resolution including their correlated error information. For this purpose a Kalman filter process was set up using a regional parameterisation by space-localising radial basis functions and a process model based on stochastic prediction. The feasibility of the approach is confirmed in a closed-loop simulation experiment using gridded water storage estimates derived from simulated monthly solutions of the GRACE satellite gravimetry mission and considering realistic error patterns. The resulting mass change time series exhibit strongly reduced noise and a very high agreement with the reference model. The modelling framework is designed to flexibly allow a future extension towards combining satellite gravimetry with other geodetic observations such as GNSS station displacements or terrestrial gravimetry.
Organisation(s): Institute of Geodesy
External Organisation(s): Universität Hamburg
German Aerospace Center (DLR)
Helmholtz Centre Potsdam - German Research Centre for Geosciences (GFZ)
University of Potsdam
University of Graz
Graz University of Technology
Type: Article
Journal: GEM - International Journal on Geomathematics
Volume: 16
ISSN: 1869-2672
Publication date: 09.12.2024
Publication status: Published
Peer reviewed: Yes
ASJC Scopus subject areas: Modelling and Simulation, General Earth and Planetary Sciences
Electronic version(s): https://doi.org/10.1007/s13137-024-00260-1 (Access: Open)

BibTeX

@article{64fa87acfeb2470c96dbcfa7c39dd850,
title = "Kalman filter framework for a regional mass change model from GRACE satellite gravity",
abstract = "In this study a regional modelling framework for water mass changes is developed. The approach can introduce geodetic observation types of varying temporal and spatial resolution including their correlated error information. For this purpose a Kalman filter process was set up using a regional parameterisation by space-localising radial basis functions and a process model based on stochastic prediction. The feasibility of the approach is confirmed in a closed-loop simulation experiment using gridded water storage estimates derived from simulated monthly solutions of the GRACE satellite gravimetry mission and considering realistic error patterns. The resulting mass change time series exhibit strongly reduced noise and a very high agreement with the reference model. The modelling framework is designed to flexibly allow a future extension towards combining satellite gravimetry with other geodetic observations such as GNSS station displacements or terrestrial gravimetry.",
keywords = "GRACE, Kalman filter, Radial basis functions, Regional gravity field modelling, Satellite gravimetry, Terrestrial water storage",
author = "Viviana W{\"o}hnke and Annette Eicker and Matthias Weigelt and Marvin Reich and Andreas G{\"u}ntner and Andreas Kvas and Torsten Mayer-G{\"u}rr",
note = "Publisher Copyright: {\textcopyright} The Author(s) 2024.",
year = "2024",
month = dec,
day = "9",
doi = "10.1007/s13137-024-00260-1",
language = "English",
volume = "16",
journal = "GEM - International Journal on Geomathematics",
issn = "1869-2672",
publisher = "Springer Verlag",
number = "1",
}