Next Article in Journal
Mangrove Phenology and Environmental Drivers Derived from Remote Sensing in Southern Thailand
Next Article in Special Issue
GOCE-Derived Coseismic Gravity Gradient Changes Caused by the 2011 Tohoku-Oki Earthquake
Previous Article in Journal
Satellite Remote Sensing Signatures of the Major Baltic Inflows
Previous Article in Special Issue
The Rapid and Steady Mass Loss of the Patagonian Icefields throughout the GRACE Era: 2002–2017

SLR, GRACE and Swarm Gravity Field Determination and Combination

Astronomical Institute, University of Bern, 3012 Bern, Switzerland
Institute of Geodesy and Geoinformatics, Wroclaw University of Environmental and Life Sciences, 50-375 Wroclaw, Poland
GFZ German Research Centre for Geosciences, 14473 Potsdam, Germany
Bundesamt für Kartographie und Geodäsie, 60598 Frankfurt, Germany
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(8), 956;
Received: 28 February 2019 / Revised: 30 March 2019 / Accepted: 16 April 2019 / Published: 22 April 2019
(This article belongs to the Special Issue Remote Sensing by Satellite Gravimetry)
Satellite gravimetry allows for determining large scale mass transport in the system Earth and to quantify ice mass change in polar regions. We provide, evaluate and compare a long time-series of monthly gravity field solutions derived either by satellite laser ranging (SLR) to geodetic satellites, by GPS and K-band observations of the GRACE mission, or by GPS observations of the three Swarm satellites. While GRACE provides gravity signal at the highest spatial resolution, SLR sheds light on mass transport in polar regions at larger scales also in the pre- and post-GRACE era. To bridge the gap between GRACE and GRACE Follow-On, we also derive monthly gravity fields using Swarm data and perform a combination with SLR. To correctly take all correlations into account, this combination is performed on the normal equation level. Validating the Swarm/SLR combination against GRACE during the overlapping period January 2015 to June 2016, the best fit is achieved when down-weighting Swarm compared to the weights determined by variance component estimation. While between 2014 and 2017 SLR alone slightly overestimates mass loss in Greenland compared to GRACE, the combined gravity fields match significantly better in the overlapping time period and the RMS of the differences is reduced by almost 100 Gt. After 2017, both SLR and Swarm indicate moderate mass gain in Greenland. View Full-Text
Keywords: satellite gravimetry; ice mass change; GRACE; SLR; swarm; normal equation combination satellite gravimetry; ice mass change; GRACE; SLR; swarm; normal equation combination
Show Figures

Graphical abstract

MDPI and ACS Style

Meyer, U.; Sosnica, K.; Arnold, D.; Dahle, C.; Thaller, D.; Dach, R.; Jäggi, A. SLR, GRACE and Swarm Gravity Field Determination and Combination. Remote Sens. 2019, 11, 956.

AMA Style

Meyer U, Sosnica K, Arnold D, Dahle C, Thaller D, Dach R, Jäggi A. SLR, GRACE and Swarm Gravity Field Determination and Combination. Remote Sensing. 2019; 11(8):956.

Chicago/Turabian Style

Meyer, Ulrich, Krzysztof Sosnica, Daniel Arnold, Christoph Dahle, Daniela Thaller, Rolf Dach, and Adrian Jäggi. 2019. "SLR, GRACE and Swarm Gravity Field Determination and Combination" Remote Sensing 11, no. 8: 956.

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

Back to TopTop