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Use of GRACE Data to Detect the Present Land Uplift Rate in Fennoscandia
KTH. (Geodesy)
KTH. (Geodesy)
University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management, Land management, GIS. 1Division of Geodesy and Satellite Positioning, Royal Institute of Technology (KTH), Stockholm, Sweden. (Geodesy)ORCID iD: 0000-0003-0910-0596
2017 (English)In: Geophysical Journal International, ISSN 0956-540X, E-ISSN 1365-246X, Vol. 209, no 2, p. 909-922Article in journal (Refereed) Published
Abstract [en]

After more than 13 years of GRACE monthly data, the determined secular trend of gravity field variation can be used to study the regions of glacial isostatic adjustment (GIA). Here we focus on Fennoscandia where long-term terrestrial and high-quality GPS data are available, and we study the monthly GRACE data from three analysis centres. We present a new approximate formula to convert the secular trend of the GRACE gravity change to the land uplift rate without making assumptions of the ice load history. The question is whether the GRACE-derived land uplift rate by our method is related to GIA. A suitable post-processing method for the GRACE data is selected based on weighted RMS differences with the GPS data. The study reveals that none of the assumed periodic changes of the GRACE gravity field is significant in the estimation of the secular trend, and they can, therefore, be neglected. Finally, the GRACE-derived land uplift rates are obtained using the selected post-processing method, and they are compared with GPS land uplift rate data. The GPS stations with significant differences were marked using a statistical significance test. The smallest RMS difference (1.0 mm/a) was obtained by using GRACE data from the University of Texas.

Place, publisher, year, edition, pages
2017. Vol. 209, no 2, p. 909-922
Keywords [en]
aliasing periodic effect, decorrelation, glacial isostatic adjustment, GRACE, land uplift
National Category
Geophysics Other Engineering and Technologies
Research subject
Innovative Learning
Identifiers
URN: urn:nbn:se:hig:diva-23736DOI: 10.1093/gji/ggx063ISI: 000402641600028OAI: oai:DiVA.org:hig-23736DiVA, id: diva2:1080596
Available from: 2017-03-10 Created: 2017-03-10 Last updated: 2022-09-19Bibliographically approved

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Bagherbandi, Mohammad

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CiteExportLink to record
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Citation style
  • apa
  • harvard-cite-them-right
  • ieee
  • modern-language-association-8th-edition
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  • Other style
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  • sv-SE
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  • nn-NO
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  • de-DE
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More languages
Output format
  • html
  • text
  • asciidoc
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