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An integral approach to regional gravity field refinement using Earth gravity models
University West, Department of Engineering Science, Division of Natural Sciences and Electrical and Surveying Engineering.ORCID iD: 0000-0003-0067-8631
2013 (English)In: Journal of Geodynamics, ISSN 0264-3707, E-ISSN 1879-1670, Vol. 68, p. 18-28Article in journal (Refereed) Published
Abstract [en]

The idea of this paper is to refine the terrestrial gravimetric data with the Earth's gravity models (EGMs) and produce a high quality source of gravity data. For this purpose, biased and unbiased integral estimators are presented. These estimators are used to refine gravimetric data over Fennoscandia with the ITG-GRACE2010s and GO_CONS_GCF_2_DIR_R2 EGMs, which are the recent products of the gravity field and climate experiment (GRACE) and the gravity field and steady-state ocean circulation explorer (GOCE) satellite missions. Numerical results show that the biased integral estimator has smaller global root mean square error (RMSE) than the unbiased one. Also a simple strategy is presented to down-weight the low-frequencies the terrestrial data in spectral combination. The gravity anomalies, computed by EGM08, are compared to the refined anomalies for evaluation purpose. In the case of using a cap size of 1° for integration the EGM08 gravity anomalies are more correlated with the refined ones. Also the band-limited kernels can simply be generated to maximum degree of the used EGMs for both estimators. Comparisons of the combined anomalies and those of EGM08 show insignificant differences between the biased and unbiased estimators in practice. However, the biased estimator seems to be proper one for gravity data refinement due to its smaller global RMSE.

Place, publisher, year, edition, pages
2013. Vol. 68, p. 18-28
Keywords [en]
Spectral combination; Gravity anomaly estimator; Biased and unbiased combination; Global root mean square error
National Category
Geophysics
Identifiers
URN: urn:nbn:se:hv:diva-5249DOI: 10.1016/j.jog.2013.03.001ISI: 000320088400002Scopus ID: 2-s2.0-84876301941OAI: oai:DiVA.org:hv-5249DiVA, id: diva2:615967
Available from: 2013-04-13 Created: 2013-04-13 Last updated: 2017-12-06Bibliographically approved

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Eshagh, Mehdi

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