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Abrehdary, Majid
Publications (3 of 3) Show all publications
Abrehdary, M., Sjöberg, L. E. & Sampietro, D. (2019). Contribution of satellite altimetry in modelling Moho density contrast in oceanic areas. Journal of Applied Geodesy, 3(1), 33-40
Open this publication in new window or tab >>Contribution of satellite altimetry in modelling Moho density contrast in oceanic areas
2019 (English)In: Journal of Applied Geodesy, ISSN 1862-9016, E-ISSN 1862-9024, Vol. 3, no 1, p. 33-40Article in journal (Refereed) Published
Abstract [en]

The determination of the oceanic Moho (or crust-mantle) density contrast derived from seismic acquisitions suffers from severe lack of data in large parts of the oceans, where have not yet been sufficiently covered by such data. In order to overcome this limitation, gravitational field models obtained by means of satellite altimetry missions can be proficiently exploited, as they provide global uniform information with a sufficient accuracy and resolution for such a task. In this article, we estimate a new Moho density contrast model named MDC2018, using the marine gravity field from satellite altimetry in combination with a seismic-based crustal model and Earth's topographic/bathymetric data. The solution is based on the theory leading to Vening Meinesz-Moritz's isostatic model. The study results in a high-accuracy Moho density contrast model with a resolution of 1° × 1° in oceanic areas. The numerical investigations show that the estimated density contrast ranges from 14.2 to 599.7 kg/m3 with a global average of 293 kg/m3. In order to evaluate the accuracy of the MDC2018 model, the result was compared with some published global models, revealing that our altimetric model is able to image rather reliable information in most of the oceanic areas. However, the differences between this model and the published results are most notable along the coastal and polar zones, which are most likely due to that the quality and coverage of the satellite altimetry data are worsened in these regions.

Keywords
Aneroid altimeters; Coastal zones; Seismology, GMG2014; Isostasy; MDC2018; Moho Density Contrast; Satellite altimetry; Vening Meinesz-Moritz, Satellites
National Category
Geophysics
Research subject
ENGINEERING, Geodesy
Identifiers
urn:nbn:se:hv:diva-13120 (URN)10.1515/jag-2018-0034 (DOI)2-s2.0-85055655330 (Scopus ID)
Available from: 2018-11-13 Created: 2018-11-13 Last updated: 2020-01-27Bibliographically approved
Abrehdary, M. & Sjöberg, L. E. (2019). Estimating a combined Moho model for marine areas via satellite altimetric: gravity and seismic crustal models. Studia Geophysica et Geodaetica
Open this publication in new window or tab >>Estimating a combined Moho model for marine areas via satellite altimetric: gravity and seismic crustal models
2019 (English)In: Studia Geophysica et Geodaetica, ISSN 0039-3169, E-ISSN 1573-1626Article in journal (Refereed) Epub ahead of print
Abstract [en]

Isostasy is a key concept in geoscience in interpreting the state of mass balance between the Earth's lithosphere and viscous asthenosphere. A more satisfactory test of isostasy is to determine the depth to and density contrast between crust and mantle at the Moho discontinuity (Moho). Generally, the Moho can be mapped by seismic information, but the limited coverage of such data over large portions of the world (in particular at seas) and economic considerations make a combined gravimetric-seismic method a more realistic approach. The determination of a high-resolution of the Moho constituents for marine areas requires the combination of gravimetric and seismic data to diminish substantially the seismic data gaps. In this study, we estimate the Moho constituents globally for ocean regions to a resolution of 1° × 1° by applying the Vening Meinesz-Moritz method from gravimetric data and combine it with estimates derived from seismic data in a new model named COMHV19. The data files of GMG14 satellite altimetry-derived marine gravity field, the Earth2014 Earth topographic/bathymetric model, CRUST1.0 and CRUST19 crustal seismic models are used in a least-squares procedure. The numerical computations show that the Moho depths range from 7.3 km (in Kolbeinsey Ridge) to 52.6 km (in the Gulf of Bothnia) with a global average of 16.4 km and standard deviation of the order of 7.5 km. Estimated Moho density contrasts vary between 20 kg m-3 (north of Iceland) to 570 kg m-3 (in Baltic Sea), with a global average of 313.7 kg m-3 and standard deviation of the order of 77.4 kg m-3. When comparing the computed Moho depths with current knowledge of crustal structure, they are generally found to be in good agreement with other crustal models. However, in certain regions, such as oceanic spreading ridges and hot spots, we generally obtain thinner crust than proposed by other models, which is likely the result of improvements in the new model. We also see evidence for thickening of oceanic crust with increasing age. Hence, the new combined Moho model is able to image rather reliable information in most of the oceanic areas, in particular in ocean ridges, which are important features in ocean basins.

Keywords
Moho density contrast, Moho depth, satellite altimetry, uncertainty, Vening Meinesz-Moritz
National Category
Geophysics
Research subject
ENGINEERING, Geodesy
Identifiers
urn:nbn:se:hv:diva-14873 (URN)10.1007/s11200-019-1067-0 (DOI)2-s2.0-85076399462 (Scopus ID)
Funder
Swedish National Space Board, 187/18
Available from: 2020-01-29 Created: 2020-01-29 Last updated: 2020-02-23Bibliographically approved
Abrehdary, M. & Sjöberg, L. (2019). Recovering Moho constituents from satellite altimetry and gravimetric data for Europe and surroundings. Journal of Applied Geodesy, 13(4), 291-303
Open this publication in new window or tab >>Recovering Moho constituents from satellite altimetry and gravimetric data for Europe and surroundings
2019 (English)In: Journal of Applied Geodesy, ISSN 1862-9016, E-ISSN 1862-9024, Vol. 13, no 4, p. 291-303Article in journal (Refereed) Published
Abstract [en]

In this research, we present a local Moho model, named MOHV19, including Moho depth and Moho density contrast (or shortly Moho constituents) with corresponding uncertainties, which are mapped from altimetric and gravimetric data (DSNSC08) in addition to seismic tomographic (CRUST1.0) and Earth topographic data (Earth2014) to a resolution of 1° × 1° based on a solution of Vening Meinesz-Moritz' theory of isostasy. The MOHV19 model covers the area of entire European plate along with the surrounding oceans, bounded by latitudes (30 °N–82 °N) and longitudes (40 °W–70 °E). The article aims to interpret the Moho model resulted via altimetric and gravimetric information from the geological and geophysical perspectives along with investigating the relation between the Moho depth and Moho density contrast. Our numerical results show that estimated Moho depths range from 7.5 to 57.9 km with continental and oceanic averages of 41.3 ± 4.9 km and 21.6 ± 9.2 km, respectively, and an overall average of 30.9 ± 12.3 km. The estimated Moho density contrast ranges from 60.2 to 565.8 kg/m3, with averages of 421.8 ± 57.9 and 284.4 ± 62.9 kg/m3 for continental and oceanic regions, respectively, with a total average of 350.3 ± 91.5 kg/m3. In most areas, estimated uncertainties in the Moho constituents are less than 3 km and 40 kg/m3, respectively, but they reach to much more significant values under Iceland, parts of Gulf of Bothnia and along the Kvitoya Island. Comparing the Moho depths estimated by MOHV19 and those derived by CRUST1.0, MDN07, GRAD09 and MD19 models shows that MOHV19 agree fairly well with CRUST1.0 but rather poor with other models. The RMS difference between the Moho density contrasts estimated by MOHV19 and CRUST1.0 models is 49.45 kg/m3.

Keywords
Geodesy; Gravimetric analysis, Altimetry; Europe; Isostasy; Moho density contrast; Moho depth; MOHV19; Vening Meinesz-Moritz, Uncertainty analysis
National Category
Geophysics
Research subject
ENGINEERING, Geodesy
Identifiers
urn:nbn:se:hv:diva-14456 (URN)10.1515/jag-2019-0011 (DOI)2-s2.0-85067414113 (Scopus ID)
Available from: 2019-10-01 Created: 2019-10-01 Last updated: 2020-01-10Bibliographically approved
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