The DNSC08GRA global marine gravity field from double retracked satellite altimetry

2009 ◽  
Vol 84 (3) ◽  
pp. 191-199 ◽  
Author(s):  
Ole Baltazar Andersen ◽  
Per Knudsen ◽  
Philippa A. M. Berry
Keyword(s):  
Gravity Field ◽  
Satellite Altimetry ◽  
Marine Gravity

A comparison between sea-bottom gravity and satellite altimeter-derived gravity in coastal environments: A case study of the Gulf of Manfredonia (SW Adriatic Sea)

2021 ◽  
Author(s):  
Luigi Sante Zampa ◽  
Emanuele Lodolo ◽  
Nicola Creati ◽  
Martina Busetti ◽  
Gianni Madrussani ◽  
...  
Keyword(s):  
Gravity Field ◽  
Satellite Altimetry ◽  
Adriatic Sea ◽  
Gravity Anomalies ◽  
Satellite Altimeter ◽  
Sea Bottom ◽  
Marine Gravity ◽  
Gravity Measurements ◽  
Near Shore ◽  
Italian Coasts

<p>In this study, we present a comparative analysis between two types of gravity data used in geophysical applications: satellite altimeter-derived gravity and sea-bottom gravity.</p><p>It is largely known that the marine gravity field derived from satellite altimetry in coastal areas is generally biased by signals back-scattered from the nearby land. As a result, the derived gravity anomalies are mostly unreliable for geophysical and geological interpretations of near-shore environments.</p><p>To quantify the errors generated by the land-reflected signals and to verify the goodness of the geologic models inferred from gravity, we compared two different altimetry models with sea-bottom gravity measurements acquired along the Italian coasts from the early 50s to the late 80s.</p><p>We focused on the Gulf of Manfredonia, located in the SE sector of the Adriatic Sea, where: (i) two different sea-bottom gravity surveys have been conducted over the years, (ii) the bathymetry is particularly flat, and (iii) seismic data revealed a prominent carbonate ridge covered by hundreds of meters of Oligocene-Quaternary sediments.</p><p>Gravity field derivatives have been used to enhance both: (i) deep geological contacts, and (ii) coastal noise. The analyses outlined a “ringing-noise effect” which causes the altimeter signal degradation up to 17 km from the coast.</p><p>Differences between the observed gravity and the gravity calculated from a geological model constrained by seismic, showed that all datasets register approximately the same patterns, associated with the Gondola Fault Zone, a major structural discontinuity traversing roughly E-W the investigated area.</p><p>This study highlights the importance of implementing gravity anomalies derived from satellite-altimetry with high-resolution near-shore data, such as the sea-bottom gravity measurements available around the Italian coasts. Such analysis may have significant applications in studying the link between onshore and offshore geological structures in transitional areas.</p>

Global and Arctic Marine Gravity Field From Recent Satellite Altimetry (DTU13)

2014 ◽  
Author(s):  
O. B. Andersen ◽  
P. Knudsen ◽  
S. Kenyon ◽  
S. Holmes
Keyword(s):  
Gravity Field ◽  
Satellite Altimetry ◽  
Marine Gravity

scholarly journals Antarctic marine gravity field from high-density satellite altimetry

1992 ◽  
Vol 109 (2) ◽  
pp. 437-448 ◽  
Author(s):  
David T. Sandwell
Keyword(s):  
Gravity Field ◽  
Satellite Altimetry ◽  
High Density ◽  
Marine Gravity ◽  
Antarctic Marine

scholarly journals Application of Radial Basis Functions for Height Datum Unification

Geosciences ◽  
2018 ◽  
Vol 8 (10) ◽  
pp. 369 ◽  
Author(s):  
Ismael Foroughi ◽  
Abdolreza Safari ◽  
Pavel Novák ◽  
Marcelo Santos
Keyword(s):  
Gravity Field ◽  
Satellite Altimetry ◽  
Gravity Data ◽  
Gravity Anomalies ◽  
Basis Functions ◽  
Gravity Potential ◽  
Field Modelling ◽  
Marine Gravity ◽  
Local Gravity ◽  
Local Gravity Field Modelling

Local gravity field modelling demands high-quality gravity data as well as an appropriate mathematical model. Particularly in coastal areas, there may be different types of gravity observations available, for instance, terrestrial, aerial, marine gravity, and satellite altimetry data. Thus, it is important to develop a proper tool to merge the different data types for local gravity field modelling and determination of the geoid. In this study, radial basis functions, as a commonly useful tool for gravity data integration, are employed to model the gravity potential field of the southern part of Iran using terrestrial gravity anomalies, gravity anomalies derived from re-tracked satellite altimetry, marine gravity anomalies, and gravity anomalies synthesized from an Earth gravity model. Reference GNSS/levelling (geometric) geoidal heights are used to evaluate the accuracy of the estimated local gravity field model. The gravimetric geoidal heights are in acceptable agreement with the geometric ones in terms of the standard deviation and the mean value which are 4.1 and 12 cm, respectively. Besides, the reference benchmark of the national first-order levelling network of Iran is located in the study area. The derived gravity model was used to compute the gravity potential difference at this point and then transformed into a height difference which results in the value of the shift of this benchmark with respect to the geoid. The estimated shift shows a good agreement with previously published studies.

scholarly journals Coastal marine gravity modelling from satellite altimetry – case study in the Mediterranean

2021 ◽  
Vol 11 (1) ◽  
pp. 29-37
Author(s):  
Adili Abulaitijiang ◽  
Ole Baltazar Andersen ◽  
Riccardo Barzaghi ◽  
Per Knudsen
Keyword(s):  
Gravity Field ◽  
Satellite Altimetry ◽  
Gravity Anomalies ◽  
Gravity Modelling ◽  
Coastal Marine ◽  
Marine Gravity ◽  
Collocation Technique ◽  
Data Coverage ◽  
Potential Improvement

Abstract The coastal marine gravity field is not well modelled due to poor data coverage. Recent satellite altimeters provide reliable altimetry observations near the coast, filling the gaps between the open ocean and land. We show the potential of recent satellite altimetry for the coastal marine gravity modelling using the least squares collocation technique. Gravity prediction error near the coast is better than 4 mGal. The modelled gravity anomalies are validated with sparse shipborne gravimetric measurements. We obtained 4.86 mGal precision when using the altimetry data with the best coastal coverage and retracked with narrow primary peak retracker. The predicted gravity field is an enhancement to EGM2008 over the coastal regions. The potential improvement in alti- metric marine gravity will be beneficial for the next generation of EGM development.

Resolution of the Scripps/NOAA Marine Gravity Field from satellite altimetry

1996 ◽  
Vol 23 (16) ◽  
pp. 2069-2072 ◽  
Author(s):  
Karen M. Marks
Keyword(s):  
Gravity Field ◽  
Satellite Altimetry ◽  
Marine Gravity

Contribution of satellite altimetry in modelling Moho density contrast in oceanic areas

2019 ◽  
Vol 13 (1) ◽  
pp. 33-40 ◽  
Author(s):  
M. Abrehdary ◽  
L. E. Sjöberg ◽  
D. Sampietro
Keyword(s):  
Satellite Altimetry ◽  
Density Contrast ◽  
Contrast Model ◽  
Bathymetric Data ◽  
Crustal Model ◽  
Marine Gravity ◽  
Study Results ◽  
Vening Meinesz ◽  
Satellite Altimetry Data

Abstract 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.

scholarly journals Evaluation of Marine Gravity Anomaly Calculation Accuracy by Multi-Source Satellite Altimetry Data

2021 ◽  
Vol 9 ◽  
Author(s):  
Shanwei Liu ◽  
Yinlong Li ◽  
Qinting Sun ◽  
Jianhua Wan ◽  
Yue Jiao ◽  
...  
Keyword(s):  
Root Mean Square Error ◽  
Gravity Anomaly ◽  
Mean Square Error ◽  
Spatial Resolution ◽  
Satellite Altimetry ◽  
Gravity Anomalies ◽  
Mean Square ◽  
Altimetry Data ◽  
Marine Gravity ◽  
Satellite Altimetry Data

The purpose of this paper is to analyze the influence of satellite altimetry data accuracy on the marine gravity anomaly accuracy. The data of 12 altimetry satellites in the research area (5°N–23°N, 105°E–118°E) were selected. These data were classified into three groups: A, B, and C, according to the track density, the accuracy of the altimetry satellites, and the differences of self-crossover. Group A contains CryoSat-2, group B includes Geosat, ERS-1, ERS-2, and Envisat, and group C comprises T/P, Jason-1/2/3, HY-2A, SARAL, and Sentinel-3A. In Experiment I, the 5′×5′ marine gravity anomalies were obtained based on the data of groups A, B, and C, respectively. Compared with the shipborne gravity data, the root mean square error (RMSE) of groups A, B, and C was 4.59 mGal, 4.61 mGal, and 4.51 mGal, respectively. The results show that high-precision satellite altimetry data can improve the calculation accuracy of gravity anomaly, and the single satellite CryoSat-2 enables achieving the same effect of multi-satellite joint processing. In Experiment II, the 2′×2′ marine gravity anomalies were acquired based on the data of groups A, A + B, and A + C, respectively. The root mean square error of the above three groups was, respectively, 4.29 mGal, 4.30 mGal, and 4.21 mGal, and the outcomes show that when the spatial resolution is satisfied, adding redundant low-precision altimetry data will add pressure to the calculation of marine gravity anomalies and will not improve the accuracy. An effective combination of multi-satellite data can improve the accuracy and spatial resolution of the marine gravity anomaly inversion.

scholarly journals Recovering Marine Gravity Over the Gulf of Guinea From Multi-Satellite Sea Surface Heights

2021 ◽  
Vol 9 ◽  
Author(s):  
Richard Fiifi Annan ◽  
Xiaoyun Wan
Keyword(s):  
Gravity Field ◽  
Gravity Anomalies ◽  
Sea Surface ◽  
Shallow Waters ◽  
Gulf Of Guinea ◽  
Gravity Field Model ◽  
The North ◽  
Marine Gravity ◽  
Sea Surface Heights ◽  
East Component

A regional gravity field product, comprising vertical deflections and gravity anomalies, of the Gulf of Guinea (15°W to 5°E, 4°S to 4°N) has been developed from sea surface heights (SSH) of five altimetry missions. Though the remove-restore technique was adopted, the deflections of the vertical were computed directly from the SSH without the influence of a global geopotential model. The north-component of vertical deflections was more accurate than the east-component by almost three times. Analysis of results showed each satellite can contribute almost equally in resolving the north-component. This is attributable to the nearly northern inclinations of the various satellites. However, Cryosat-2, Jason-1/GM, and SARAL/AltiKa contributed the most in resolving the east-component. We attribute this to the superior spatial resolution of Cryosat-2, the lower inclination of Jason-1/GM, and the high range accuracy of the Ka-band of SARAL/AltiKa. Weights of 0.687 and 0.313 were, respectively, assigned to the north and east components in order to minimize their non-uniform accuracy effect on the resultant gravity anomaly model. Histogram of computed gravity anomalies compared well with those from renowned models: DTU13, SIOv28, and EGM2008. It averagely deviates from the reference models by −0.33 mGal. Further assessment was done by comparing it with a quadratically adjusted shipborne free-air gravity anomalies. After some data cleaning, observations in shallow waters, as well as some ship tracks were still unreliable. By excluding the observations in shallow waters, the derived gravity field model compares well in ocean depths deeper than 2,000 m.

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