Establishing a Marine Gravity Database around Egypt from Satellite Altimetry-Derived and Shipborne Gravity Data

2021 ◽  
pp. 1-20
Author(s):  
Ahmed Zaki ◽  
Mahmoud Magdy ◽  
Mostafa Rabah ◽  
Ahmed Saber
2011 ◽  
Vol 37 (1) ◽  
pp. 5-14 ◽  
Author(s):  
Ahmed Abdalla ◽  
Robert Tenzer

We compile a new geoid model at the computation area of New Zealand and its continental shelf using the method developed at the Royal Institute of Technology (KTH) in Stockholm. This method utilizes the least-squares modification of the Stokes integral for the biased, unbiased, and optimum stochastic solutions. The modified Bruns-Stokes integral combines the regional terrestrial gravity data with a global geopotential model (GGM). Four additive corrections are calculated and applied to the approximate geoid heights in order to obtain the gravimetric geoid. These four additive corrections account for the combined direct and indirect effects of topography and atmosphere, the contribution of the downward continuation reduction, and the formulation of the Stokes problem in the spherical approximation. The gravimetric geoid model is computed using two heterogonous gravity data sets: the altimetry-derived gravity anomalies from the DNSC08 marine gravity database (offshore) and the ground gravity measurements from the GNS Science gravity database (onshore). The GGM coefficients are taken from EIGEN-GRACE02S complete to degree 65 of spherical harmonics. The topographic heights are generated from the 1×1 arc-sec detailed digital terrain model (DTM) of New Zealand and from the 30×30 arc-sec global elevation data of SRTM30_PLUS V5.0. The least-squares analysis is applied to combine the gravity and GPS-levelling data using a 7-parameter model. The fit of the KTH geoid model with GPS-levelling data in New Zealand is 7 cm in terms of the standard deviation (STD) of differences. This STD fit is the same as the STD fit of the NZGeoid2009, which is the currently adopted official quasigeoid model for New Zealand. Santrauka Stokholmo Karališkajame technologijos institute (KTH) sukurtu metodu apskaičiuotas naujas Naujosios Zelandijos ir kontinentinio šelfo geoido modelis. Taikoma Stokso integralo mažiausiųjų kvadratų modifikacija, įvertinant paklaidas ir jų nevertinant bei ieškant optimalių stochastinių sprendinių. Modifikuotas Bruno ir Stokso integralas sieja regioninius žemyninius gravimetrinius duomenis su globaliuoju geopotencialo modeliu (GGM). Gravimetriniam geoidui gauti skaičiuojamos keturios papildomos pataisos: topografinės situacijos ir atmosferos tiesioginės ir netiesioginės įtakos, redukcijos įtakos ir Stokso integralo taikymo sferiniam paviršiui. Gravimetrinis geoido modelis apskaičiuotas pagal du duomenų rinkinius: DNSC08 jūrinių gravimetrinių duomenų bazėje (šelfas) esančias altimetriniu metodu nustatytas sunkio pagreičio anomalijas ir žemyninės dalies gravimetrinių matavimų duomenis iš GNS gravimetrinės duomenų bazės (pakrantė). GGM koeficientai imti iš EIGEN-GRACE02S modelio sferinių iki 65 laipsnio harmonikų. Topografiniai aukščiai sugeneruoti iš Naujosios Zelandijos 1×1 sekundės detaliojo skaitmeninio reljefo modelio ir iš 30×30 sekundžių globaliojo aukščių modelio SRTM30_PLUS V5.0. Gravimetriniams ir GPS niveliacijos duomenims sujungti taikytas mažiausiųjų kvadratų 7 parametrų metodas. KTH metodu sudaryto geoido modelio vidutinė kvadratinė paklaida 7 cm. Tai sutampa su NZGeoid 2009 geoido modelio, taikomo Naujoje Zelandijoje, tikslumu. Резюме Модель геоида континентального шельфа Новой Зеландии построена с применением метода, созданного в Королевском технологическом институте Стокгольма. Данный метод основан на модификации решения интеграла Стокса методом наименьших квадратов с оценкой или без оценки погрешностей и поиском оптимальных статистических решений. Модифицированный интеграл БрунаСтокса объединяет региональные надземные гравиметрические данные с глобальной геопотенциальной моделью (GGM). Для определения гравиметрического геоида вычисляются дополнительные поправки прямого и косвенного влияния топографии и атмосферы, редукции и применения проблемы Стокса для сферической поверхности. Гравиметрическая модель геоида вычисляется на основе двух баз данных: альтиметрическим методом определенных аномалий силы тяжести в базе морских гравиметрических данных DNSC08 (шельф) и надземной части гравиметрических измерений из базы данных GNS. Коэффициенты GGM взяты из сферических гармоник до 65 степени модели EIGENGRACEO2S. Топографические высоты сгенерированы из детальной цифровой модели рельефа Новой Зеландии с сеткой 1×1 секунду и из глобальной модели высот SRTM30_PLUSv5.0 с сеткой 30×30 секунд. Для объединения гравиметрических и GPSнивелирных данных применялся метод наименьших квадратов с 7 параметрами. Среднеквадратическая погрешность модели геоида, созданной по методу КТН, равна 7 см. Точность аналогична точности применяемой в Новой Зеландии модели геоида NZGeoid2009.


Geosciences ◽  
2018 ◽  
Vol 8 (10) ◽  
pp. 369 ◽  
Author(s):  
Ismael Foroughi ◽  
Abdolreza Safari ◽  
Pavel Novák ◽  
Marcelo Santos

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.


2021 ◽  
Vol 14 (1) ◽  
pp. 41
Author(s):  
Zilong Ling ◽  
Lihong Zhao ◽  
Tao Zhang ◽  
Guojun Zhai ◽  
Fanlin Yang

To understand the influence of sea ice on shipborne gravity measurements and the accuracy of the satellite-altimetry-derived gravity field in the Arctic Ocean, we compared shipborne gravity measurements with those obtained from satellite altimetric gravity measurements. The influence of sea ice on the shipborne gravity measurements was mainly concentrated in the 0–6 km wavelength range, and the standard deviation of the noise amplitudes was 2.62 mGal. Compared to ice-free regions, the accuracies in the region with floating ice were reduced by 13% for DTU21 and 6% for SV31. Due to the influence of sea ice, satellite altimetric gravity data lose significant information in the 9–12 km wavelength range. The coherence curve of the shipborne gravity with bathymetry was nearly the same as that of the satellite altimetric gravity. The satellite data contain nearly all of the significant information that is present in the shipborne data. The differences between the shipborne and satellite gravity data are small and can be used to study the crustal structure of the Arctic.


2014 ◽  
Vol 37 (4) ◽  
pp. 419-439 ◽  
Author(s):  
Wenjin Chen ◽  
Robert Tenzer ◽  
Xiang Gu
Keyword(s):  

2021 ◽  
Author(s):  
Jean-Francois Crétaux ◽  
Muriel Berge-Nguyen ◽  
Stephane Calmant ◽  
Sara Fleury ◽  
Rysbek Satylkanov ◽  
...  

<p>Lake water height is a key variable in water cycle and climate change studies, which is achievable using satellite altimetry constellation. A method based on data processing of altimetry from several satellites has been developed to interpolate mean lake surface (MLS) over a set of 22 big lakes distributed on the Earth. It has been applied on nadir radar altimeters in Low Resolution Mode (LRM: Jason-3, Saral/AltiKa, CryoSat-2) in Synthetic Aperture Radar (SAR) mode (Sentinel-3A), and in SAR interferometric (SARin) mode (CryoSat-2), and on laser altimetry (ICESat). Validation of the method has been performed using a set of kinematic GPS height profiles from 18 field campaigns over the lake Issykkul, by comparison of altimetry’s height at crossover points for the other lakes and using the laser altimetry on ICESat-2 mission. The precision reached ranges from 3 to 7 cm RMS (Root Mean Square) depending on the lakes. Currently, lake water level inferred from satellite altimetry is provided with respect to an ellipsoid. Ellipsoidal heights are converted into orthométric heights using geoid models interpolated along the satellite tracks. These global geoid models were inferred from geodetic satellite missions coupled with absolute and regional anomaly gravity data sets spread over the Earth. However, the spatial resolution of the current geoid models does not allow capturing short wavelength undulations that may reach decimeters in mountaineering regions or for rift lakes (Baikal, Issykkul, Malawi, Tanganika). We interpolate in this work the geoid height anomalies with three recent geoid models, the EGM2008, XGM2016 and EIGEN-6C4d, and compare them with the Mean Surface of 22 lakes calculated using satellite altimetry. Assuming that MLS mimics the local undulations of the geoid, our study shows that over a large set of lakes (in East Africa, Andean mountain and Central Asia), short wavelength undulations of the geoid in poorly sampled areas can be derived using satellite altimetry. The models used in this study present very similar geographical patterns when compared to MLS. The precision of the models largely depends on the location of the lakes and is about 18 cm, in average over the Earth. MLS can serve as a validation dataset for any future geoid model. It will also be useful for validation of the future mission SWOT (Surface Water and Ocean Topography) which will measure and map water heights over the lakes with a high horizontal resolution of 250 by 250 meters.</p>


2019 ◽  
Vol 13 (1) ◽  
pp. 33-40 ◽  
Author(s):  
M. Abrehdary ◽  
L. E. Sjöberg ◽  
D. Sampietro

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.


2021 ◽  
Vol 9 ◽  
Author(s):  
Shanwei Liu ◽  
Yinlong Li ◽  
Qinting Sun ◽  
Jianhua Wan ◽  
Yue Jiao ◽  
...  

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.


1999 ◽  
Vol 36 (1) ◽  
pp. 75-89 ◽  
Author(s):  
Hamid Telmat ◽  
Jean-Claude Mareschal ◽  
Clément Gariépy

Gravity data were obtained along two transects on the southern coast of Ungava Bay, which provide continuous gravity coverage between Leaf Bay and George River. The transects and the derived gravity profiles extend from the Superior craton to the Rae Province across the New Quebec Orogen (NQO). Interpretation of the transect along the southwestern coast of Ungava Bay suggests crustal thickening beneath the NQO and crustal thinning beneath the Kuujjuaq Terrane, east of the NQO. Two alternative interpretations are proposed for the transect along the southeastern coast of the bay. The first model shows crustal thickening beneath the George River Shear Zone (GRSZ) and two shallow bodies correlated with the northern extensions of the GRSZ and the De Pas batholith. The second model shows constant crustal thickness and bodies more deeply rooted than in the first model. The gravity models are consistent with the easterly dipping reflections imaged along a Lithoprobe seismic line crossing Ungava Bay and suggest westward thrusting of the Rae Province over the NQO. Because no gravity data have been collected in Ungava Bay, satellite altimetry data have been used as a means to fill the gap in data collected at sea. The satellite-derived gravity data and standard Bouguer gravity data were combined in a composite map for the Ungava Bay region. The new land-based gravity measurements were used to verify and calibrate the satellite data and to ensure that offshore gravity anomalies merge with those determined by the land surveys in a reasonable fashion. Three parallel east-west gravity profiles were extracted: across Ungava Bay (59.9°N), on the southern shore of the bay (58.5°N), and onshore ~200 km south of Ungava Bay (57.1°N). The gravity signature of some major structures, such as the GRSZ, can be identified on each profile.


Sign in / Sign up

Export Citation Format

Share Document