scholarly journals Evaluation of GGMs Based on the Terrestrial Gravity Data of Gravity Disturbance and Moho Depthin Afar, Ethiopia

2021 ◽  
Vol 56 (3) ◽  
pp. 78-100
Author(s):  
Eyasu Alemu

Abstract To estimate Moho depth, geoid, gravity anomaly, and other geopotential functionals, gravity data is needed. But, gravity survey was not collected in equal distribution in Ethiopia, as the data forming part of the survey were mainly collected on accessible roads. To determine accurate Moho depth using Global Gravity Models (GGMs) for the study area, evaluation of GGMs is needed based on the available terrestrial gravity data. Moho depth lies between 28 km and 32 km in Afar. Gravity disturbances (GDs) were calculated for the terrestrial gravity data and the recent GGMs for the study area. The model-based GDs were compared with the corresponding GD obtained from the terrestrial gravity data and their differences in terms of statistical comparison parameters for determining the best fit GGM at a local scale in Afar. The largest standard deviation (SD) (36.10 mGal) and root mean square error (RMSE) (39.00 mGal) for residual GD and the lowest correlation with the terrestrial gravity (0.61 mGal) were obtained by the satellite-only model (GO_CONS_GCF_2_DIR_R6). The next largest SD (21.27 mGal) and RMSE (25.65 mGal) for residual GD were obtained by the combined gravity model (XGM2019e_2159), which indicates that it is not the best fit model for the study area as compared with the other two GGMs. In general, the result showed that the combined models are more useful tools for modeling the gravity field in Afar than the satellite-only GGMs. But, the study clearly revealed that for the study area, the best model in comparison with the others is the EGM2008, while the second best model is the EIGEN6C4.

2021 ◽  
Author(s):  
◽  
Jack McCubbine

<p>It is important to be able to accurately determine the height of a point on the Earth in terms of the Earth's gravitational potential field. These heights predict how water will flow and so they are vital for engineering and surveying purposes. They are determined using a vertical datum which consists of a specif ed height system and a defined reference surface.  At present, in New Zealand, the o fficial vertical datum is NZVD2009 which uses a normal-orthometric height system and gravimetric quasigeoid, NZGeoid2009, as the reference surface. The aim of this thesis is to develop a more accurate gravimetric quasigeoid than NZGeoid2009, by incorporating new gravity data and utilising a re fined data processing strategy, to establish a better vertical datum for New Zealand.  A new airborne gravimetry data set has been collected which covers the North, South and Stewart Islands of New Zealand with a flight line spacing of 10km. The data were susceptible to short error prone sections of track due to poor (turbulent) flight conditions and mean off sets which separate the recorded gravity data along flight lines by a constant value from neighbouring lines and existing gravity models. The error prone sections of track have been visually identified by assessing the cross track agreement with other flight lines and with the global gravity model EGM2008, and the mean offsets were estimated by a least squares method which takes into consideration the spatially correlated gravity signal.  The repeatability of the data was assessed from data collected from five flights along two separate calibration lines. The mean gravity anomaly pro files calculated along the calibration lines each had a standard deviation of around 2.5 mGal. The internal consistency of the data was assessed by evaluating the diff erence between flight line data at intersection points. This accuracy measure was shown to be influenced by the along track filter, anisotropic topography and the relative flight line elevations. After correcting for all these effects the set of all intersecting differences had a standard deviation of approximately 5.9 mGal.  From an existing terrestrial gravity database, around 40000 observations have been reprocessed to reduce them to Bouguer gravity anomalies, this was done to ensure consistency in the formulas that have been used. A new national 8 m digital elevation model (DEM) was used to calculate terrain corrections and these were carefully compared with terrain corrections estimated from field observations of the topography to reduce any discrepancies in calculating near zone terrain e ffects. The largest source of error in the terrestrial gravity anomaly data is due to inaccurate height estimates of the marks. The height discrepancies have been estimated by comparing the recorded heights in the database to those determined from the 8 m DEM and have been translated into mGal by calculating the propagated effect on the free air and Bouguer slab corrections.  The airborne and terrestrial gravity data, along with a satellite altimetry marine gravity anomaly and existing shipborne gravity data, were assimilated by least squares collocation with a logarithmic covariance function to appropriately deal with the downward continuation of the airborne data, and gridded at 1 arc-minute resolution in the geographical region 25° (S) to 60 ° (S) and 160° (E) to 190° (E). 1 arc-minute block averaged heights were then used to calculate a reverse Bouguer slab correction, which when applied to the gravity data gave a gridded Faye anomaly. Different noise level variances were assigned to the separate data sets to optimally combine them.  Forty six of the most contemporary global gravity models (from 2008 onwards) have each been compared to 1422 leveling and GNSS derived quasigeoid height anomalies. Overall the Eigen-6C4 model fitted the leveling and GNSS derived quasigeoid height anomalies best with a root mean squared error of 5.29cm.  The Eigen-6C4 gravity model was subtracted from the gridded Faye anomaly (remove) and Stokes integral was evaluated on the residual gravity anomaly grid. A, theoretically optimum, modified Stokes kernel has been used and the modification degree L and spherical cap for the integration Ψ₀ were varied over the ranges L = 20; 40; 60; ..., 320 and Ψ₀ = 1° ; 1:5° ; 2° ; 2:5° ; 3° . The Eigen-6C4 geoid undulations were then added back to the residual geoid undulation grids and the primary indirect topographic effect was restored to obtain 80 quasigeoids for each L and Ψ₀ parameter variation.  The optimal parameter choice was determined to be L = 280 and Ψ₀ = 1:5 which had the best agreement with the leveling and GNSS derived quasigeoid height anomalies with a standard deviation of 3.8cm and root mean squared residual of 4.8cm of the differences. This is a 1.25cm improvement on NZGeoid2009. The quasigeoid was also assessed closely in three main urban areas, Auckland, Wellington and Christchurch, where the majority of large scale engineering projects and surveying takes place in New Zealand. Here there were 123, 169 and 125 data points and the standard deviations of the differences were 3.976, 3.385 and 2.071cm and root mean squared differences of 3.58,4.388 and 4.572 cm respectively. This gives an average accuracy of 3.1 cm standard deviation in urban areas which is 1.5 cm better than the average for NZGeoid2009.</p>


2021 ◽  
Author(s):  
◽  
Jack McCubbine

<p>It is important to be able to accurately determine the height of a point on the Earth in terms of the Earth's gravitational potential field. These heights predict how water will flow and so they are vital for engineering and surveying purposes. They are determined using a vertical datum which consists of a specif ed height system and a defined reference surface.  At present, in New Zealand, the o fficial vertical datum is NZVD2009 which uses a normal-orthometric height system and gravimetric quasigeoid, NZGeoid2009, as the reference surface. The aim of this thesis is to develop a more accurate gravimetric quasigeoid than NZGeoid2009, by incorporating new gravity data and utilising a re fined data processing strategy, to establish a better vertical datum for New Zealand.  A new airborne gravimetry data set has been collected which covers the North, South and Stewart Islands of New Zealand with a flight line spacing of 10km. The data were susceptible to short error prone sections of track due to poor (turbulent) flight conditions and mean off sets which separate the recorded gravity data along flight lines by a constant value from neighbouring lines and existing gravity models. The error prone sections of track have been visually identified by assessing the cross track agreement with other flight lines and with the global gravity model EGM2008, and the mean offsets were estimated by a least squares method which takes into consideration the spatially correlated gravity signal.  The repeatability of the data was assessed from data collected from five flights along two separate calibration lines. The mean gravity anomaly pro files calculated along the calibration lines each had a standard deviation of around 2.5 mGal. The internal consistency of the data was assessed by evaluating the diff erence between flight line data at intersection points. This accuracy measure was shown to be influenced by the along track filter, anisotropic topography and the relative flight line elevations. After correcting for all these effects the set of all intersecting differences had a standard deviation of approximately 5.9 mGal.  From an existing terrestrial gravity database, around 40000 observations have been reprocessed to reduce them to Bouguer gravity anomalies, this was done to ensure consistency in the formulas that have been used. A new national 8 m digital elevation model (DEM) was used to calculate terrain corrections and these were carefully compared with terrain corrections estimated from field observations of the topography to reduce any discrepancies in calculating near zone terrain e ffects. The largest source of error in the terrestrial gravity anomaly data is due to inaccurate height estimates of the marks. The height discrepancies have been estimated by comparing the recorded heights in the database to those determined from the 8 m DEM and have been translated into mGal by calculating the propagated effect on the free air and Bouguer slab corrections.  The airborne and terrestrial gravity data, along with a satellite altimetry marine gravity anomaly and existing shipborne gravity data, were assimilated by least squares collocation with a logarithmic covariance function to appropriately deal with the downward continuation of the airborne data, and gridded at 1 arc-minute resolution in the geographical region 25° (S) to 60 ° (S) and 160° (E) to 190° (E). 1 arc-minute block averaged heights were then used to calculate a reverse Bouguer slab correction, which when applied to the gravity data gave a gridded Faye anomaly. Different noise level variances were assigned to the separate data sets to optimally combine them.  Forty six of the most contemporary global gravity models (from 2008 onwards) have each been compared to 1422 leveling and GNSS derived quasigeoid height anomalies. Overall the Eigen-6C4 model fitted the leveling and GNSS derived quasigeoid height anomalies best with a root mean squared error of 5.29cm.  The Eigen-6C4 gravity model was subtracted from the gridded Faye anomaly (remove) and Stokes integral was evaluated on the residual gravity anomaly grid. A, theoretically optimum, modified Stokes kernel has been used and the modification degree L and spherical cap for the integration Ψ₀ were varied over the ranges L = 20; 40; 60; ..., 320 and Ψ₀ = 1° ; 1:5° ; 2° ; 2:5° ; 3° . The Eigen-6C4 geoid undulations were then added back to the residual geoid undulation grids and the primary indirect topographic effect was restored to obtain 80 quasigeoids for each L and Ψ₀ parameter variation.  The optimal parameter choice was determined to be L = 280 and Ψ₀ = 1:5 which had the best agreement with the leveling and GNSS derived quasigeoid height anomalies with a standard deviation of 3.8cm and root mean squared residual of 4.8cm of the differences. This is a 1.25cm improvement on NZGeoid2009. The quasigeoid was also assessed closely in three main urban areas, Auckland, Wellington and Christchurch, where the majority of large scale engineering projects and surveying takes place in New Zealand. Here there were 123, 169 and 125 data points and the standard deviations of the differences were 3.976, 3.385 and 2.071cm and root mean squared differences of 3.58,4.388 and 4.572 cm respectively. This gives an average accuracy of 3.1 cm standard deviation in urban areas which is 1.5 cm better than the average for NZGeoid2009.</p>


2017 ◽  
Vol 43 (1) ◽  
pp. 1-13 ◽  
Author(s):  
Ismael FOROUGHI ◽  
Yosra AFRASTEH ◽  
Sabah RAMOUZ ◽  
Abdolreza SAFARI

Global gravity models are being developed according to new data sets available from satellite gravity missions and terrestrial/marine gravity data which are provided by different countries. Some countries do not provide all their available data and the global gravity models have many vague computational methods. Therefore, the models need to be evaluated locally before using. It is generally understood that the accuracy of global gravity models is enough for local (civil, mining, construction, etc.) projects, however, our results in Iran show that the differences between synthesized values and observation data reach up to ∼300 mGal for gravity anomalies and ∼2 m for geoid heights. Even by applying the residual topographical correction to synthetized gravity anomalies, the differences are still notable. The accuracy of global gravity models for predicting marine gravity anomalies is also investigated in Persian Gulf and the results show differences of ∼140 mGal in coastal areas. The results of evaluating selected global gravity models in Iran indicate that the EIGEN-6C4 achieves the lowest RMS for estimating the geoid heights. EGM08 predicts the closest results to terrestrial gravity anomalies. DIR-R5 GOCE satellite-only model estimates the low-frequency part of gravity field more accurately. The best prediction of marine gravity anomalies is also achieved by EGM08.


2021 ◽  
Author(s):  
Mirko Scheinert ◽  
Philipp Zingerle ◽  
Theresa Schaller ◽  
Roland Pail ◽  
Martin Willberg

&lt;p&gt;In the frame of the IAG Subcommission 2.4f &amp;#8220;Gravity and Geoid in Antarctica&amp;#8221; (AntGG) a first Antarctic-wide grid of ground-based gravity anomalies was released in 2016 (Scheinert et al. 2016). That data set was provided with a grid space of 10 km and covered about 73% of the Antarctic continent. Since then a considerably amount of new data has been made available, mainly collected by means of airborne gravimetry. Regions which were formerly void of any terrestrial gravity observations and have now been surveyed include especially the polar data gap originating from GOCE satellite gravimetry. Thus, it is timely to come up with an updated and enhanced regional gravity field solution for Antarctica. For this, we aim to improve further aspects in comparison to the AntGG 2016 solution: The grid spacing will be enhanced to 5 km. Instead of providing gravity anomalies only for parts of Antarctica, now the entire continent should be covered. In addition to the gravity anomaly also a regional geoid solution should be provided along with further desirable functionals (e.g. gravity anomaly vs. disturbance, different height levels).&lt;/p&gt;&lt;p&gt;We will discuss the expanded AntGG data base which now includes terrestrial gravity data from Antarctic surveys conducted over the past 40 years. The methodology applied in the analysis is based on the remove-compute-restore technique. Here we utilize the newly developed combined spherical-harmonic gravity field model SATOP1 (Zingerle et al. 2019) which is based on the global satellite-only model GOCO05s and the high-resolution topographic model EARTH2014. We will demonstrate the feasibility to adequately reduce the original gravity data and, thus, to also cross-validate and evaluate the accuracy of the data especially where different data set overlap. For the compute step the recently developed partition-enhanced least-squares collocation (PE-LSC) has been used (Zingerle et al. 2021, in review; cf. the contribution of Zingerle et al. in the same session). This method allows to treat all data available in Antarctica in one single computation step in an efficient and fast way. Thus, it becomes feasible to iterate the computations within short time once any input data or parameters are changed, and to easily predict the desirable functionals also in regions void of terrestrial measurements as well as at any height level (e.g. gravity anomalies at the surface or gravity disturbances at constant height).&lt;/p&gt;&lt;p&gt;We will discuss the results and give an outlook on the data products which shall be finally provided to present the new regional gravity field solution for Antarctica. Furthermore, implications for further applications will be discussed e.g. with respect to geophysical modelling of the Earth&amp;#8217;s interior (cf. the contribution of Schaller et al. in session G4.3).&lt;/p&gt;


2018 ◽  
Vol 935 (5) ◽  
pp. 2-9
Author(s):  
K.I. Markovich

The possible range of application of models of the Earth’s gravitational field is considered in the article by reducing the results of geometric leveling to a system of normal heights. The accuracy of the global gravity models EGM2008, EIGEN-6C4, GECO on the gravity acceleration differences calculated for the territory of the Republic of Belarus by the results of instrumental gravimetric measurements and obtained from gravity models was estimated. Areas of Belarus are determined for which the gravitational correction for the transition to the system of normal heights will be caused by the deviation of the level surfaces of the normal gravitational field from the actual, and not by the errors of the gravitational models in the form of acceleration of gravity. It is shown that the error of the gravitational correction obtained from the data of gravity models for the territory of Belarus is many times less than the permissible random mean error of geometric leveling of the first class.


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