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The Uruguayan gravimetric quasi-geoid model UruQGeoide110 was calculated by the Military Geographic Institute (IGM) in 2023. The extent is from 29.5° S to 35.5° S in latitude, and 52.5° W to 59.5° W in longitude, covering parts of Argentina and Brazil, with a grid resolution of 1´ x 1´. The geodetic reference system is SIRGAS ROU-98 (the reference ellipsoid is GRS80). The model is a combination of the EIGEN-6C4 geopotential model up to degree and order of 720, 10,429 land gravimetric stations plus 10,089 free air gravity anomalies in marine areas, based on the DTU13 model. The terrain data at the final 90 m resolution was taken from a 2017 Lidar survey in Uruguay with a 2.5 m initial resolution and SRTM (V2) for the external terrestrial data. The DT18 bathymetry model was used for the marine areas. Due to the total terrain data points (about 104 million), the overall area was divided into 4 overlapped blocks in the framework of the remove-compute-restore procedure. The reduced height anomalies were computed from the reduced gravity anomalies with Stokes 1D FFT and Wong Gore´s kernel modification (170-180 degrees) and the quasi-geoid model was finally obtained by adding back the residual terrain model effects and the contribution of the global geopotential model. The geoid model is provided in ISG format 2.0 (ISG Format Specifications), while the file in its original data format is available at the model ISG webpage.
The new time series of GRACE and GRACE-FO monthly solution HUST-Grace2024 is recently developed at Huazhong University of Science and Technology. During retrieving our model, the reprocessed GRACE L1b RL03 data and GRACE-FO RL04 data are used, and the newly de-aliasing product AOD1B RL07 is applied. In addition, a hybrid processing chain is applied to improve the quality of final solutions. Further details are presented in Zhou et al. (2024). This work is supported by the National Natural Science Foundation of China (No. 42074018, 41931074, 42061134007).
The Uruguayan gravimetric geoid model UruGeoide110 was calculated by the Military Geographic Institute (IGM) in 2023. The extent is from 29.5° S to 35.5° S in latitude, and 52.5° W to 59.5° W in longitude, covering parts of Argentina and Brazil, with a grid resolution of 1´ x 1´. The geodetic reference system is SIRGAS ROU-98 (the reference ellipsoid is GRS80). The model is a combination of the EIGEN-6C4 geopotential model up to degree and order of 720, 10,429 land gravimetric stations plus 10,089 free air gravity anomalies in marine areas, based on the DTU13 model. The terrain data at the final 90 m resolution was taken from a 2017 Lidar survey in Uruguay with a 2.5 m initial resolution and SRTM (V2) for the external terrestrial data. The DT18 bathymetry model was used for the marine areas. Due to the total terrain data points (about 104 million), the overall area was divided into 4 overlapped blocks in the framework of the remove-compute-restore procedure. The reduced height anomalies were computed from the reduced gravity anomalies with Stokes 1D FFT and Wong Gore´s kernel modification (170-180 degrees). After adding back the residual terrain model effects and the contribution of the global geopotential model, the obtained quasi-geoid was transformed into a geoid model via Bouguer anomalies, even if the difference between the two models is just a few mm. A comparison with 51 GNSS/levelling stations shows a standard deviation of 10 cm. The geoid model is provided in ISG format 2.0 (ISG Format Specifications), while the file in its original data format is available at the model ISG webpage.
The official Uruguayan geoid model, called IGM110, was calculated by the Military Geographic Institute (IGM) in 2023 and consists of a grid of 1´ x 1´ geoidal undulations with a total of 151,981 points. The geodetic reference system is SIRGAS ROU-98 (the reference ellipsoid is GRS80). The extent is from 29.5° S to 35.5° S in latitude, and 52.5° W to 59.5° W in longitude, covering parts of Argentina and Brazil. The model is a combination of the EIGEN-6C4 geopotential model up to degree and order of 720, 10,429 land gravimetric stations plus 10,089 free air gravity anomalies in marine areas, based on the DTU13 model. The terrain data at the final 90 m resolution was taken from a 2017 Lidar survey in Uruguay with a 2.5 m initial resolution and SRTM (V2) for the external terrestrial data. The DT18 bathymetry model was used for the marine areas. Due to the total terrain data points (about 104 million), the overall area was divided into 4 overlapped blocks in the framework of the remove-compute-restore procedure. The reduced height anomalies were computed from the reduced gravity anomalies with Stokes 1D FFT and Wong Gore´s kernel modification (170-180 degrees). After adding back the residual terrain model effects and the contribution of the global geopotential model, the obtained quasi-geoid was transformed into a geoid model via Bouguer anomalies, even if the difference between the two models is just a few mm. A comparison with 51 GNSS/levelling stations shows a standard deviation of 10 cm. The resulting geoid was also adapted by a bias and a tilt to the national vertical system, Cabildo 1948, by fitting GNSS/levelling observations, with a mean of 1 cm and a standard deviation of 7 cm. The geoid model is provided in ISG format 2.0 (ISG Format Specifications), while the file in its original data format is available at the model ISG webpage.
The gravimetric geoid model xGGM23 was computed at the University of New Brunswick, Canada, with the aim to update the national geoid for Mexico, as well as to contribute to the construction of the regional geoid for North and Central America. Terrestrial gravimetry collected up to year 2020 was processed in spectral combination with the satellite-derived geopotential model GOCO06s (up to degree and order 230) using the UNB’s Stokes-Helmert technique. The geoid model is purely gravimetric, corresponds to the regional standard reference gravity potential for North America (Wo=6263656.0 m2/s2), tide-free gravity concept, and covers latitudes from 10° N to 40° N and longitudes from 125° W to 80° W, with a grid resolution of 2.5 arc minutes. This resolution is coherent with the densification of terrestrial gravity data collected inside Mexico. The accuracy of geoidal height is estimated as 10 cm inside Mexico and 5 cm in the southern US. The geoid model is provided in ISG format 2.0 (ISG Format Specifications), while the file in its original data format is available at the model ISG webpage.
The ColSHAWG-NGS2019 gravimetric geoid model has been computed by the US National Geodetic Survey (NGS). It has been worked out in the frame of the International Association of Geodesy Joint Working Group 2.2.2 "The 1 cm geoid experiment" and the so called "Colorado experiment". The area covered by the model is 251°E ≤ longitude ≤ 257°E, 36°N ≤ latitude ≤ 39°N with a grid spacing of 1' in both latitude and in longitude. The computation method is based on the spherical harmonic analysis scheme. The airborne gravity data are combined with the reference model xGEOID17RefB to produce an enhanced reference spherical harmonic model. This model is then used in a remove-compute-restore procedure, computing residual height anomalies from terrestrial gravity data by using the Wong-Gore modification of the Stokes kernel (truncation degree equal to 980), also including the g1 term because of rugged mountains. Finally, the geoid undulations are obtained by adding the geoid/quasi-geoid separation term (based on the simple Bouguer anomalies) to the computed height anomalies. The accuracy of the geoid model, when compared against GSVS17 GPS/leveling, is equal to 2.3 cm. The geoid model is provided in ISG format 2.0 (ISG Format Specifications), while the file in its original data format is available at the model ISG webpage.
DRUKGEOID2022 is the official geoid model of Bhutan, covering the area from 88.5°E to 92.5°E in longitude and from 26.5°N to 28.5°N in latitude with a grid resolution of 0.02°. It is an update of the previous DRUKGEOID2015 model, that was changed by a bias of 0.8761 m. This update was due to the change of the reference benchmark from the TH01 station at NLC headquarters to the more reliable THIZ station belonging to the national zero-order GNSS/levelling network. In this way, the resulting geoid can be used for the conversion from ellipsoidal heights in the DRUKREF03 system (ITRF2000 at epoch 2003.87) to orthometric heights in the national vertical datum, which is in turns connected to the Indian mean sea level through the neighboring benchmarks in the Indian states of West Bengal and Assam. Comparison of 27 GNSS/levelling benchmarks with DRUKGEOID2022 showed a standard deviation of 0.55 m. The geoid model is provided in ISG format 2.0 (ISG Format Specifications), while the file in its original data format is available at the model ISG webpage.
The WHU-GRACE-GPD01s models are the latest monthly gravity field solutions recovered from GRACE intersatellite geopotential difference (GPD) data processed at the School of Geodesy and Geomatics, Wuhan University, China. The intersatellite GPDs are estimated from GRACE Level-1B (RL03) data based on the improved energy balance equation and remove-compute-restore (RCR) technique, and the background models are consistent with GRACE Level-2 processing standards document (RL06). Further details are presented in Zhong et al. (2020, 2022). The WHU-GRACE-GPD01s models include two sets of GRACE monthly solutions: one is the unconstrained monthly solutions with the maximum degree and order of 60, the other is the constrained monthly solutions up to the maximum degree and order 96 with Kaula regularization constraint, and the optimal regularization parameter is determined using variance component estimation (VCE). This work is supported by the National Natural Science Foundation of China (No. 41974015, 41474019, 42061134007) and the Project Supported by the Special Fund of Hubei Luojia Laboratory (Grant No. 220100004).
The gravimetric quasi-geoid model for the State of Minas Gerais covers the longitude range of -38º to -53º and the latitude range of -12º to -25º, with a resolution of 5 arc minutes. A total of 49,067 terrestrial gravity values were utilized to compute Molodenski's gravity anomalies. The quasi-geoid model was computed by the Least Squares Collocation method. The XGM2019 geopotential model up to degree and order 300 was employed to represent the long-wavelengths of the gravity field. The digital terrain model SRTM15+ was selected for the RTM computation, while the DTU17 gravity field model was used in oceanic areas. The quasi-geoid model was validated against 136 GNSS/leveling stations, yielding a bias of 23 cm and a standard deviation of 11 cm. The geoid model is provided in ISG format 2.0 (ISG Format Specifications), while the file in its original data format is available at the model ISG webpage.
The ColLSMHA2021 geoid gravimetric model has been computed by the Gravity Research Group of the Department of Geomatics Engineering, Istanbul Technical University (ITU-GRG). This is an updated solution with respect to the ColLSMSA2020 geoid model, that has been computed in the frame of the International Association of Geodesy Joint Working Group 2.2.2 "The 1 cm geoid experiment". The area covered by the model is 109°W ≤ longitude ≤ 103°W, 36°N ≤ latitude ≤ 39°N with a grid spacing of 2' in both latitude and in longitude. The computation is based on the Least Squares Modification of Hotine Integral with Additive Corrections (LSMHA). In the computation, the XGM2016 global geopotential model up to degree/order 719 is used. Integration radius for Hotine integral is chosen as 0.5°. The error degree variance of gravity anomalies is constructed using a bandlimited white noise model where standard deviation is taken as 3 mGal. The input gravity data include terrestrial and airborne data combined using 3D Least-Squares Collocation (LSC). The accuracy of the geoid model over GSVS17 GPS/leveling is 2.7 cm. The geoid model is provided in ISG format 2.0 (ISG Format Specifications), while the file in its original data format is available at the model ISG webpage.
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