Displays

Electron density is the most important key parameter to describe the state of the ionospheric plasma varying with latitude, longitude, altitude and time. The upper atmosphere is decomposed into the four layers D, E, F1 and F2 of the ionosphere as well as the plasmasphere. Space weather events manifest themselves with specific "signatures" in distinct ionospheric layers. Therefore, the role of each layer in characterizing the ionosphere during nominal and extreme space weather events is highly important for scientific and operational purposes.

Accordingly, we model the total electron density as the sum of the electron densities of the individual layers. The key parameters of each layer, namely peak electron density, the corresponding peak height and scale height, are modeled by series expansions in terms of polynomial B-splines for latitude and trigonometric B-splines for longitude. The Chapman profile function is chosen to define the electron density along the altitude. This way, the electron density modeling is setup as a parameter estimation problem. In the case of modelling multiple layers simultaneously, the estimation of coefficients of the key parameters becomes challenging due to the correlations between the different key parameters.

One possibility to address the above issue is by imposing constraints on the ionospheric key parameters (and by extension on the B-spline coefficients). As an example, we constrain the F2 layer peak height to be always above the F1 layer peak height. We also constrain the key parameters to be non-negative and possibly to to certain well defined bounds. This way the physical properties of the ionosphere layers are included in the modelling. We estimate the coefficients with regard to the imposition of the bounds in form of inequality constraints using a convex optimization approach. We describe the underlying mathematical procedure and validate it using the IRI model as well as GNSS observations and electron density measurements from occultation missions. For the specific case of using IRI model data as the reference “truth”, we show the performance of the optimization algorithm using a “closed loop” validation. Such a validation allows an in-depth analysis of the impact of choosing a desired number of unknown coefficients to be estimated and the total number of constraints applied. We describe the parameterization of the different ionosphere key parameters considering the specific requirements from operational aspects (such as the need for modelling F2 layer), scientific aspects with regard to ionosphere-thermosphere studies (need for modelling the D, E or F1 layers) and also considering the aspects related to computation load.

We describe the advantages of using the optimization approach compared to the unconstrained least squares solution. While such constraints on key parameters can be fixed under nominal ionospheric conditions, but under adverse space weather effects these constraints need to be modified (constraints become stricter or more relaxed). For this purpose, we show the dynamic effect of modifying the constraints on global modelling performance and accuracy. We also provide the uncertainty of the estimated coefficients using a Monte-Carlo approach.

How to cite: Lalgudi Gopalakrishnan, G., Schmidt, M., and Erdogan, E.: Global Multi-layer Electron Density Modeling Based on Constraint optimization, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18785, https://doi.org/10.5194/egusphere-egu2020-18785, 2020.

The project OPTIMAP is at the current stage a joint initiative of BGIC, GSSAC and DGFI-TUM. The development of an operational tool for ionospheric mapping and prediction is the main goal of the project.

The ionosphere is a dispersive medium. Therefore, GNSS signals are refracted while they pass through the ionosphere. The magnitude of the refraction rate depends on the frequencies of the transmitted GNSS signals. The ionospheric disturbance on the GNSS signals paves the way of extracting Vertical Total Electron Content (VTEC) information of the ionosphere.

In OPTIMAP, the representation of the global and regional VTEC signal is based on localizing B-spline basis functions. For global VTEC modeling, polynomial B-splines are employed to represent the latitudinal variations, whereas trigonometric B-splines are used for the longitudinal variations. The regional modeling in OPTIMAP relies on a polynomial B-spline representation for both latitude and longitude.

The VTEC modeling in this study relies on both a global and a regional sequential estimator (Kalman filter) running in a parallel mode. The global VTEC estimator produces VTEC maps based on data from GNSS receiver stations which are mainly part of the global real-time IGS network. The global estimator relies on additional VTEC information obtained from a forecast procedure using ultra-rapid VTEC products. The regional estimator makes use of the VTEC product of the real-time global estimator as background information and generates high-resolution VTEC maps using real-time data from the EUREF Permanent GNSS Network. EUREF provides a network of very dense GNSS receivers distributed alongside Europe.

Carrier phase observations acquired from GPS, GLONASS and GALILEO constellations, which are transmitted in accordance with RTCM standard, are used for real-time regional VTEC modeling. After the acquisition of GNSS data, cycle slips for each satellite-receiver pair are detected, and ionosphere observations are constructed via the linear combination of carrier-phase observations in the data pre-processing step. The unknown B-spline coefficients, as well as the biases for each phase-continuous arc belonging to each receiver-satellite pair, are simultaneously estimated in the Kalman filter.

Within this study, we compare the performance of regional and global VTEC products generated in real-time using the well-known dSTEC analysis.

How to cite: Erdogan, E., Goss, A., Schmidt, M., Dettmering, D., Seitz, F., Müller, J., Görres, B., and Kersten, W. F.: Real-time regional VTEC modeling based on B-splines using real-time GPS, GLONASS and GALILEO observations, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-15908, https://doi.org/10.5194/egusphere-egu2020-15908, 2020.

An accurate estimation of the Thermospheric Neutral Density (TND) is important to compute drag forces acting on Low-Earth-Orbit (LEO) satellites and debris. Empirical thermospheric models are often used to compute TNDs (along-track of LEO satellites) for the Precise Orbit Determination (POD) experiments. However, recent studies indicate that the TNDs of available models do not perfectly reproduce TNDs derived from accelerometer observations. In this study, we use TND estimates from the Challenging Minisatellite Payload (CHAMP) and Gravity Recovery and Climate Experiment (GRACE) missions and merge them with the NRLMSISE00 from the Mass Spectrometer and Incoherent Scatter family. The integration is implemented by applying a simultaneous Calibration and Data Assimilation (C/DA) technique. The application of C/DA is advantageous since it uses model equation to interpolate and extrapolate TNDs that are not covered by CHAMP and GRACE. It also modifies the model's selected parameters to simulate TNDs that are closer to those of CHAMP and GRACE. The C/DA of this study is implemented daily using CHAMP- and/or GRACE-TNDs, while using the Ensemble Kalman Filter (EnKF) and Ensemble Square-Root Kalman Filter (EnSRF) as merger. Compared to the original model, on average, we found 27% (in the range of 2% to 56%) improvements in the estimation of TNDs. In addition, the results of the C/DA are compared with the TND outputs of the JB2008 model along the CHAMP and GRACE orbits, whose results indicate that the daily C/DA outputs are 60% closer to the observed TNDs (that are not used for the C/DA). Overall, our assessment indicates that EnSRF results in more realistic TND simulation and prediction compared to those derived from EnKF. We show that the improved TND estimates of this study will be beneficial for Precise Orbit Determination (POD) studies.  

Keywords: Thermosphere, Calibration and Data Assimilation (C/DA), NRLMSISE00, Ensemble Kalman Filter (EnKF), Ensemble Square-Root Kalman Filter (EnSRF)

How to cite: Forootan, E., Farzaneh, S., Kosary, M., and Schumacher, M.: How can Thermospheric Neutral Density (TND) estimates from CHAMP and GRACE accelerometer observations be used to improve empirical models?, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-369, https://doi.org/10.5194/egusphere-egu2020-369, 2020.

Multiple space geodetic techniques are capable of measuring effects caused by space weather events. In particular, space weather events can cause ionospheric disturbances correlated with variations in the vertical total electron content (VTEC) or the electron density (Ne) of the ionosphere.

In this regard and in the context of the new Focus Area on Geodetic Space Weather Research within IAG’s GGOS (International Association of Geodesy; Global Geodetic Observing System), the Joint Working Group 3 on Improved understanding of space weather events and their monitoring by satellite missions has been created as part of IAG Commission 4, Sub-Commission 4.3 to run for the next four years.

Within JWG3, we expect investigating different approaches to monitor space weather events using the data from different space geodetic techniques and, in particular, combinations thereof. Simulations will be beneficial to identify the contribution of different techniques and prepare for the analysis of real data. Different strategies for the combination of data will also be investigated, in particular, the weighting of estimates from different techniques in order to increase the performance and reliability of the combined estimates. Furthermore, existing algorithms for the detection and prediction of space weather events will be explored and improved to the extent possible. Furthermore, the geodetic measurement of the ionospheric electron density will be complemented by direct observations from the Sun gathered from existing spacecraft, such as SOHO, ACE, SDO, Parker Solar Probe, among others. The combination and joint evaluation of multiple datasets with the measurements of space geodetic observation techniques (e.g. geodetic VLBI) is still a great challenge. In addition, other indications for solar activity - such as the F10.7 index on solar radio flux, SOLERA as EUV proxy or rate of Global Electron Content (dGEC)-, provide additional opportunities for comparisons and validation.

Through these investigations, we will identify the key parameters useful to improve real-time/prediction of ionospheric/plasmaspheric VTEC, Ne estimates, as well as ionospheric perturbations, in case of extreme solar weather conditions. In general, we will gain a better understanding of space weather events and their effect on Earth’s atmosphere and near-Earth environment.

How to cite: Garcia-Rigo, A. and Soja, B.: New GGOS JWG3 on Improved understanding of space weather events and their monitoring, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20492, https://doi.org/10.5194/egusphere-egu2020-20492, 2020.

A major benefit of ground-based GNSS reflectometry (GNSS-R) over e.g. traditional tide gauge installations is the lower cost and basically maintenance-free operations. Still, a geodetic GNSS antenna is not exactly free of charge, so using cheaper equipment can make the technology available to even more people. With the ever increasing computing power and functionality in mobile phones and tablet computers, some new models are capable of recording raw GNSS data in e.g. RINEX-files. Therefore, they can act as a complete GNSS-R system, with both antenna, receiver, and processing done on a single unit. We make a proof of concept by using GNSS data received with a tablet computer to calculate sea level heights using spectral Lomb-Scargle retrievals. The latter strategy is used  for their low computational cost and simplicity. In comparing the resulting sea level retrievals to a traditional tide gauge and a geodetic quality GNSS-R installation, we show that the two GNSS-R installations perform on similar levels of precision. At the same time, the recorded GNSS data can also be used to derive the position of the tablet computer. Thus, mobile devices can be used as a cheap, and mobile, GNSS-R installation with possible applications in both oceanography and agriculture.

How to cite: Strandberg, J. and Haas, R.: Mobile GNSS reflectometry measurements, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7525, https://doi.org/10.5194/egusphere-egu2020-7525, 2020.

We present an updated 5′ ×5′ global geoid model 2020 (GGM2020), which is determined based on the shallow layer method (or simply Shen method). We choose an inner surface S below the EGM2008 global geoid by 15 m, and the layer bounded by the inner surface S and the Earths geographical surface E is referred to as the shallow layer. We formulate the 3D shallow mass layer model using the refined 5′ ×5′ crust density model, CRUST1.0-5min, which is an improved 5′ ×5′ density model of the CRUST1.0 with taking into account the corrections of the areas covered by ice sheets and the land-ocean crossing regions. Based on the shallow mass layer model and the gravity field EGM2008 that is defined in the region outside the Earth’s geographical surface E, we determine the gravity field model EGM2008S that is defined in the whole region outside the inner surface S. Based on the gravity field EGM2008S and the geoid equation W(P) =W0, where W0 is the geopotential constant on the geoid and P is the point on the geoid G, we established a 5′ ×5′ global geoid model GGM2020. Comparisons show that in average the GGM2020 fits the globally available GPS/leveling points better than the EGM2008 global geoid. This study is supported by NSFCs (grant Nos. 41721003, 41631072, 41874023, 41804012, 41429401, 41574007).

How to cite: Shen, W., Xie, Y., Han, J., and Li, J.: Development of a global geoid model 2020 (GGM2020) , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2072, https://doi.org/10.5194/egusphere-egu2020-2072, 2020.

The National Geospatial-Intelligence Agency [NGA], in conjunction with its U.S. and international partners, has completed its next Earth Gravitational Model (EGM2020), to replace EGM2008. The new ‘Earth Gravitational Model 2020’ [EGM2020] will retain the same harmonic basis and resolution as EGM2008. As such, EGM2020 will be a ellipsoidal harmonic model up to degree (n) and order (m) 2159, but will be released as a spherical harmonic model to degree 2190 and order 2159. EGM2020 has benefited from new data sources and procedures. Updated satellite gravity information from the GOCE and GRACE mission, will better support the lower harmonics, globally. Multiple new acquisitions (terrestrial, airborne and shipborne) of gravimetric data over specific geographical areas (Antarctica, Greenland …), will provide improved global coverage and resolution over the land, as well as for coastal and some ocean areas. Ongoing accumulation of satellite altimetry data as well as improvements in the treatment of this data, will better define the marine gravity field, most notably in polar and near-coastal regions. NGA and partners are evaluating different approaches for optimally combining the new GOCE/GRACE satellite gravity models with the terrestrial data. These include the latest methods employing a full covariance adjustment. NGA is also working to assess systematically the quality of its entire gravimetry database, towards correcting biases and other egregious errors where possible, and generating improved error models that will inform the final combination with the latest satellite gravity models. Outdated data gridding procedures have been replaced with improved approaches. For EGM2020, NGA intends to extract maximum value from the proprietary data that overlaps geographically with unrestricted data, whilst also making sure to respect and honor its proprietary agreements with its data-sharing partners.

How to cite: Barnes, D., Barnes, D., Beale, J., Small, H., and Ingalls, S.: Introducing EGM2020, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9884, https://doi.org/10.5194/egusphere-egu2020-9884, 2020.

Spherical harmonic synthesis (SHS) can be used to compute various gravity functions (e.g., geoid undulations, height anomalies, deflections of vertical, gravity disturbances, gravity anomalies, etc.) using the 4pi fully normalised Stokes coefficients from the many freely available Global Geopotential Models (GGMs).  This requires a normal ellipsoid and its gravity field, which are defined by four parameters comprising (i) the second-degree even zonal Stokes coefficient (J2) (aka dynamic form factor), (ii) the product of the mass of the Earth and universal gravitational constant (GM) (aka geocentric gravitational constant), (iii) the Earth’s angular rate of rotation (ω), and (iv) the length of the semi-major axis (a). GGMs are also accompanied by numerical values for GM and a, which are not necessarily identical to those of the normal ellipsoid.  In addition, the value of W_0, the potential of the geoid from a GGM, needs to be defined for the SHS of many gravity functions. W₀ may not be identical to U₀, the potential on the surface of the normal ellipsoid, which follows from the four defining parameters of the normal ellipsoid.  If W₀ and U₀ are equal and if the normal ellipsoid and GGM use the same value for GM, then some terms cancel when computing the disturbing gravity potential.  However, this is not always the case, which results in a zero-degree term (bias) when the masses and potentials are different.  There is also a latitude-dependent term when the geometries of the GGM and normal ellipsoids differ.  We demonstrate these effects for some GGMs, some values of W₀, and the GRS80, WGS84 and TOPEX/Poseidon ellipsoids and comment on its omission from some public domain codes and services (isGraflab.m, harmonic_synth.f and ICGEM).  In terms of geoid heights, the effect of neglecting these parameters can reach nearly one metre, which is significant when one goal of modern physical geodesy is to compute the geoid with centimetric accuracy.  It is also important to clarify these effects for all (non-specialist) users of GGMs.

How to cite: Goyal, R., Claessens, S., Featherstone, W., and Dikshit, O.: Subtleties in spherical harmonic synthesis of the gravity field , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-59, https://doi.org/10.5194/egusphere-egu2020-59, 2020.

Based on the absolute gravity measurements of 4 gravimetric stations (Shigatse, Zhongba, Lhasa and Naqu) in southern Tibet surveyed from 2010 to 2013, we modeled the source region as a disk of 580 km in diameter by Hypocentroid model, shown that the gravity increase at these stations may be related to mass changes in the source region of the 2015 Mw7.8 Nepal earthquake. We analyzed the characteristics of gravity variations from the repeated regional gravity network, which including the 4 absolute gravimetric stations and 13 relative gravimetric stations from 2010 to 2019, to study the characteristics of gravity changes before and after the earthquake.

We firstly estimated the reliability of the absolute gravity measurements by the errors of each station, and considered the effect of vertical displacement, denudation of surface mass, GIA correction and the secular and background gravity changes. Secondly we employed the Bayesian adjustment method for the relative gravimetric network data analysis, which was more robust and adaptive for solving problems caused by irregular nonlinear drift of different gravimeters, and then carried out error analysis for the repeated relative gravity measurements. Furthermore, we took the Shigatse station as example, which covered absolute and relative measurements and was most close to the Hypocenter of the inversion Hypocentroid model, the hydrologic effects of the Shigatse station was modeled exactly, and the results shown that the secular and background gravity changes were much smaller than the observed gravity changes. Lastly we studied the characteristics of gravity changes before and after the earthquake through the Hypocentroid model, we found the coincident gravity increase both in absolute and repeated regional gravity results before the earthquake, and gravity decreased after the earthquake, which suggested that the pre-earthquake gravity increase may be caused by strain and mass (fluid) transfer in broad seismogenic source regions of the earthquake. Moreover, the study indicated that high-precision ground gravity measurements (absolute and relative) may provide a useful method for monitoring mass changes in the source regions of potential large earthquakes.

Acknowledgment: This research is supported by National Key R&D Program of China (Grant No.2018YFC1503806 and No.2017YFC1500503) and National Natural Science Foundation of China (Grant No.U1939205 and No.41774090).

How to cite: Xu, W., Chen, S., and Lu, H.: Gravity changes before and after the 2015 Mw7.8 Nepal earthquake, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4304, https://doi.org/10.5194/egusphere-egu2020-4304, 2020.

Accurate calculation of displacements due to glacial isostatic adjustment (GIA) are essential for studies of tectonics, sea level projection, and the estimation of recent ice melting or other mass transport. However, most GIA studies to date have used a 1D viscosity model, with earth parameters varying only in the radial direction, while surface geology and seismic tomography show that the thickness of the lithosphere and the structure of the mantle also varies laterally. Therefore, models with 3D earth structure are needed. Using a 3D earth model requires finite element models, which are computationally expensive and hence make it difficult to compute a wide range of potential parameter values. Consequently, the question is for which application is a 3D model necessary, and for which parameters (and where) do 1D models give sufficiently accurate predictions?

In this study, we investigate the sensitivity of the GIA modeling to the earth structure, using the Abaqus finite element analysis software, an ice model assumed to be known, and various viscosity models. We start with Patagonia as a test region, because the 3D structure of the mantle is complex due to the proximity of the subduction of the Antarctic plate below South American and the Chile triple junction. In this region, the GIA contributes significantly to the regional recent rapid uplift.

How to cite: Prevost, P. and Freymueller, J.: Comparison of 1D vs 3D viscosity models for glacial isostatic adjustment, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12331, https://doi.org/10.5194/egusphere-egu2020-12331, 2020.

We have modelled the surface volume and gravity changes caused by the three mainshocks (moment magnitudes Mw 6.0, 5.9, 6.5) occurred during the last seismic period started on 2016, August 24 in central Italy. Our calculations start from the source parameters estimated by the inversion of the largest dataset of InSAR and GNSS observations ever managed in Italy after earthquake occurrences, based on the half-space elastic dislocation theory. The vertical displacements modelled after the 2016 events allow to infer a substantial unbalance between the subsided and uplifted volumes. In particular, we detected ~106∙10⁶ m³ of hangingwall subsidence against ~37∙10⁶ m³ of footwall uplift, that accounts for ~74% of the total volume mobilization. From the ratio between the footwall and total deformed volumes, we have computed an average fault dip of ~47°, in line with the values retrieved by seismological methods. The total gravity variations which affected the study area are of the order of ~1 μGal (1 μGal = 10⁻⁸ ms⁻²) in the far field, and ~170 μGal in the near field.
The area affected within a gravity change of 1 μGal is ~140 km long and ~57 km wide, parallel to the Apennines chain. The larger contribution is given by positive variations which account for the tensional style of deformation and larger subsided area.

How to cite: Riguzzi, F., Tan, H., and Shen, C.: Expected impact of the 2016 central Italy earthquakes on the local gravity field , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7083, https://doi.org/10.5194/egusphere-egu2020-7083, 2020.

In 2018 INGV funded a project aimed to detect gravity variations and ground deformations over different time-scale possibly associated with the postseismic relaxation affecting the area where the recent seismic events of L'Aquila (2009 Mw 6.3) and Amatrice-Norcia (2016 Mw 6.1 and 6.5) took place. To this aim a network of five absolute gravity stations was realized (Terni, Popoli, Sant’Angelo Romano, L’Aquila University and L'Aquila Laboratori Nazionali del Gran Sasso). The site of L'Aquila University was chosen since location of the permanent GNSS station (AQUI) managed by the Italian Space Agency and contributing to the EUREF network. AQUI is continuously operating on the roof of the Science Faculty (Coppito, L'Aquila).

In the basement of the same building we realized the absolute gravimetric station (AQUIg), indoor the Geomagnetic laboratory of the Physics Department. This is one of the numerous applications where satellite systems must be integrated with traditional terrestrial surveying techniques. These include the case of underground or indoor gravimetric surveys, where the height of the gravimetric reference point should be determined precisely starting from an outdoor reference point with known coordinates. In this case, the use of classical observation techniques and instruments (e.g., total stations, levels) is crucial to measure the height difference between a reference GNSS station and a gravimetric benchmark. We will draw the steps followed to estimate the height difference between AQUIg and AQUI by a classical topographic survey and therefore the height of AQUIg from estimating first the height of AQUI.

How to cite: Mazzoni, A., Fortunato, M., Sonnessa, A., Berrino, G., Greco, F., and Riguzzi, F.: Indoor height determination of the new absolute gravimetric station of L'Aquila, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8834, https://doi.org/10.5194/egusphere-egu2020-8834, 2020.

Absolute gravity time series are available at various stations in Norway. The data have mainly been used for investigation of secular variations due to glacial isostatic adjustment. Previous work indicates that some of the estimated gravity trends suffer from unmodeled geophysical effects, like hydrological mass variations. Here we try to correct for hydrological effects by employing a combination of global and regional hydrological models. We use gravity data at two locations in the Norwegian network (NMBU and TRYC) which have frequently been observed with the absolute gravimeter FG5-226. 

For computing the gravity corrections, we test various Global Hydrological Models (GHMs) and combine them with a Regional Runoff Model (RRM) for Norway, run by the Norwegian Water Resources and Energy Directorate (NVE). We distinguish between an outer and an inner zone. In the outer zone, Newtonian attraction and loading effects are derived from the GHMs, while the RRM is used in the inner zone. Both types of models provide information on soil moisture and snow layers. The RRM provides groundwater variations in addition. Furthermore, we try to consider the ‘umbrella effect’ that accounts for local disturbances in subsurface water flow caused by the existence of the building in which the gravity site is located.  

Neglecting the GIA trend, both NMBU and TRYC gravity time series show different amplitude and pattern. NMBU shows a lower amplitude, and with no prominent periodic pattern in the data, while TRYC shows the opposite. Significant discrepancies occurring in the NMBU gravity dataset between 2014 and 2015 are likely due to an instrumental effect, such as maintenance. The total modelled hydrological signal ranges from -4 and 4 µGal. Application of the correction reduces the standard deviation in the gravity time series, at its best, by about 33% or 0.8 µGal for NMBU, and by about 43% or two µGal for TRYC. Secular gravity rates have been derived from both, the uncorrected and the corrected time series. We find that application of the hydrological correction improves the fit of the computed secular gravity rates as compared to rates derived from the state-of-the-art Fennoscandian land uplift model NKG2016LU_abs. The uncorrected trends are 75% and 50% of the expected trend (0.77 and 1.12 µGal/year), while the hydrological corrections improve the fit to 82% and 93% for NMBU and TRYC, respectively.

How to cite: Bramanto, B., Ophaug, V., Gerlach, C., and Breili, K.: Can we use regional runoff models for correcting time series of absolute gravimetry?, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-544, https://doi.org/10.5194/egusphere-egu2020-544, 2020.

we propose a method to apply the polynomial fitting for regional-residual separation of microgravity data based on the characteristics of gravity anomaly without a prior information. Since the microgravity survey is usually carried out in small regions, it is common to approximate regional anomaly by the first-order polynomial plane. However, if the regional anomaly patterns are unsuited to be approximated to a first-order plane, the complete gravity anomaly is divided into small zones enough to approximate first-order plane by means of Parasnis density estimation method. The regional-residual separation is then applied on the splitted zones individually. When the gravity anomalies can be splitted spatially, we showed that the residual anomalies can be more effectively extracted based on the regional geological structures by regional anomaly separation from each of the divided regions, rather than applying the entire data set at one time.

Acknowledgment: This work was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea government(MSIT) (No. 2019R1F1A1055093).

How to cite: Rim, H., Park, G., and Kim, C.-R.: Regional-residual separation of microgravity data based on data clustering, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2493, https://doi.org/10.5194/egusphere-egu2020-2493, 2020.

Airborne gravimetry has become increasingly important for geoid modeling because of its capability of collecting large scale gravity data over difficult areas. In order to quantify the contribution of airborne gravity data for geoid determination, two regions with distinct topographical condition, a hilly desert area in Mu Us of China and a mountainous region in Colorado of the USA were selected for gravimetric geoid modeling experiment. The gravimetric geoid model computed by combining satellite gravity model, terrestrial and airborne gravity data fits with GPS leveling data to 0.8 cm for Mu Us case and 5.3 cm for Colorado case. The contribution of airborne gravity data to the signal and accuracy improvement of the geoid was quantitatively evaluated for different spatial distribution and density of terrestrial gravity data. The results demonstrate that in the cases of the spacing of terrestrial gravity points exceeds 15 km, the additions of airborne gravity data improve the accuracies of gravimetric geoid models by 11.1%~48.3% for Mu Us case and 13%~20% for Colorado case.

How to cite: Jiang, T., Dang, Y., and Zhang, C.: Quantifying the contribution of airborne gravity data for geoid modeling: two case studies, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-17734, https://doi.org/10.5194/egusphere-egu2020-17734, 2020.

In this paper, by combining the Global Geopotential Model (GGM, specifically, EGM2008 is used) and the Residual Terrain Model (RTM) data, we have modeled the Gravity Gradient Tensor (GGT) in eastern Tian shan mountains areas, China. The RTM data are obtained from the Shuttle Radar Topography Mission (SRTM) elevation model and the DTM2006.0 high degree spherical harmonic reference surface. The integration of RTM data reduces the truncation errors (or called omission errors) due to the finite expansion terms of the spherical harmonic coefficients of the GGM, and compensates for the high frequency information and spatial resolution of the GGT within the study area.

How to cite: Liu, J.: Combining GGM and RTM to model the gravity gradient tensor, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4407, https://doi.org/10.5194/egusphere-egu2020-4407, 2020.

Solid Earth is affected by tidal cycles triggered by the gravity attraction of the celestial bodies. However, about 70% the Earth is covered with seawater which is also affected by the tidal forces. In the coastal areas, the ocean tide loading (OTL) can reach up to 10% of the earth tide, 90% for tilt, and 25% for strain (Farrell, 1972). Since 2007, a high-precision continuous gravity observation network in China has been established with 78 stations. The long-term high-precision tidal data of the network can be used to validate, verifying and even improve the ocean tide model (OTM).

In this paper, tidal parameters of each station were extracted using the harmonic analysis method after a careful editing of the data. 8 OTMs were used for calculating the OTL. The results show that the Root-Mean-Square of the tidal residuals (M₀) vary between 0.078-1.77 μgal, and the average errors as function of the distance from the sea for near(0-60km), middle(60-1000km) and far(>1000km) stations are 0.76, 0.30 and 0.21 μgal. The total final gravity residuals (Tx) of the 8 major constituents (M₂, S₂, N₂, K₂, K₁, O₁, P₁, Q₁) for the best OTM has amplitude ranging from 0.14 to 3.45 μgal. The average efficiency for O₁ is 77.0%, while 73.1%, 59.6% and 62.6% for K₁, M₂ and Tx. FES2014b provides the best corrections for O₁ at 12 stations, while SCHW provides the best for K_{1 ,}M₂and Tx at 12,8and 9 stations. For the 11 costal stations, there is not an obvious best OTM. The models of DTU10, EOT11a and TPXO8 look a litter better than FES2014b, HAMTIDE and SCHW. For the 17 middle distance stations, SCHW is the best OTM obviously. For the 7 far distance stations, FES2014b and SCHW model are the best models. But the correction efficiency is worse than the near and middle stations’.

The outcome is mixed: none of the recent OTMs performs the best for all tidal waves at all stations. Surprisingly, the Schwiderski’s model although is 40 years old with a coarse resolution of 1° x 1° is performing relative well with respect to the more recent OTM. Similar results are obtained in Southeast Asia (Francis and van Dam, 2014). It could be due to systematic errors in the surroundings seas affecting all the ocean tides models. It's difficult to detect, but invert the gravity attraction and loading effect to map the ocean tides in the vicinity of China would be one way.

How to cite: Tan, H., Shen, C., and Wu, G.: Evaluation of global ocean tide models based on tidal gravity observations in China, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3297, https://doi.org/10.5194/egusphere-egu2020-3297, 2020.

This paper presents a general overview of gravimetric measurements carried out for the first order gravimetric network of Albania.   Data compensation, correction methodologies, interpretation and related results have been presented as well. Relative gravimetric measurements were carried out in 42points,  with two CG-5 instruments. Real Vertical Gradients have been measured at all the points of first order network which together with other corrections,  are used in the final data compensation in order to bring the final values at reference point as absolute ones. Apart from the first order network, other 38 second order and 138 third order gravimetric points have been measured in a grid 2x2 km, in the  flat and most dense area (Tirana-Durresi) of Albania,  with the  scope the determination of  Geoid Gravimetric Height on that region. The gravimetric measurements were realized with two Scintrex CG-5 gravimeters for three orders. For the first order points were used two gravimeters simultaneously, whereas for the points of second and third order only one. In this paper we present the results for only the first order measurements. The measurements were carried out during the period from August to October 2018, in collaboration with Aristotle University of Thessaloniki, Department of Geophysics. The project was supported by the Agency of Geospatial Information of Albania.

How to cite: Reci, H., Stampolidis, A., Ndoj, P., Tsokas, G., Pašteka, R., Hábel, B., Bushati, S., and Qirko, K.: Gravity networks for the Geodetic Reference Framework of Albania, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11518, https://doi.org/10.5194/egusphere-egu2020-11518, 2020.

The digital zenith camera VESTA (VErtical by STArs) was designed by the Institute of Geodesy and Geoinformatics (GGI) of the University of Latvia and completed in 2016. By 2020 more than 400 terrestrial vertical deflection measurements were observed in the territory of Latvia. These observations were post-processed by the GGI developed software and the accuracy was evaluated at 0.1 arc seconds. In 2019 two new cameras have been developed, which will be used in future projects, e.g., in determination of properties of local geological structure or Earth crust movement monitoring. Measurement control software corrections and complements, data processing improvements and automation and transition to GAIA data release 2 star catalog were done. The accuracy of the measurements of improved camera was evaluated at 0.05 arc seconds.

Terrestrial vertical deflection observations were compared with global geopotential models, e.g. GGM+ and EGM2008. The results show a better correspondence with GGM+ model by evaluating the standard deviation: 0.314 and 0.307 arc seconds for ξ and η components respectively in comparison to 0.346 and 0.358 arc seconds for ξ and η components for EGM2008 model. The comparisons of average and minimum/maximum differences are introduced in this study for better evaluation of the results. Moreover, vertical deflections have been used as additional terrestrial data in DFHRS (Digital Finite-element Height Reference Surface) software v. 4.3 in combination with GNSS/levelling data (B, L, hH) and global geopotential model EGM2008 for gravity field and quasi-geoid improvement (www.dfhbf.de). This approach is based on parametric modelling and computation of height reference surfaces (HRS) from geometric and physical observation components in a hybrid adjustment approach. The results of the computed quasi-geoid models using different types of data are introduced in this research, representing several solutions, as well as these solutions are compared with the national quasi-geoid model LV’14.

How to cite: Morozova, K., Silabriedis, G., Zarins, A., Balodis, J., and Jaeger, R.: The digital zenith camera as an additional technique for quasi-geoid model determination of Latvia, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20420, https://doi.org/10.5194/egusphere-egu2020-20420, 2020.

Gravity and magnetic surveys are widely used in geology exploration because of its advantages, such as efficient and economy, green and environment-friendly, widely coverage and strong horizontal resolution. In order to well study in the geology exploration, it is required to comprehensively combine the different scales (different scales data) and different dimensions (satellite data, aeronautical data, ground data, ocean data, well data, etc.) of gravity and magnetic data that were observed in different periods, however, the comprehensive application of the multi-dimensional and multi-scale gravity and magnetic data still stays in the initial stage. In this paper, we do research on the key point of the fusion of potential field data (gravity and magnetic data): the way to fuse the different scales and different dimensions of potential field data into a benchmark and the same surface. Based on this research, we propose a scheme to fuse the multi-dimensional and multi-scale gravity and magnetic data. The synthetic models show that this fusion scheme is able to fuse the multi-dimensional and multi-scale gravity and magnetic data with great fusion results and small errors, in addition, the most important is that the fusion data conform to the characteristics of the potential field data and can meet the needs of data processing in the following steps. One of case studies in China has been accomplished to fuse aeronautical and ground gravity data that are different scales by using this fusion scheme. The fusion scheme we proposed in this study can be used in the fusion of the multi-dimensional (aeronautical, ground and ocean) and multi-scale gravity and magnetic data, which is good for interpretation and popularization.

How to cite: Ji, X., Wang, W., Liu, F., Yang, M., Xiong, S., and Ma, J.: Preliminary Study on Fusion Scheme of Multi-dimensional and Multi-scale Potential Field Data, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6651, https://doi.org/10.5194/egusphere-egu2020-6651, 2020.

Coastline extraction and decisions have important implications for efficient land management and national policy formulation. Therefore, shorelines should be determined in a reasonable manner, and consistent results should be produced for the same area. This must be calculated efficiently. For example, simple shoreline areas should be constructed using relatively large vertex intervals (point-to-point distances) for efficiency, while complex shoreline areas should be constructed using small vertex intervals, thus improving accuracy. In this study, we suggest an optimum vertex interval that can represent more than 99.7% (3σ) of the original shoreline data using a grid generated by applying a box-counting method. All coastline areas were gridded using 11 grid sizes. Generalization was performed on the shorelines contained within each grid, and the sum of the generalized shoreline lengths was calculated. As the grid size used increases, the shoreline will become more simplified, and the difference from the original data will increase. As the grid size decreases, the more precisely the shoreline will be represented, and the sum will be similar to the original value. As a result of regression analysis, using the sum of the generalized shoreline length, we could predict the vertex interval that would represent more than 99.7% (3σ) of the original data. For the experiment, three regions with distinct coastline characteristics were selected. The grid was generated by the box-counting method, a representative fractal technique, and the vertex interval was estimated. From this, the fractal dimension was then calculated. As a result of the experiment, it was confirmed that the area A had a vertex interval of 0.7m, and the areas B and C had vertex intervals of 1m. These optimal vertex interval values mean that when the coastline was reconstructed, it was the closest, efficient representation of the actual coastline. Furthermore, these interval values suggest that the area A has a more complex coastline, and therefore the coastline should be constructed with a smaller vertex interval than the other areas. Using fractal dimensions, we also found that the area B has a more complex coastline than the area C. Overall, we confirmed that the optimal vertex interval for the accurate and efficient construction of the shoreline is able to be calculated by the approach presented in this paper. This research is expected to contribute to efficient land management and national policy establishment and progress. 

How to cite: Woo, H. S., Kwon, K. S., and Kim, B. G.: Optimal Vertex Interval Determination for Efficient Shoreline Length Calculation, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18453, https://doi.org/10.5194/egusphere-egu2020-18453, 2020.