ALBERT

All Library Books, journals and Electronic Records Telegrafenberg

feed icon rss

Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
  • 1
    Publication Date: 2018-05-18
    Description: Ultra-sensitive space-borne accelerometers on board of low Earth orbit (LEO) satellites are used to measure non-gravitational forces acting on the surface of these satellites. These forces consist of the Earth radiation pressure, the solar radiation pressure and the atmospheric drag, where the first two are caused by the radiation emitted from the Earth and the Sun, respectively, and the latter is related to the thermospheric density. On-board accelerometer measurements contain systematic errors, which need to be mitigated by applying a calibration before their use in gravity recovery or thermospheric neutral density estimations. Therefore, we improve, apply and compare three calibration procedures: (1) a multi-step numerical estimation approach, which is based on the numerical differentiation of the kinematic orbits of LEO satellites; (2) a calibration of accelerometer observations within the dynamic precise orbit determination procedure and (3) a comparison of observed to modeled forces acting on the surface of LEO satellites. Here, accelerometer measurements obtained by the Gravity Recovery And Climate Experiment (GRACE) are used. Time series of bias and scale factor derived from the three calibration procedures are found to be different in timescales of a few days to months. Results are more similar (statistically significant) when considering longer timescales, from which the results of approach (1) and (2) show better agreement to those of approach (3) during medium and high solar activity. Calibrated accelerometer observations are then applied to estimate thermospheric neutral densities. Differences between accelerometer-based density estimations and those from empirical neutral density models, e.g., NRLMSISE-00, are observed to be significant during quiet periods, on average 22 % of the simulated densities (during low solar activity), and up to 28 % during high solar activity. Therefore, daily corrections are estimated for neutral densities derived from NRLMSISE-00. Our results indicate that these corrections improve model-based density simulations in order to provide density estimates at locations outside the vicinity of the GRACE satellites, in particular during the period of high solar/magnetic activity, e.g., during the St. Patrick's Day storm on 17 March 2015.
    Print ISSN: 0992-7689
    Electronic ISSN: 1432-0576
    Topics: Geosciences , Physics
    Published by Copernicus on behalf of European Geosciences Union.
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
  • 2
    Publication Date: 2017-11-27
    Description: Measuring the spatiotemporal variation of ocean mass allows one to partition volumetric sea level change, sampled by radar altimeters, into a mass-driven and a steric part, the latter being related to ocean heat change and the current Earth’s energy imbalance. Since 2002, the Gravity Recovery and Climate Experiment (GRACE) mission provides estimates of the Earth’s time-variable gravity field, from which one can derive ocean mass variability. However, GRACE has reached the end of its lifetime with data degradation and several gaps during the last years, and there will be a prolonged gap until the launch of the follow-on mission GRACE-FO. Therefore, efforts focus on generating a long and consistent ocean mass time series by analyzing kinematic orbits from other low-flying satellites; i.e. extending the GRACE time series. Here we utilize data from the European Space Agency’s (ESA) Swarm Earth Explorer satellites to derive and investigate ocean mass variations. We investigate the potential to bridge the gap between the GRACE missions and to substitute missing monthly solutions. Our monthly Swarm solutions have a root mean square error (RMSE) of 4.0 mm with respect to GRACE, whereas directly estimating trend, annual and semiannual signal terms leads to an RMSE of only 1.7 mm. Concerning monthly gaps, our Swarm solution appears better than interpolating existing GRACE data in 13.5 % of all cases, for 80.0 % of all investigated cases of an 18-months-gap, Swarm ocean mass was found closer to the observed GRACE data compared to interpolated GRACE data. Furthermore, we show that precise modelling of non-gravitational forces acting on the Swarm satellites is the key for reaching these accuracies. Our results have implications for sea level budget studies, but they may also guide further research in gravity field analysis schemes, including non-dedicated satellites.
    Electronic ISSN: 1869-9537
    Topics: Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
  • 3
    Publication Date: 2018-03-23
    Description: Measuring the spatiotemporal variation of ocean mass allows for partitioning of volumetric sea level change, sampled by radar altimeters, into mass-driven and steric parts. The latter is related to ocean heat change and the current Earth's energy imbalance. Since 2002, the Gravity Recovery and Climate Experiment (GRACE) mission has provided monthly snapshots of the Earth's time-variable gravity field, from which one can derive ocean mass variability. However, GRACE has reached the end of its lifetime with data degradation and several gaps occurred during the last years, and there will be a prolonged gap until the launch of the follow-on mission GRACE-FO. Therefore, efforts focus on generating a long and consistent ocean mass time series by analyzing kinematic orbits from other low-flying satellites, i.e. extending the GRACE time series. Here we utilize data from the European Space Agency's (ESA) Swarm Earth Explorer satellites to derive and investigate ocean mass variations. For this aim, we use the integral equation approach with short arcs (Mayer-Gürr, 2006) to compute more than 500 time-variable gravity fields with different parameterizations from kinematic orbits. We investigate the potential to bridge the gap between the GRACE and the GRACE-FO mission and to substitute missing monthly solutions with Swarm results of significantly lower resolution. Our monthly Swarm solutions have a root mean square error (RMSE) of 4.0 mm with respect to GRACE, whereas directly estimating constant, trend, annual, and semiannual (CTAS) signal terms leads to an RMSE of only 1.7 mm. Concerning monthly gaps, our CTAS Swarm solution appears better than interpolating existing GRACE data in 13.5 % of all cases, when artificially removing one solution. In the case of an 18-month artificial gap, 80.0 % of all CTAS Swarm solutions were found closer to the observed GRACE data compared to interpolated GRACE data. Furthermore, we show that precise modeling of non-gravitational forces acting on the Swarm satellites is the key for reaching these accuracies. Our results have implications for sea level budget studies, but they may also guide further research in gravity field analysis schemes, including satellites not dedicated to gravity field studies.
    Print ISSN: 1869-9510
    Electronic ISSN: 1869-9529
    Topics: Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
  • 4
    Publication Date: 2018-09-21
    Print ISSN: 0949-7714
    Electronic ISSN: 1432-1394
    Topics: Architecture, Civil Engineering, Surveying , Geosciences
    Published by Springer
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
  • 5
    Publication Date: 2018-02-26
    Print ISSN: 0949-7714
    Electronic ISSN: 1432-1394
    Topics: Architecture, Civil Engineering, Surveying , Geosciences
    Published by Springer
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
  • 6
    Publication Date: 2020-12-23
    Description: A new approach to recover time-variable gravity fields from satellite laser ranging (SLR) is presented. It takes up the concept of lumped coefficients by representing the temporal changes of the Earth’s gravity field by spatial patterns via combinations of spherical harmonics. These patterns are derived from the GRACE mission by decomposing the series of monthly gravity field solutions into empirical orthogonal functions (EOFs). The basic idea of the approach is then to use the leading EOFs as base functions in the gravity field modelling and to adjust the respective scaling factors straightforward within the dynamic orbit computation; only for the lowest degrees, the spherical harmonic coefficients are estimated separately. As a result, the estimated gravity fields have formally the same spatial resolution as GRACE. It is shown that, within the GRACE time frame, both the secular and the seasonal signals in the GRACE time series are reproduced with high accuracy. In the period prior to GRACE, the SLR solutions are in good agreement with other techniques and models and confirm, for instance, that the Greenland ice sheet was stable until the late 1990s. Further validation is done with the first monthly fields from GRACE Follow-On, showing a similar agreement as with GRACE itself. Significant differences to the reference data only emerge occasionally when zooming into smaller river basins with strong interannual mass variations. In such cases, the approach reaches its limits which are set by the low spectral sensitivity of the SLR satellites and the strong constraints exerted by the EOFs. The benefit achieved by the enhanced spatial resolution has to be seen, therefore, primarily in the proper capturing of the mass signal in medium or large areas rather than in the opportunity to focus on isolated spatial details.
    Print ISSN: 0949-7714
    Electronic ISSN: 1432-1394
    Topics: Architecture, Civil Engineering, Surveying , Geosciences
    Published by Springer
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
  • 7
    Publication Date: 2021-04-18
    Print ISSN: 0094-8276
    Electronic ISSN: 1944-8007
    Topics: Geosciences , Physics
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
  • 8
    Publication Date: 2022-01-21
    Description: Abstract
    Description: Monthly gravity fields from Swarm A, B, and C, using the integral equation approach with short arcs. Software: GROOPS; Approach: Short-arc approach (Mayer-Gürr, 2006); Kinematic orbit product: IfG Graz: https://ftp.tugraz.at/outgoing/ITSG/satelliteOrbitProducts/operational/Swarm-1/kinematicOrbit/; Arc length: 45 minutes; Reference GFM: GOCO06s (Kvas et. al, 2021), monthly mean has been added back to the solution; Drag model: NRLMSIS2; SRP and EARP and EIRP models: Vielberg & Kusche (2020); Empirical parameters: + for non-gravitational accelerations (sum of Drag+SRP+EIRP+EARP): Bias per arc and direction; + for Drag: Scale per arc and direction; + for radiation pressure (sum of SRP+EIRP+EARP): Scale per day and direction; Non-tidal model: Atmosphere and Ocean De-aliasing Level 1B RL06 (Dobslaw et al., 2017); Ocean tidal model: 2014 finite element solution FES2014b (Carrere et al., 2015); Atmospheric tidal model: AOD1B RL06 atmospheric tides ; Solid Earth tidal model: IERS2010; Pole tidal model: IERS2010; Ocean pole tidal model: IERS2010 (Desai 2002); Third-body perturbations: Sun, Moon, Mercury, Venus, Mars, Jupiter, and Saturn, following the JPL DE421 Planetary and Lunar Ephemerides (Folkner et al., 2014).
    Keywords: Swarm ; monthly gravity field model ; ICGEM ; geodesy ; global gravity field model ; EARTH SCIENCE 〉 SOLID EARTH 〉 GEODETICS ; EARTH SCIENCE 〉 SOLID EARTH 〉 GRAVITY/GRAVITATIONAL FIELD
    Type: Dataset , Dataset
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
  • 9
    Publication Date: 2022-03-25
    Description: A major problem in the precise orbit determination (POD) of satellites at altitudes below 1,000 km is the modeling of the aerodynamic drag which mainly depends on the thermospheric density and causes the largest non‐gravitational acceleration. Typically, empirical thermosphere models are used to calculate density values at satellite positions but current thermosphere models cannot provide the required accuracy. Thus, unaccounted variations in the thermospheric density may lead to significantly incorrect satellite positions. For the first time, we bring together thermospheric density corrections for the NRLMSISE‐00 model in terms of scale factors with a temporal resolution of 12 hr derived from satellite laser ranging (SLR) and accelerometer measurements. Whereas, the latter are in situ information given along the satellite orbit, SLR results have to be interpreted as mean values along the orbit within the underlying time interval. From their comparison, we notice a rather similar behavior with correlations of up to 80% and more depending on altitude. During high solar activity, scale factors vary around 30% at low solar activity and up to 70% at high solar activity from the value one. In addition, we found the scaled thermospheric density decreasing stronger as the modeled density of NRLMSISE‐00. To check the reliability of the SLR‐derived scale factors, we compare the POD result of two different software packages, namely DOGS‐OC from DGFI‐TUM and GROOPS from IGG Bonn. Furthermore, a validation of our estimated scale factors with respect to an external data set proofs the high quality of the obtained results.
    Description: Plain Language Summary: Variations in the density of the thermosphere must be taken into account when modeling and predicting the motion of satellites in the near‐Earth environment. Typically, thermospheric densities at the position of satellites are provided by models, but their accuracy is limited. Due to the sensitivity of satellites orbiting the Earth in the altitude range of the thermosphere, they can be used to derive information about the thermospheric density. In this study, we compare for the first time thermospheric density corrections in terms of scale factors for the NRLMSISE‐00 model with a temporal resolution of 12 hr derived from two geodetic measurement techniques, namely satellite laser ranging (SLR) and accelerometry. Our results demonstrate that both measurement techniques can be used to derive comparable scale factors of the thermospheric density, which vary around the desired value one. This indicates to which extent the NRLMSISE‐00 model differs from the observed thermospheric density. On average, during high solar activity, the model underestimates the thermospheric density and can be scaled up using the estimated scale factors. We additionally discuss our estimated scale factors with respect to an external data set. Furthermore, we validate the approach of deriving scale factors from SLR measurements by using two independent software packages.
    Description: Key Points: For the first time, we compare scale factors of the thermospheric density derived from satellite laser ranging (SLR) and accelerometer measurements. The estimated scale factors vary by up to 30% at low solar activity and up to 70% at high solar activity from the desired value 1. Correlations of 0.7–0.8 are obtained between the estimated scale factors from SLR and accelerometer measurements depending on the height.
    Description: German Research Foundation (DFG)
    Description: Technical University of Munich (TUM)
    Keywords: ddc:551.5 ; ddc:526.1
    Language: English
    Type: doc-type:article
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
  • 10
    Publication Date: 2024-06-12
    Description: TND-IGG RL01: This dataset is the first release of thermospheric neutral densities (TND) processed at the Institute of Geodesy and Geoinformation (IGG), University of Bonn, Germany. TNDs are derived from accelerometer measurements of the satellites GRACE-A, CHAMP and Swarm-C. For GRACE-A and CHAMP we first calibrate the accelerometer data within a precise orbit determination procedure (Vielberg et al., 2018). For Swarm-C we use the calibrated along-track accelerations from ESA (Siemes et al., 2016). In a second step, solar and Earth radiation pressure accelerations according to Vielberg and Kusche (2020) are reduced from the calibrated accelerometer data. The resulting atmospheric drag is then related to the thermospheric neutral density following the direct procedure by Doornbos et al. (2010) with temperature and density of atmospheric constituents from the empirical model NRLMSIS2.0. We apply an accommodation coefficient of 0.93 for GRACE, 0.82 for Swarm and 0.85 for CHAMP. Detailed information about the processing can be found in the ReadMe.txt and in Vielberg et al. (2021, in review). The final thermospheric neutral densities with a temporal resolution of 10 seconds are provided as monthly netCDF files.
    Keywords: accelerometer; Accelerometer; ACCM; Binary Object; Binary Object (File Size); Binary Object (Media Type); CHAMP; GRACE; mass density; neutral density; satellite data; Swarm; thermopshere
    Type: Dataset
    Format: text/tab-separated-values, 3 data points
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
Close ⊗
This website uses cookies and the analysis tool Matomo. More information can be found here...