Atmospheric Pressure Loading

Wijaya, Dudy D.; Boehm, J.; Karbon, Maria; Krásná, Hana; Schuh, Harald

doi:10.1007/978-3-642-36932-2_4

Cited by 31 publications

(11 citation statements)

References 22 publications

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“…For the assessment of APL effects on the analysis of LEO SLR data (see Sect. 4.2) we make use of 6-hourly APL values provided by the Technical University of Vienna on a 1 • × 1 • longitude/latitude grid (Wijaya et al 2013).…”

Section: Range Modelmentioning

confidence: 99%

Satellite laser ranging to low Earth orbiters: orbit and network validation

Arnold

Montenbruck

Hackel

et al. 2018

J Geod

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Satellite laser ranging (SLR) to low Earth orbiters (LEOs) provides optical distance measurements with mm-to cm-level precision. SLR residuals, i.e., differences between measured and modeled ranges, serve as a common figure of merit for the quality assessment of orbits derived by radiometric tracking techniques. We discuss relevant processing standards for the modeling of SLR observations and highlight the importance of line-of-sight dependent range corrections for the various types of laser retroreflector ararys (LRAs). A 1-3 cm consistency of SLR observations and GPSbased precise orbits is demonstrated for a wide range of past and present LEO missions supported by the International Laser Ranging Service (ILRS). A parameter estimation approach is presented to investigate systematic orbit errors and it is shown that SLR validation of LEO satellites is not only able to detect radial but also along-track and cross-track offsets. SLR residual statistics clearly depend on the employed precise orbit determination technique (kinematic vs. reduced-dynamic, float vs. fixed ambiguities) but also reveal pronounced differences in the ILRS station performance. Using the residuals-based parameter estimation approach, corrections to ILRS station coordinates, range bi

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Section: Range Modelmentioning

confidence: 99%

Satellite laser ranging to low Earth orbiters: orbit and network validation

Arnold

Montenbruck

Hackel

et al. 2018

J Geod

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“…The largest process noise is, as expected, in the radial component, and primarily affected by non-tidal atmospheric pressure loading. Sites close to the sea and at lower latitudes are affected less due to the inverse barometer effect and attenuated pressure fluctuations near the equator, respectively (Wijaya et al, 2013). The PSD values of the east-west and north-south components, which are of much smaller magnitude, are mostly affected by nontidal ocean loading.…”

Section: Stochastic Model From Geophysical Deformationsmentioning

confidence: 94%

Determination of a terrestrial reference frame via Kalman filtering of very long baseline interferometry data

Soja

Nilsson

Balidakis

et al. 2016

J Geod

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Terrestrial reference frames (TRF), such as the ITRF2008, are primary products of geodesy. In this paper, we present TRF solutions based on Kalman filtering of very long baseline interferometry (VLBI) data, for which we estimate steady station coordinates over more than 30 years that are updated for every single VLBI session. By applying different levels of process noise, non-linear signals, such as seasonal and seismic effects, are taken into account. The corresponding stochastic model is derived site-dependent from geophysical loading deformation time series and is adapted during periods of post-seismic deformations. Our results demonstrate that the choice of stochastic process has a much smaller impact on the coordinate time series and velocities than the overall noise level. If process noise is applied, tests with and without additionally estimating seasonal signals indicate no difference between the resulting coordinate time series for periods when observational data are available. In a comparison with epoch reference frames, the Kalman filter solutions provide better short-term stability. Furthermore, we find out that the Kalman filter solutions are of similar quality when compared to a consistent least-squares solution, however, with the enhanced attribute of being

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“…These solutions follow the IERS Conventions 2010 by Petit and Luzum (2010) for reducing the observations and geophysical modeling. Also, antenna thermal deformation (Nothnagel 2009) and atmospheric pressure loading (Wijaya et al 2013) were taken into account.…”

Section: Dataandanalysismentioning

confidence: 99%

Comparing Vienna CRF solutions to Gaia-CRF2

Mayer

Boehm

2020

International Association of Geodesy Symposia

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We are using various models and analysis strategies, such as galactic aberration, ray-tracing etc., to create different Vienna celestial reference frame (CRF) solutions. These solutions are then compared against the Gaia reference frame (Gaia-CRF2). This is done using a degree 2 vector spherical harmonics approach. The estimated parameters are used to investigate the impact of the various analysis methods on the differences between Gaia and the Very Long Baseline Interferometry (VLBI) CRF. We find that correcting for galactic aberration reduces the difference between the Gaia-CRF2 and the VLBI CRF significantly (30 µas in D 2 and 13 µas in D 3 ). Furthermore, we find that using a priori ray-traced tropospheric delays in addition with low absolute constraints on tropospheric gradients reduces the a e 20 parameter by 20 µas. Using these analysis strategies we can explain almost all significant differences between the Gaia-CRF2 and the VLBI CRF. However, the vector spherical harmonic (VSH) parameter a e 20 is still highly significant and can not be explained by modeling and analysis choices from the VLBI technique.

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Atmospheric Pressure Loading

Cited by 31 publications

References 22 publications

Satellite laser ranging to low Earth orbiters: orbit and network validation

Satellite laser ranging to low Earth orbiters: orbit and network validation

Determination of a terrestrial reference frame via Kalman filtering of very long baseline interferometry data

Comparing Vienna CRF solutions to Gaia-CRF2

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