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  • 1
    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
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  • 2
    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
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  • 3
    Publication Date: 2022-12-01
    Description: Deutsche Forschungsgemeinschaft
    Description: poster
    Keywords: ddc:550
    Language: English
    Type: doc-type:conferenceObject
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