17 Dec 2020
| 17 Dec 2020
Benchmark data for verifying background model implementations in orbit and gravity field determination software
Martin Lasser
CORRESPONDING AUTHOR
Astronomical Institute, University of Bern, Bern, Switzerland
Ulrich Meyer
Astronomical Institute, University of Bern, Bern, Switzerland
Adrian Jäggi
Astronomical Institute, University of Bern, Bern, Switzerland
Torsten Mayer-Gürr
Institute of Geodesy, Graz University of Technology, Graz, Austria
Andreas Kvas
Institute of Geodesy, Graz University of Technology, Graz, Austria
Karl Hans Neumayer
GFZ German Research Centre for Geosciences, Potsdam, Germany
Christoph Dahle
GFZ German Research Centre for Geosciences, Potsdam, Germany
Frank Flechtner
GFZ German Research Centre for Geosciences, Potsdam, Germany
Jean-Michel Lemoine
Groupe de Recherche de Géodésie Spatiale, Centre National
d’Etudes Spatiales, Toulouse, France
Igor Koch
Institut für Erdmessung, Leibniz University of Hannover, Hannover, Germany
Matthias Weigelt
Institut für Erdmessung, Leibniz University of Hannover, Hannover, Germany
Jakob Flury
Institut für Erdmessung, Leibniz University of Hannover, Hannover, Germany
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Cited articles
Altamimi, Z., Rebischung, P., Métivier, L., and Collilieux, X.: ITRF2014: A
new release of the International Terrestrial Reference Frame modeling
nonlinear station motions, J. Geophys. Res.-Sol. Ea., 121,
6109–6131, https://doi.org/10.1002/2016JB013098, 2016. a
Arnold, D., Bertone, S., Jäggi, A., Beutler, G., and Mervart, L.: GRAIL
gravity field determination using the Celestial Mechanics Approach, Icarus,
261, 182–192, https://doi.org/10.1016/j.icarus.2015.08.015, 2015. a
Barthelmes, F. and Förste, C.: The ICGEM-format, Technical report, GFZ
Potsdam, Germany, Department 1 Geodesy and Remote Sensing, available at: http://icgem.gfz-potsdam.de/ICGEM-Format-2011.pdf (last access: 1 December 2020), 2011. a
Bizouard, C., Lambert, S., Gattano, C., Becker, O., and Richard, J.-Y.: The
IERS EOP 14C04 solution for Earth orientation parameters consistent with ITRF
2014, J. Geodesy, 93, 621–633, https://doi.org/10.1007/s00190-018-1186-3,
2018. a
Dach, R., Lutz, S., Walser, P., and Fridez, F.: Bernese GPS software version
5.2, Documentation, University of Bern, Bern Open Publishing,
https://doi.org/10.7892/boris.72297, 2015. a
Dahle, C., Murböck, M., Flechtner, F., Dobslaw, H., Michalak, G., Neumayer,
K. H., Abrykosov, O., Reinhold, A., König, R., Sulzbach, R., and Förste,
C.: The GFZ GRACE RL06 Monthly Gravity Field Time Series: Processing Details
and Quality Assessment, Remote Sens.-Basel, 11, 2116, https://doi.org/10.3390/rs11182116, 2019. a
Desai, S. D.: Observing the pole tide with satellite altimetry, J. Geophys. Res.-Oceans, 107, 71713, https://doi.org/10.1029/2001JC001224, 2002. a, b
Dobslaw, H., Bergmann-Wolf, I., Dill, R., Poropat, L., Thomas, M., Dahle, C.,
Esselborn, S., König, R., and Flechtner, F.: A new high-resolution model of
non-tidal atmosphere and ocean mass variability for de-aliasing of satellite
gravity observations: AOD1B RL06, Geophys. J. Int., 211,
263–269, https://doi.org/10.1093/gji/ggx302, 2017. a, b
Doodson, A. T. and Lamb, H.: The harmonic development of the tide-generating
potential, P. Roy. Soc. Lond. A, 100, 305–329,
https://doi.org/10.1098/rspa.1921.0088, 1921. a, b
Ellmer, M. and Mayer-Gürr, T.: High precision dynamic orbit integration for
spaceborne gravimetry in view of GRACE Follow-on, Adv. Space Res.,
60, 1–13, https://doi.org/10.1016/j.asr.2017.04.015, 2017. a
Fey, A. L., Gordon, D., and Jacobs, C. S.: The Second Realization of the
International Celestial Reference Frame by Very Long Baseline Interferometry, IERS Technical Note No. 35, Verlag des Bundesamts für Kartographie und Geodäsie, Frankfurt am Main, Germany, 2009. a
Förste, C., Bruinsma, S. L., Abrikosov, O., Lemoine, J.-M., Marty, J. C.,
Flechtner, F., Balmino, G., Barthelmes, F., and Biancale, R.: EIGEN-6C4 The
latest combined global gravity field model including GOCE data up to degree
and order 2190 of GFZ Potsdam and GRGS Toulouse, GFZ Data Services,
https://doi.org/10.5880/icgem.2015.1, 2014. a, b
Friis-Christensen, E., Lühr, H., Knudsen, D., and Haagmans, R.: Swarm – An
Earth Observation Mission investigating Geospace, Adv. Space Res.,
41, 210–216, https://doi.org/10.1016/j.asr.2006.10.008, 2006. a
Glaser, S., König, R., Neumayer, K. H., Nilsson, T., Heinkelmann, R.,
Flechtner, F., and Schuh, H.: On the impact of local ties on the datum
realization of global terrestrial reference frames, J. Geodesy, 93,
655–667, https://doi.org/10.1007/s00190-018-1189-0, 2019. a
Heiskanen, W. A. and Moritz, H.: Physical geodesy, W. H. Freeman and Company,
San Francisco, USA, 1967. a
IEEE-754: IEEE Standard for Binary Floating-Point Arithmetic in ANSI/IEEE Std 754–1985, 1–20, https://doi.org/10.1109/IEEESTD.1985.82928, 1985. a
IERS: Update IERS 2010 Conventions ch. 7.1.4, available at: http://iers-conventions.obspm.fr/content/chapter7/icc7.pdf (last access: 1 December 2020),
2018. a
Jäggi, A., Meyer, U., Lasser, M., Jenny, B., Lopez, T., Flechtner, F., Dahle,
C., Förste, C., Mayer-Gürr, T., Kvas, A., Lemoine, J.-M., Bourgogne, S.,
Weigelt, M., and Groh, A.: International Combination Service for
Time-Variable Gravity Fields (COST-G) – Start of Operational Phase and Future Perspectives, IAG Symposia, Springer, Berlin, Heidelberg, 1–9, https://doi.org/10.1007/1345_2020_109, 2020. a
Johnston, G., Riddell, A., and Hausler, G.: The International GNSS Service,
Springer Handbooks, Cham, 967–982, https://doi.org/10.1007/978-3-319-42928-1_33, 2017. a
Koch, I., Flury, J., Naeimi, M., and Shabanloui, A.: LUH-GRACE2018: A New Time
Series of Monthly Gravity Field Solutions from GRACE, IAG Symposia, Springer, Berlin, Heidelberg 1–9,
https://doi.org/10.1007/1345_2020_92, 2020. a, b
Kvas, A., Behzadpour, S., Ellmer, M., Klinger, B., Strasser, S., Zehentner, N.,
and Mayer-Gürr, T.: ITSG‐Grace2018: Overview and evaluation of a new
GRACE‐only gravity field time series, J. Geophys. Res.-Sol. Ea., 124, 9332–9344, https://doi.org/10.1029/2019JB017415, 2019. a
Landerer, F. W., Flechtner, F. M., Save, H., Webb, F. H., Bandikova, T.,
Bertiger, W. I., Bettadpur, S. V., Byun, S. H., Dahle, C., Dobslaw, H.,
Fahnestock, E., Harvey, N., Kang, Z., Kruizinga, G. L. H., Loomis, B. D.,
McCullough, C., Murböck, M., Nagel, P., Paik, M., Pie, N., Poole, S.,
Strekalov, D., Tamisiea, M. E., Wang, F., Watkins, M. M., Wen, H.-Y., Wiese,
D. N., and Yuan, D.-N.: Extending the Global Mass Change Data Record: GRACE
Follow-On Instrument and Science Data Performance, Geophys. Res.
Lett., 47, e2020GL088306, https://doi.org/10.1029/2020GL088306, 2020. a
Mayer-Gürr, T. and Kvas, A.: COST-G software comparison, Graz University of Technology, available at: ftp://ftp.tugraz.at/outgoing/ITSG/COST-G/softwareComparison/, 2019. a
Meyer, U., Jäggi, A., Jean, Y., and Beutler, G.: AIUB-RL02: an improved
time-series of monthly gravity fields from GRACE data, Geophys. J.
Int., 205, 1196–1207, https://doi.org/10.1093/gji/ggw081, 2016. a
Naeimi, M.: A modified Gauss-Jackson method for the numerical integration of
the variational equations, Geophysical Research Abstracts, Vol. 20, EGU2018-1513-2, 2018, EGU General Assembly 2018, Vienna, Austria, 8–13, April 2018. a
Pearlman, M. R., Degnan, J. J., and Bosworth, J. M.: The International Laser
Ranging Service, Adv. Space Res., 30, 135–143,
https://doi.org/10.1016/S0273-1177(02)00277-6, 2002. a
Prange, L., Orliac, E., Dach, R., Arnold, D., Beutler, G., Schaer, S., and Jäggi,
A.: CODE's five-system orbit and clock solution – the challenges of
multi-GNSS data analysis, J. Geodesy, 91, 345–360,
https://doi.org/10.1007/s00190-016-0968-8, 2017. a
Strasser, S., Mayer-Gürr, T., and Zehentner, N.: Processing of GNSS
constellations and ground station networks using the raw observation
approach, J. Geodesy, 93, 1045–1057, https://doi.org/10.1007/s00190-018-1223-2, 2019. a
Tapley, B. D., Bettadpur, S., Watkins, M., and Reigber, C.: The gravity
recovery and climate experiment: Mission overview and early results,
Geophys. Res. Lett., 31, L09607, https://doi.org/10.1029/2004GL019920, 2004. a
Touboul, P., Willemenot, E., Foulon, B., and Josselin, V.: Accelerometers for
CHAMP, GRACE and GOCE space missions: Synergy and evolution, Bol. Geofis.
Teor. Appl., 40, 321–327, 1999. a
Weigelt, M., van Dam, T., Jäggi, A., Prange, L., Tourian, M. J., Keller, W.,
and Sneeuw, N.: Time-variable gravity signal in Greenland revealed by
high-low satellite-to-satellite tracking, J. Geophys. Res.-Sol. Ea., 118, 3848–3859, https://doi.org/10.1002/jgrb.50283, 2013.
a, b
Zhu, S., Reigber, C., and König, R.: Integrated adjustment of CHAMP, GRACE,
and GPS data, J. Geodesy, 78, 103–108,
https://doi.org/10.1007/s00190-004-0379-0, 2004. a
Short summary
Correctly determining the orbit of Earth-orbiting satellites requires to account multiple background effects which appear in the system Earth. Usually, these effects are introduced by various complex force models, which are not always easy to handle. We publish and validate a data set of commonly used models to make it easier to track down potential issues when applying such background forces in orbit and gravity field determination.
Correctly determining the orbit of Earth-orbiting satellites requires to account multiple...
