Open Access
Issue
J. Space Weather Space Clim.
Volume 7, 2017
Article Number A4
Number of page(s) 13
DOI https://doi.org/10.1051/swsc/2017003
Published online 21 February 2017
  • Bock, H., R. Dach, A. Jäggi, and G. Beutler. High-rate GPS clock corrections from CODE: support of 1 Hz applications. J. Geod., 83 (11), 1083–1094, 2009, DOI: 10.1007/s00190-009-0326-1. [CrossRef] [Google Scholar]
  • Bock, H., A. Jäggi, G. Beutler, and U. Meyer. GOCE: precise orbit determination for the entire mission. J. Geod., 88 (11), 1047–1060, 2014, DOI: 10.1007/s00190-014-0742-8. [CrossRef] [Google Scholar]
  • Bowman, B.R., W.K. Tobiska, F.A. Marcos, and C. Valladares. The JB2006 empirical thermospheric density model. J. Atmos. Sol. Terr. Phys., 70, 774–793, 2007, DOI: 10.1016/j.jastp.2007.10.002. [CrossRef] [Google Scholar]
  • Bruinsma, S., D. Tamagnan, and R. Biancale. Atmospheric densities derived from CHAMP/STAR accelerometer observations. Planet. Space Sci., 52, 297–312, 2004. [CrossRef] [Google Scholar]
  • Bruinsma, S.L. The DTM-2013 thermosphere model. J. Space Weather Space Clim., 5, A1, 2015, DOI: 10.1051/swsc/2015001. [CrossRef] [EDP Sciences] [Google Scholar]
  • Bruinsma, S.L., and J.M. Forbes. Medium to large-scale density variability as observed by CHAMP. Space Weather, 6, S08002, 2008, DOI: 10.1029/2008SW000411. [CrossRef] [Google Scholar]
  • Bruinsma, S.L., N. Sánchez-Ortiz, E. Olmedo, and N. Guijarro. Evaluation of the DTM-2009 thermosphere model for benchmarking purposes. J. Space Weather Space Clim., 2, A04, 2012, DOI: 10.1051/swsc/2012005. [CrossRef] [EDP Sciences] [Google Scholar]
  • Bruinsma, S.L., E. Doornbos, and B.R. Bowman. Validation of GOCE densities and thermosphere model evaluation. Adv. Space Res., 54, 576–585, 2014, DOI: 10.1016/j.asr.2014.04.008. [CrossRef] [Google Scholar]
  • Dach, R., E. Brockmann, S. Schaer, G. Beutler, M. Meindl, L. Prange, H. Bock, A. Jaeggi, and L. Ostini, GNSS processing at CODE: status report. J. Geod., 83, 3–4, 353–365, 2009, DOI: 10.1007/s00190-008-0281-2 [CrossRef] [Google Scholar]
  • Dach, R., S. Lutz, P. Walser, and P. Fridez, Editors. Bernese GNSS software version 5.2, Astronomical Institute, University of Bern, Switzerland, 2015, DOI: 10.7892/boris.72297. [Google Scholar]
  • Doornbos, E., S. Bruinsma, B. Fritsche, G. Koppenwallner, P. Visser, J. van den IJssel, and J. de Teixeira de Encarnação. ESA contract 4000102847/NL/EL, GOCE+ Theme 3: air density and wind retrieval using GOCE data – final report, TU Delft, Delft, The Netherlands, 2014. [Google Scholar]
  • Doornbos, E., H. Klinkrad, and P. Visser. Use of two-line element data for thermosphere neutral density model calibration. Adv. Space Res., 41, 1115–1122, 2008. [CrossRef] [Google Scholar]
  • European Space Agency. Gravity Field and Steady-State Ocean Circulation Mission – The Four Candidate Earth Explorer Core Missions. Technical Report, ESA SP-1233(1), European Space Agency Publications Division, Noordwijk, The Netherlands, 1999. [Google Scholar]
  • Gasperini, F., J.M. Forbes, E.N. Doornbos, and S.L. Bruinsma. Wave coupling between the lower and middle thermosphere as viewed from TIMED and GOCE. J. Geophys. Res., 120, 5788–5804, 2015, DOI: 10.1002/2015JA021300. [CrossRef] [Google Scholar]
  • T., Gruber, R. Rummel, O. Abrikosov, R. van Hees, Editors. GOCE Level 2 Product Data Handbook. GO-MA-HPF-GS-0110, Issue 4, Revision 3, European Space Agency, Noordwijk, The Netherlands, 2012. [Google Scholar]
  • Häusler, K., M.E. Hagan, J.M. Forbes, X. Zhang, E. Doornbos, S. Bruinsma, and G. Lu. Intraannual variability of tides in the thermosphere from model simulations and in situ satellite observations. J. Geophys. Res., 120, 751–765, 2015, DOI: 10.1002/2014JA020579. [CrossRef] [Google Scholar]
  • Hedin, A.E.. MSIS-86 thermospheric model. J. Geophys. Res., 92, 4649–4662, 1987. [NASA ADS] [CrossRef] [Google Scholar]
  • Intelisano, A., L. Mazzini, A. Notarantonio, S. Landenna, A. Zin, L. Scaciga, and L. Marradi. Recent flight experiences of TAS-I on-board navigation equipments. In: Proceedings of the 4th ESA workshop on satellite navigation user equipment technologies, NAVITEC2008, 10–12 Dec 2008, Noordwijk, The Netherlands, 2008. [Google Scholar]
  • Jäggi, A., H. Bock, and R. Floberghagen. GOCE orbit predictions for SLR tracking. GPS Solut., 15 (2), 129–137, 2011, DOI: 10.1007/s10291-010-0176-6. [CrossRef] [Google Scholar]
  • Marcos, F.A. Accuracy of atmospheric drag models at low satellite altitudes. Adv. Space Res., 10 (3), 417–422, 1990. [CrossRef] [Google Scholar]
  • Marcos, F.A., D.F. Gillette, and E.C. Robinson. Evaluation of selected global thermospheric density models during low solar flux conditions. Adv. Space Res., 3, 85–89, 1983. [CrossRef] [Google Scholar]
  • Picone, J.M., A.E. Hedin, D.P. Drob, and A.C. Aikin. NRLMSISE-00 empirical model of the atmosphere: statistical comparisons and scientific issues. J. Geophys. Res., 107 (A12), 1468, 2002, DOI: 10.1029/2002JA009430. [NASA ADS] [CrossRef] [Google Scholar]
  • Reigber, Ch., R. Bock, Ch. Foerste, L. Grunwaldt, N. Jakowski, H. Luehr, P. Schwintzer, and C. Tilgner. CHAMP phase B executive summary, Scientific Technical Report STR96/13, GeoForschungsZentrum Potsdam, Germany, 1996. [Google Scholar]
  • Sentman, L.H. Comparison of the exact and approximate methods for predicting free molecule aerodynamic coefficients. ARS J., 31, 1576–1579, 1961. [Google Scholar]
  • Storz, M.F., B.R. Bowman, M.J.I. Branson, S.J. Casali, and W.K. Tobiska. High accuracy satellite drag model (HASDM). Adv. Space Res., 36, 2497–2505, 2005, DOI: 10.1016/j.asr.2004.02.020. [CrossRef] [Google Scholar]
  • Svehla, D., and M. Rothacher. Kinematic precise orbit determination for gravity field determination. In: F. Sansò, Editor. A Window on the Future of Geodesy, vol. 128, Springer, Berlin, 181–188, 2005, DOI: 10.1007/3-540-27432-4_32. [CrossRef] [Google Scholar]
  • Visser, P.N.A.M., and J.A.A. van den IJssel. Calibration and validation of individual GOCE accelerometers by precise orbit determination. J. Geod., 90, 1–13, 2015, DOI: 10.1007/s00190-015-0850-0. [CrossRef] [Google Scholar]

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