Comparison between refraction angles measured in the Microlab-1 experiment and calculated on the basis of an atmospheric general circulation model
The differences between the refraction angles measured and calculated for the reanalyses of the European Centre for Medium-Range Weather Forecasts were statistically analyzed on the basis of 64 radio occultation events recorded by the Microlab-1 satellite. It is shown that, for minimum ray heights below 20 km, the main contribution to the differences is made by spatial refractive-index fluctuations neglected by the model. The power spectral density of these fluctuations is mainly concentrated within the vertical wave-number range 0.5–10 rad/km. For heights above 30 km, the deviations are mainly determined by ionospheric disturbances and may vary several times during changes of the site and time of observations. This suggests that the results of satellite radio-occultation sounding of the neutral atmosphere can be used as an indirect quantitative estimate of local discrepancies between the actual field of the refractive index and its values calculated on the basis of a hydrodynamic atmospheric general circulation model.
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- 2.E. R. Kursinski, G. A. Hajj, S. S. Leroy, and B. Herman, “The GPS Radio Occultation Technique,” Terr. Atmos. Ocean. Sci. 11, 53–114 (2000).Google Scholar
- 8.M. E. Gorbunov, K. V. Lauritsen, A. Rodin, et al., “Analysis of the CHAMP Experimental Data on Radio-Occultation Sounding of the Earth’s Atmosphere,” Izv. Akad. Nauk, Fiz. Atmos. Okeana 41, 798–813 (2005) [Izv., Atmos. Ocean. Phys. 41, 726–740 (2005)].Google Scholar
- 9.V. V. Vorob’ev and T. G. Krasil’nikova, “Estimating the Accuracy of Retrieving the Atmospheric Refractive Index from Measurements of the Doppler Shift at the NAVSTAR Frequencies,” 29, 626–632 (1993).Google Scholar
- 11.M. E. Gorbunov, “Ionospheric Correction and Statistical Optimization of Radio Occultation Data,” Radio Sci. 37, 17-1–17-9, doi: 10.1029/2000RS002370 (2002).Google Scholar
- 12.V. V. Vorob’ev and V. Kan, “Background Fluctuations in the Ionosphere during GPS-Microlab-1 Radio-Occultation Experiment,” Izv. Vyssh. Uchebn. Zaved., Radiofiz. 42, 511–523 (1999).Google Scholar
- 13.S. M. Uppala, P. W. Kallberg, A. J. Simmons, et al., “The ERA-40 Re-Analysis,” Q. J. R. Meteorol. Soc., No. 131, 2961–3012, doi: 10.1256/qj.04.176 (2005).Google Scholar
- 14.M. E. Gorbunov, “Canonical Transform Method for Processing GPS Radio Occultation Data in Lower Troposphere,” Radio Sci. 37, 9-1–9-10, doi:10.1029/2000RS002592 (2002).Google Scholar
- 17.M. E. Gorbunov, H.-H. Benzon, A. S. Jensen, et al., “Comparative Analysis of Radio Occultation Processing Approaches Based on Fourier Integral Operators,” Radio Sci. 39, 6004, doi: 10.1029/2003RS002916 (2004).Google Scholar
- 19.M. E. Gorbunov and K. B. Lauritsen, “Analysis of Wave Fields by Fourier Integral Operators and Its Application for Radio Occultations,” Radio Sci. 39, 4010, doi: 10.1029/2003RS002971 (2004).Google Scholar
- 20.M. E. Gorbunov, “Analysis of the Data of Radio-Occultation Sounding of the Earth’s Atmosphere with the Use of the Theory of Fourier Integral Operators,” Elektromagn. Volny Elektron. Sist., No. 9, 9–10 (2004).Google Scholar
- 21.A. M. Yaglom, Correlation Theory of Stationary Random Functions (Gidrometeoizdat, Leningrad, 1981) [in Russian].Google Scholar
- 22.J. S. Bendat and A. G. Piersol, Engineering Applications of Correlation and Spectral Analysis (Mir, Moscow, 1983; Wiley, New York, 1980).Google Scholar