## 1. Introduction

[2] Radio occultations using the signals of the Global Positioning System (GPS) can play a very important role in the sounding of the Earth's atmosphere for the purposes of numerical weather prediction [*Ware et al.*, 1996; *Rocken et al.*, 1997; *Kursinski et al.*, 1997]. It is also clear that the reconstruction of the structure of the lower troposphere is of primary importance for these purposes. The Microlab-1 experiment performed in the frame of the GPS Meteorology Program (GPS/MET) provided a big array of occultation data. However, the quality of these data was degraded in the lower troposphere due to technical problems with the receiver [*Rocken et al.*, 1997; *Sokolovskiy*, 2001b]. To a significant extent, this is explained by the results of numerical simulations of GPS radio occultation experiments, which show that the effects of multipath propagation must play a significant role in the lower troposphere [*Gorbunov and Gurvich*, 1998b; *Gorbunov et al.*, 2000; *Sokolovskiy*, 2001a]. Radio signals in multipath areas have a complicated structure, which impedes both their tracking and interpretation. In this paper we shall discuss a new method of the interpretation of lower tropospheric radio occultation signals.

[3] Two techniques for processing radio occultation data in multipath regions were discussed in the literature: (1) the back propagation method [*Gorbunov et al.*, 1996; *Hinson et al.*, 1997, 1998; *Gorbunov and Gurvich*, 1998a] and (2) the radio-optics (or radioholographic, or sliding spectral) method [*Lindal et al.*, 1987; *Pavelyev*, 1998; *Hocke et al.*, 1999; *Sokolovskiy*, 2001a]. The former method consists in the numerical back propagation of the wave field recorded during a radio occultation experiment to a single-ray region. The latter method is based on the analysis of local spatial spectra of the wave field, where the spectral maxima are interpreted as rays. It can also be observed that the radio-optics method is very similar to the wavelet analysis.

[4] The comparative analysis of both methods [*Gorbunov et al.*, 2000] indicates that they have their restrictions. The back propagation method does not work for complicated caustic structures. Numerical simulations with high-resolution radiosonde data indicate that for the real atmosphere this restriction may be critical [*Sokolovskiy*, 2001a]. The radio-optics method cannot locate rays in subcaustic zones, where the wave field cannot be described in terms of geometric optics. The radio-optics method also has a limited resolution. This restriction, however, is not very significant in the lower troposphere. Another problem was that the radio-optics method in its standard variant was inconvenient for the automated data processing.

[5] In this paper we discuss two simple modifications of the radio-optics method, the first of which allows for the automated data processing, and the second modification reduces the effects of subcaustic zones. For a record of complex field *u*_{LEO}(*t*) measured at the low Earth orbiter (LEO) during a radio occultation experiment, we can compute a two-dimensional (2-D) array of sliding spectra *ũ*_{LEO}(*t*, ω). For each moment of time *t* the spectrum *ũ*_{LEO}(*t*, ω) is defined as the local Fourier spectrum of the complex field *u*_{LEO}(*t*) for time interval *t* − *T*/2 … *t* + *T*/2, where *T* is the size of the sliding aperture. Rays can be identified as the maxima of these spectra. Given the satellite positions for time *t*, the refraction angle ϵ and ray impact parameter *p* can be computed from the Doppler frequency ω. This means that the coordinates (*t*, ω) can be mapped to ray coordinates (ϵ, *p*), and we can now compute the 2-D spectrum as a function of ray coordinates *ũ*_{LEO}(ϵ, *p*). Plotting the absolute values of sliding spectra |*ũ*_{LEO}(ϵ, *p*)| is a very convenient means of data visualization, because the spectral maxima trace the dependence ϵ(*p*). For automated data processing the dependence ϵ(*p*) is defined as the position ϵ of the main maximum of the cross section of the spectrum *ũ*_{LEO}(ϵ, *p*) for given *p*. This method has an advantage as compared to the standard approach, where multiple spectral maxima ω_{i} are detected for given time *t* and then corresponding refraction angles ϵ_{i} and impact parameters *p*_{i} are computed. This is because (1) the detection of the main maximum is algorithmically very simple, unlike the detection of multiple maxima and (2) not all of the multiple spectral maxima can be really attributed to rays, while the main maximum for given impact parameter *p* is much more likely to correspond to the only ray with this *p*.

[6] In order to reduce the effect of subcaustic zones, where the spectral maxima cannot be interpreted in terms of rays, we proceed as follows. We compute the back-propagated field *u*_{BP}(*t*), and its local spectra transformed the ray coordinates *ũ*_{BP}(ϵ, *p*). Simple geometrical considerations show that “false” spectral maxima arising in subcaustic zones will have different positions for back-propagated field as compared to the field measured along the LEO trajectory, while the positions of “true” maxima corresponding to rays remain the same. The computation of the spectral maxima of the averaged logarithmic spectrum [ln *u*_{LEO}(ϵ, *p*) + ln *u*_{BP}(ϵ, *p*)]/2 proves then more stable to the effects of subcaustic zones.

[7] The method is validated on the material of global fields of atmospheric variables from analyses of the European Centre for Medium-Range Weather Forecasts (ECMWF).