Abstract
Abstract. Linear and non-linear representations of wave fields constitute the basis of modern algorithms for analysis of radio occultation (RO) data. Linear representations are implemented by Fourier Integral Operators, which allow for high-resolution retrieval of bending angles. Non-linear representations include Wigner Distribution Function (WDF), which equals the pseudo-density of energy in the ray space. Representations allow for filtering wave fields by suppressing some areas of the ray space and mapping the field back from the transformed space to the initial one. We apply this technique to the retrieval of reflected rays from RO observations. The use of reflected rays may increase the accuracy of the retrieval of the atmospheric refractivity. Reflected rays can be identified by the visual inspection of WDF or spectrogram plots. Numerous examples from COSMIC data indicate that reflections are mostly observed over oceans or snow, in particular over Antarctica. We introduce the reflection index that characterizes the relative intensity of the reflected ray with respect to the direct ray. The index allows for the automatic identification of events with reflections. We use the radio holographic estimate of the errors of the retrieved bending angle profiles of reflected rays. A comparison of indices evaluated for a large base of events including the visual identification of reflections indicated a good agreement with our definition of reflection index.
Highlights
A clear signature of signals reflected by the Earth’s surface was revealed as early as the beginning of 21st century, by means of the radio holographic analysis of CHAMP radio occultation (RO) data (Beyerle and Hocke, 2001; Beyerle et al, 2002)
Where umax is the maximum of the spectral density taken within the interval of p ∈ [−0.1 km, 0.1 km], pmax is the location of the spectral maximum of the reflection, uave is the spectral density averaged over the interval of pmax − 0.3, pmax + 0.3, ubkg is the background spectral density estimated by averaging over the interval of p ∈ [1.0 km, 2.0 km], and α is the regularization parameter, pM(t) is the dependence of the impact parameter on the model reflected signal vs. time, and δp(t) is the radio holographic error estimate of the impact parameter
We described our modification of the canonical transform (CT) technique for the retrieval of bending angle profiles of reflected www.atmos-meas-tech.net/11/1181/2018/
Summary
A clear signature of signals reflected by the Earth’s surface was revealed as early as the beginning of 21st century, by means of the radio holographic analysis of CHAMP radio occultation (RO) data (Beyerle and Hocke, 2001; Beyerle et al, 2002). We discuss the algorithm of reflected ray retrieval based on the modification of the CT method. It is more convenient to project the reflected field component back into the time domain (Cardellach et al, 2009, 2010) For this projection we use the inverse FIO. In relation to the problem of the reflected ray retrieval, this approach has the same advantages of the radio holographic (sliding spectral) method (Beyerle and Hocke, 2001; Beyerle et al, 2002), as it is more accurate and computationally more efficient (Gorbunov, 2002c). We discuss the filtering algorithm based on FIO that allow separating reflection from RO observations.
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