Observation, analysis, and modeling of deep radio occultation signals: Effects of tropospheric ducts and interfering signals

Abstract

GPS radio occultation (RO) signals are sometimes observed very deep in the Earth's shadow.To investigate these phenomena, one of the FORMOSAT-3/COSMIC RO receivers was set to track RO signals deep below the limb, down to a height of straight line À350 km on 5-6 October 2010. Analysis of the spectrograms revealed the existence of two types of signals below À200 km, RO signals induced by tropospheric propagation and interfering signals not transmitted by the occulted GPS. The RO signals induced by tropospheric propagation arrive from impact heights corresponding to inversion layers. Wave optics modeling of RO signals showed that deep signals exist when the refractivity gradient exceeds critical (super-refraction). The existence of such signals is a diffractional phenomenon, which offers a new quality control parameter to identify occultations that may be affected by super-refraction. This is important for RO data assimilation in weather models in the moist lower troposphere because assimilation of RO data affected by super-refraction is an ill-conditioned problem. Detection of the tropospheric ducts also may be useful for evaluation of radio wave propagation conditions. For infinitely horizontally extended ducts, the deep signals are extended in duration, have amplitudes of about 0.1%, and exist for only elevated ducts. For ducts of limited horizontal extension, the deep signals are shorter in duration, have amplitude of about 1%, and may exist for both elevated and surface ducts. The interfering signals were found in about half of occultations. Based on frequency modeling, in most cases, the interfering signal was identified with non-occulted GPS. The disturbance of retrieved bending angle induced by an interfering signal from a non-occulted GPS in a region of strong defocusing and significant spectral spread of RO signal was modeled and determined to be quite large, up to 10% of bending angle. However, the probability of occurrence of such interference (not estimated), generally, must be low. Removal of the interfering signal by high-pass filtering was tested, but it introduced a disturbance of bending angle of about the same magnitude as the interfering signal itself.

COSMIC‐2 Radio Occultation Constellation: First Results

“…NWP models can reproduce SR, but their predictions may contain errors and so direct observations of SR are useful for NWP as well as weather and climate research. SR can be detected by the existence of deep signals in spectrograms of RO signals acquired under high SNR (Sokolovskiy et al, 2014). Figure 3 shows three C2 occultations tracked down to −350 km height of the tangent point (TP) of the straight line from the transmitter to receiver.…”

GNSS-RO Refractivity Bias Correction Under Ducting Layer Using Surface-Reflection Signal

“…This difference in the reflected bending angle profile can thus be used to distinguish different profiles corresponding to the same direct bending angle in the ducting situations. Note that this is a useful feature for weather forecast data assimilation, which can identify or flag a specific case if it is contaminated by the ducting-caused N-bias [28]. Here, we take this idea further to reconstruct the refractivity profile and reduce the N-bias, and the algorithm to identify the correct profile with the reflected bending angle is introduced in the next section.…”

Ionospheric irregularity reconstruction using multisource data fusion via deep learning

“…Ionospheric E-layer irregularities, or sporadic E (Es), are dense layers of metallic ions in the lower thermosphere between 80 and 130 km, a region that is characterized by complicated atmospheric dynamics and nonlinear plasma processes (Matsushita and Reddy, 1967;Whitehead, 1970;Mathews, 1998;Haldoupis, 2011). The intense plasma ir-regularities within Es layers, which are representative of the complex interaction between the neutral atmosphere and the ionosphere, can cause perturbations and scintillation in radio signals due to a large vertical gradient in electron density (Pavelyev et al, 2007;Zeng and Sokolovskiy, 2010;Sokolovskiy et al, 2014). The phenomenon has attracted considerable attention over the last decades, which led to numerous scientific studies (Arras et al, 2008;Lei et al, P. Tian et al: Ionospheric irregularity reconstruction using multisource data fusion via deep learning 2007, 2008; Chu et al, 2014;Tsai et al, 2018;Arras and Wickert, 2018;Yu et al, 2019;Shinagawa et al, 2021;Ye et al, 2023).…”