scholarly journals Systematic errors in atmospheric profiles obtained from Abelian inversion of radio occultation data: Effects of large-scale horizontal gradients

1999 ◽  
Vol 104 (D4) ◽  
pp. 3971-3992 ◽  
Author(s):  
Bilal Ahmad ◽  
G. Leonard Tyler
Keyword(s):  
Large Scale ◽  
Radio Occultation ◽  
Systematic Errors ◽  
Horizontal Gradients ◽  
Atmospheric Profiles ◽  
Occultation Data ◽  
Radio Occultation Data

Analysis of radio occultation data to determine atmospheric profiles and associated uncertainties 

2021 ◽  
Author(s):  
Flavio Petricca ◽  
Gael Cascioli ◽  
Antonio Genova
Keyword(s):  
Frequency Shift ◽  
Radio Occultation ◽  
Precise Orbit Determination ◽  
Tracking Data ◽  
Radio Tracking ◽  
Numerical Predictions ◽  
Spacecraft Trajectory ◽  
Atmospheric Profiles ◽  
Occultation Data ◽  
Radio Occultation Data

<div> <p><span>The analysis of atmospheric radio occultations enables an in-depth investigation of planetary ionosphere and neutral atmospheres, by measuring the radio frequency shift that affects a signal propagating through the medium. A precise characterization of the atmospheric layers requires a thorough processing of the radio tracking data to estimate the thermodynamic properties of the atmosphere and their related uncertainties. </span></p> </div><div> <p><span>A standard procedure to process radio occultation data requires a preliminary knowledge of the spacecraft trajectory. In this work, we present a technique to retrieve refractivity, density, pressure, and temperature profiles with their associated uncertainties through the analysis of raw radio tracking data occulted by the atmosphere. By integrating the algorithm for radio occultation processing with a Precise Orbit Determination (POD) software, an enhanced reconstruction of the spacecraft trajectory is obtained to recover the frequency shift due to the medium refraction. The resulting radio signal is then processed to yield information regarding atmospheric properties. A Monte Carlo simulation algorithm is also included to provide the formal uncertainties of the estimated parameters.</span></p> </div><div> <p><span>We applied this technique to radio occultation profiles of the NASA mission Mars Reconnaissance Orbiter (MRO). To validate the method, our estimated atmospheric profiles are compared to the numerical predictions of the Mars Global Reference Atmospheric Model (GRAM) and the Mars Climate Database (MCD). </span></p> </div>

A global 3-D electron density reconstruction model based on radio occultation data and neural networks

2021 ◽  
pp. 105702
Author(s):  
John Bosco Habarulema ◽  
Daniel Okoh ◽  
Dalia Burešová ◽  
Babatunde Rabiu ◽  
Mpho Tshisaphungo ◽  
...  
Keyword(s):  
Neural Networks ◽  
Electron Density ◽  
Radio Occultation ◽  
Model Based ◽  
Occultation Data ◽  
Reconstruction Model ◽  
Radio Occultation Data

Analysis of selected Solar events with Mars Express radio occultation data 

2021 ◽  
Author(s):  
Özgür Karatekin ◽  
Ananya Krishnan ◽  
Nayeem Ebrahimkutty ◽  
Greg Henry ◽  
Ahmed El Fadhel ◽  
...  
Keyword(s):  
Radio Occultation ◽  
Mars Express ◽  
Solar Events ◽  
Occultation Data ◽  
Radio Occultation Data

Analyzing the Diurnal Cycle by Bayesian Interpolation on a Sphere for Mapping GNSS Radio Occultation Data

2021 ◽  
Vol 38 (5) ◽  
pp. 951-961
Author(s):  
Stephen S. Leroy ◽  
Chi O. Ao ◽  
Olga P. Verkhoglyadova ◽  
Mayra I. Oyola
Keyword(s):  
Diurnal Cycle ◽  
Radio Occultation ◽  
Basis Functions ◽  
Atmospheric Tides ◽  
Spherical Harmonic Degree ◽  
Construct Maps ◽  
Bayesian Interpolation ◽  
Occultation Data ◽  
High Degree ◽  
Radio Occultation Data

AbstractBayesian interpolation has previously been proposed as a strategy to construct maps of radio occultation (RO) data, but that proposition did not consider the diurnal dimension of RO data. In this work, the basis functions of Bayesian interpolation are extended into the domain of the diurnal cycle, thus enabling monthly mapping of radio occultation data in synoptic time and analysis of the atmospheric tides. The basis functions are spherical harmonics multiplied by sinusoids in the diurnal cycle up to arbitrary spherical harmonic degree and diurnal cycle harmonic. Bayesian interpolation requires a regularizer to impose smoothness on the fits it produces, thereby preventing the overfitting of data. In this work, a formulation for the regularizer is proposed and the most probable values of the parameters of the regularizer determined. Special care is required when obvious gaps in the sampling of the diurnal cycle are known to occur in order to prevent the false detection of statistically significant high-degree harmonics of the diurnal cycle in the atmosphere. Finally, this work probes the ability of Bayesian interpolation to generate a valid uncertainty analysis of the fit. The postfit residuals of Bayesian interpolation are dominated not by measurement noise but by unresolved variability in the atmosphere, which is statistically nonuniform across the globe, thus violating the central assumption of Bayesian interpolation. The problem is ameliorated by constructing maps of RO data using Bayesian interpolation that partially resolve the temporal variability of the atmosphere, constructing maps for approximately every 3 days of RO data.

scholarly journals Improvement of Rainfall Forecast by Assimilations of Ground-Based GPS Data and Radio Occultation Data

SOLA ◽  
2010 ◽  
Vol 6 ◽  
pp. 81-84 ◽  
Author(s):  
Hiromu Seko ◽  
Masaru Kunii ◽  
Yoshinori Shoji ◽  
Kazuo Saito
Keyword(s):  
Radio Occultation ◽  
Gps Data ◽  
Rainfall Forecast ◽  
Occultation Data ◽  
Radio Occultation Data

Backpropagation Processing of GPS Radio Occultation Data

2003 ◽  
pp. 415-422 ◽  
Author(s):  
Chi O. Ao ◽  
George A. Hajj ◽  
Thomas K. Meehan ◽  
Stephen S. Leroy ◽  
E. Robert Kursinski ◽  
...  
Keyword(s):  
Radio Occultation ◽  
Gps Radio Occultation ◽  
Occultation Data ◽  
Radio Occultation Data
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