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

Author(s):  
Flavio Petricca ◽  
Gael Cascioli ◽  
Antonio Genova

<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>

Author(s):  
John Bosco Habarulema ◽  
Daniel Okoh ◽  
Dalia Burešová ◽  
Babatunde Rabiu ◽  
Mpho Tshisaphungo ◽  
...  

2021 ◽  
Author(s):  
Özgür Karatekin ◽  
Ananya Krishnan ◽  
Nayeem Ebrahimkutty ◽  
Greg Henry ◽  
Ahmed El Fadhel ◽  
...  

2021 ◽  
Vol 38 (5) ◽  
pp. 951-961
Author(s):  
Stephen S. Leroy ◽  
Chi O. Ao ◽  
Olga P. Verkhoglyadova ◽  
Mayra I. Oyola

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.


SOLA ◽  
2010 ◽  
Vol 6 ◽  
pp. 81-84 ◽  
Author(s):  
Hiromu Seko ◽  
Masaru Kunii ◽  
Yoshinori Shoji ◽  
Kazuo Saito

Author(s):  
Chi O. Ao ◽  
George A. Hajj ◽  
Thomas K. Meehan ◽  
Stephen S. Leroy ◽  
E. Robert Kursinski ◽  
...  

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