Phase Transform Algorithm for Radio Occultation Data Processing

2009 ◽  
pp. 27-37
Author(s):  
J.J.W. Wilson ◽  
J.-P. Luntama
Keyword(s):  
Data Processing ◽  
Radio Occultation ◽  
Phase Transform ◽  
Occultation Data ◽  
Radio Occultation Data

GRACE-FO radio occultation data processing – First result

2020 ◽  
Author(s):  
Torsten Schmidt ◽  
Patrick Schreiner ◽  
Byron Iijima ◽  
Chi Ao
Keyword(s):  
Data Processing ◽  
Radio Occultation ◽  
Temperature Data ◽  
Gps Satellites ◽  
Weather And Climate ◽  
First Results ◽  
Software Updates ◽  
Occultation Data ◽  
Radio Occultation Data

<p>An objective of the GRACE-FO mission is the continuation of GRACE radio occultation measurements successfully performed between 2006 and 2017.</p> <p>GRACE and GRACE-FO radio occultations contribute to the overall radio occultation dataset used in weather and climate applications.</p> <p>Since mid-2019 rising occultations from GF1 are available while setting radio occultations from GF2 are still disabled. After several on-board software updates and raw data reader improvements about 280 daily GF1 radio occultations are available since March 2020.</p> <p>Currently GF1 radio occultation data are processed on the basis of different measured variables: For different GPS satellites a combination of L1CA/L2P, L1CA/L2C, or L1CA/L5 is available.</p> <p>In this study first results of GF1 processing are presented. Refractivity and temperature data up to an altitude of 60 km will be compared with ECMWF operational analyses and the quality of the different measured variables will be evaluated.</p>

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
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