Comparison of the CHAMP radio occultation data with the Canadian advanced digital ionosonde in the Polar Regions

2009 ◽  
Vol 44 (11) ◽  
pp. 1304-1308 ◽  
Author(s):  
Samaneh Sadighi ◽  
P.T. Jayachandran ◽  
N. Jakowski ◽  
J.W. MacDougall
Keyword(s):  
Radio Occultation ◽  
Polar Regions ◽  
Occultation Data ◽  
Radio Occultation Data

scholarly journals Evaluation of E Layer Dominated Ionosphere Events Using COSMIC/FORMOSAT-3 and CHAMP Ionospheric Radio Occultation Data

2020 ◽  
Vol 12 (2) ◽  
pp. 333
Author(s):  
Sumon Kamal ◽  
Norbert Jakowski ◽  
Mohammed M. Hoque ◽  
Jens Wickert
Keyword(s):  
Radio Occultation ◽  
Geomagnetic Storms ◽  
Temporal Variations ◽  
Polar Regions ◽  
Solar Cycles ◽  
Satellite Mission ◽  
Occultation Data ◽  
Electron Density Profiles ◽  
Cycle Dependent ◽  
Radio Occultation Data

At certain geographic locations, especially in the polar regions, the ionization of the ionospheric E layer can dominate over that of the F2 layer. The associated electron density profiles show their ionization maximum at E layer heights between 80 and 150 km above the Earth’s surface. This phenomenon is called the “E layer dominated ionosphere” (ELDI). In this paper we systematically investigate the characteristics of ELDI occurrences at high latitudes, focusing on their spatial and temporal variations. In our study, we use ionospheric GPS radio occultation data obtained from the COSMIC/FORMOSAT-3 (Constellation Observing System for Meteorology, Ionosphere, and Climate/Formosa Satellite Mission 3) and CHAMP (Challenging Minisatellite Payload) satellite missions. The entire dataset comprises the long period from 2001 to 2018, covering the previous and present solar cycles. This allows us to study the variation of the ELDI in different ways. In addition to the geospatial distribution, we also examine the temporal variation of ELDI events, focusing on the diurnal, the seasonal, and the solar cycle dependent variation. Furthermore, we investigate the spatiotemporal dependency of the ELDI on geomagnetic storms.

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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