University of Oulu

Bires, A., Roininen, L., Damtie, B., Nigussie, M., Vanhamäki, H. (2016) Study of TEC fluctuation via stochastic models and Bayesian inversion. Radio Science, 51 (11), 1772-1782. doi:10.1002/2016RS005959

Study of TEC fluctuation via stochasticmodels and Bayesian inversion

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Author: Bires, A.1,2; Roininen, L.3,4; Damtie, B.1;
Organizations: 1Washera Geospace and Radar Science Laboratory, Bahir Dar University, Bahir Dar, Ethiopia
2Ionospheric Research Group, University of Oulu, Oulu, Finland
3Sodankylä Geophysical Observatory, University of Oulu, Sodankylä, Finland
4Department of Statistics, University of Warwick, Coventry, UK
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 1.1 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe2018050723596
Language: English
Published: American Geophysical Union, 2016
Publish Date: 2018-05-07
Description:

Abstract

We propose stochastic processes to be used to model the total electron content (TEC) observation. Based on this, we model the rate of change of TEC (ROT) variation during ionospheric quiet conditions with stationary processes. During ionospheric disturbed conditions, for example, when irregularity in ionospheric electron density distribution occurs, stationarity assumption over long time periods is no longer valid. In these cases, we make the parameter estimation for short time scales, during which we can assume stationarity. We show the relationship between the new method and commonly used TEC characterization parameters ROT and the ROT Index (ROTI). We construct our parametric model within the framework of Bayesian statistical inverse problems and hence give the solution as an a posteriori probability distribution. Bayesian framework allows us to model measurement errors systematically. Similarly, we mitigate variation of TEC due to factors which are not of ionospheric origin, like due to the motion of satellites relative to the receiver, by incorporating a priori knowledge in the Bayesian model. In practical computations, we draw the so-called maximum a posteriori estimates, which are our ROT and ROTI estimates, from the posterior distribution. Because the algorithm allows to estimate ROTI at each observation time, the estimator does not depend on the period of time for ROTI computation. We verify the method by analyzing TEC data recorded by GPS receiver located in Ethiopia (11.6∘N, 37.4∘E). The results indicate that the TEC fluctuations caused by the ionospheric irregularity can be effectively detected and quantified from the estimated ROT and ROTI values.

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Series: Radio science
ISSN: 0048-6604
ISSN-E: 1944-799X
ISSN-L: 0048-6604
Volume: 51
Issue: 11
Pages: 1772 - 1782
DOI: 10.1002/2016RS005959
OADOI: https://oadoi.org/10.1002/2016RS005959
Type of Publication: A1 Journal article – refereed
Field of Science: 115 Astronomy and space science
Subjects:
Funding: This work has been funded by the American Air Force Office of Scientific Researches (AFOSR), USA, under the project Understanding the unique characteristics of equatorial ionosphere (FA8655-13-1-3052), and Academy of Finland (application 250215, Finnish Program for Centers of Excellence in Research 2012–2017), Ministry for Foreign Affairs of Finland (HEI-ICI project HELM406-10), and Center for International Mobility of Finland (North-South project East-Africa Techno mathematics IV 2013–2015 project 2013-NSS-1).
Copyright information: © 2016. American Geophysical Union. Published in this repository with the kind permission of the publisher.