Regional modeling of ionospheric peak parameters using GNSS data—An update for IRI

Wu, Liang; Limberger, M; Schmidt, Michaël; Dettmering, D; Hugentobler, Urs; Bilitza, D.; Jakowski, N.; Hoque, Mohammed Mainul; Wilken, Volker; Gerzen, Tatjana

doi:10.1016/j.asr.2014.12.006

Cited by 11 publications

(2 citation statements)

References 38 publications

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“…Moreover, the coefficients of the B‐spline representation resemble global VTEC maps in terms of the spatio‐temporal distribution and magnitude, which allow for inferring physical interpretations from the coefficients directly (Erdogan et al., 2020). B‐splines were applied to model ionospheric variables in various studies, for instance, modeling regional VTEC (Durmaz & Karslioglu, 2015; Goss, Schmidt, et al., 2020; Nohutcu et al., 2010; Schmidt et al., 2008; Zeilhofer et al., 2009) and global VTEC (Dettmering et al., 2014; Erdogan et al., 2017, 2020; Goss et al., 2019; Schmidt et al., 2011), the computation of corrections to a climatological reference model such as IRI (Liang et al., 2015), the estimation of key parameters of the Chapman function for electron density modeling (Limberger et al., 2013), and the combination of different space geodetic techniques for VTEC modeling (Dettmering et al., 2011).…”

Section: Introductionmentioning

confidence: 99%

Real‐Time Monitoring of Ionosphere VTEC Using Multi‐GNSS Carrier‐Phase Observations and B‐Splines

Erdogan¹,

Schmidt²,

Goss³

et al. 2021

Space Weather

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Real-time monitoring of the ionospheric plasma distribution and associated irregularities is of increasing importance for users of the Global Navigation Satellite Systems (GNSS) in various fields such as telecommunication, positioning, navigation, aviation, natural disaster monitoring and warning. It is also vital to monitor the ionosphere in real-time for forecasting space weather events. Rapid technological advances in the fast transmission of big data allow for generating and disseminating the essential ionosphere parameters, including the spatio-temporal variations of the Vertical Total Electron Content (VTEC), with low latency. The International GNSS Service (IGS) and its Ionosphere Associated Analysis Centers have been continuously providing Global Ionosphere Maps (GIMs) with improving resolution, accuracy, and latency since 1998 (Hernández-Pajares et al., 2009). By following the launch of the experimental IGS International

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Section: Introductionmentioning

confidence: 99%

Real‐Time Monitoring of Ionosphere VTEC Using Multi‐GNSS Carrier‐Phase Observations and B‐Splines

Erdogan¹,

Schmidt²,

Goss³

et al. 2021

Space Weather

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“…These authors reconstruct the 3D ionosphere by algebraic iterative methods. An alternative is to estimate the electron density as a linear combination of smooth and continuous basis functions, like, for example, spherical harmonics (SPHs; Schaer, 1999), B-splines (Schmidt et al, 2008;Zeilhofer, 2008;Zeilhofer et al, 2009;Olivares-Pulido et al, 2019), B-splines and trigonometric B-splines (Schmidt et al, 2015), B-splines and Chapman functions (Liang et al, 2015(Liang et al, , 2016, and empirical orthogonal functions and SPHs .…”

Section: Introductionmentioning

confidence: 99%

Analysis of different propagation models for the estimation of the topside ionosphere and plasmasphere with an ensemble Kalman filter

Gerzen¹,

Minkwitz

Schmidt³

et al. 2020

Ann. Geophys.

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Abstract. The accuracy and availability of satellite-based applications, like Global Navigation Satellite System (GNSS) positioning and remote sensing, crucially depend on the knowledge of the ionospheric electron density distribution. The tomography of the ionosphere is one of the major tools for providing links to specific ionospheric corrections and studying and monitoring physical processes in the ionosphere and plasmasphere. In this work, we apply an ensemble Kalman filter (EnKF) approach for the 4D electron density reconstruction of the topside ionosphere and plasmasphere, with the focus on the investigation of different propagation models, and compare them with the iterative reconstruction technique of simultaneous multiplicative column normalized method plus (SMART+). The slant total electron content (STEC) measurements of 11 low earth orbit (LEO) satellites are assimilated into the reconstructions. We conduct a case study on a global grid with altitudes between 430 and 20 200 km, for two periods of the year 2015, covering quiet to perturbed ionospheric conditions. Particularly the performance of the methods for estimating independent STEC and electron density measurements from the three Swarm satellites is analysed. The results indicate that the methods of EnKF, with exponential decay as the propagation model, and SMART+ perform best, providing, in summary, the lowest residuals.

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Multi-source data ingestion for IRI-2020 model: a combination of ground-based and space-borne observations

Hu,

Xu,

Luo

2024

GPS Solut

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Regional modeling of ionospheric peak parameters using GNSS data—An update for IRI

Cited by 11 publications

References 38 publications

Real‐Time Monitoring of Ionosphere VTEC Using Multi‐GNSS Carrier‐Phase Observations and B‐Splines

Real‐Time Monitoring of Ionosphere VTEC Using Multi‐GNSS Carrier‐Phase Observations and B‐Splines

Analysis of different propagation models for the estimation of the topside ionosphere and plasmasphere with an ensemble Kalman filter

Multi-source data ingestion for IRI-2020 model: a combination of ground-based and space-borne observations

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