Assessment of ionospheric variability from IRI-2016, SPIM-2017, and IGS-GIM using Digisonde and GPS observations over Cyprus

Panda, Sampad Kumar; Reddybattula, Kanaka Durga; Haralambous, Haris; Sharma, Sunil Kumar

doi:10.1007/s10509-020-03752-2

Cited by 13 publications

(2 citation statements)

References 101 publications

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“…This phenomenon is attributed to the fact the solar zenith angle of sun is lower during the equinox season and higher during the solstice seasons (Katsavrias et al 2022;. The descending phase of the solar cycle (2016 and 2017) experiences a fall in the value of TEC which was as a result of dropped in the sunspot number (Fu et al 2021;Oloketuyi et al 2019;Ansari et al 2017;Panda et al 2020;Lazzús et al 2022;Pilipenko et al 2006). The highest peak value of TEC recorded in this phase was ~67 TECU during the September equinox around the noon period (12:00UT) from the GPS-TEC while the lowest value of TEC recorded was observed from the NeQuick-2 model around the post-midnight period (02:00UT).…”

Section: Data and Methods Of Analysismentioning

confidence: 99%

Total Electron Content Variations at a Low Latitude East African Station and Its Comparison with IRI-2016, IRI-Plas2017 and NeQuick-2 Models during Solar Cycle 24

Kayode,

Okoh,

Onori

et al. 2023

Preprint

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Ionospheric modelling is one of the most crucial approaches to study the activities of the ionosphere particularly in regions where experimental data are not readily available. This research aims to study the variations of Total Electron Content (TEC) in a low latitude east African station (Addis Ababa) by comparing experimental values of TEC from the Global Positioning System (GPS) with predicted data from IRI-2016, IRI-Plas2017 and NeQuick-2 models during solar cycle 24 using Root Mean Square Error (RMSE) and Mean Absolute Error (MAE) metric analysis approach. An hourly interval profile computed on seasonal basis were used to study the behaviors of TEC. A monthly interval error profile plotted on annual basis was also used to investigate the deviations of the models from the GPS values. This study analyzed TEC data from 2011 to 2017, utilizing 84 months of available data. The results from this study showed TEC have their lowest values during the post-midnight hours (02:00UT) and highest values during the pre-noon hours (11:00UT). We also observed that Equinoxes have high value of TEC than Solstices except during the ascending and maximum phases where seasonal/winter anomalies were recorded. From our statistical analysis, MAE was observed to give error value of ~ 3 TECU (TEC units) lower than the RMSE. Also from this result, we concluded that MAE is a better statistical metric than RMSE. IRI-Plas2017 outperformed IRI-2016 and NeQuick-2 models in predicting TEC values in East Africa during solar cycle 24, with a 71.4% better performance compared to other models.

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Section: Data and Methods Of Analysismentioning

confidence: 99%

Total Electron Content Variations at a Low Latitude East African Station and Its Comparison with IRI-2016, IRI-Plas2017 and NeQuick-2 Models during Solar Cycle 24

Kayode,

Okoh,

Onori

et al. 2023

Preprint

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“…The extreme unsettling influence and transportation of energy and mass, which happens in the ionosphere, can impact space vehicles and their communication with stations on Earth. So ionospheric space weather has vital influence in human's economy and even day by day life (Alcay et al, 2012;Panda et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Regional ionospheric total electron content over Africa from ground-based GNSS observations

Moses¹,

Dodo²,

Ojigi³

et al. 2022

SA J of Geomatics

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Due to the wide use of GNSS receivers both on satellites at low earth orbit and on the ground, continuous and long-time ionospheric data with increasing accuracy have been obtained and used to study variations in the Earth’s ionosphere. Daily data from 2010.001 to 2017.365 sampled at 30 seconds from 104 African Geodetic Reference Frame (AFREF) dual-frequency GNSS Continuously Operating Reference Stations receivers distributed across Africa, were used in this study. Single Layer Model which assumes that all free electrons are concentrated in a shell of infinitesimal thickness, provides determining ionospheric total electron content value. In this study, the SLM model was used to derive total electron content values. TEC values obtained from the AFREF GNSS CORS measurements were compared with the TEC values from the global ionosphere maps provided by the Centre for Orbit Determination in Europe (CODE). The comparison was achieved by means of time series and wavelet analyses, and also by considering various model validation metrics. Comparative results for TEC estimates from both datasets based on goodness of fit measures, time series and wavelet analyses show good agreement on a statistical basis (r = 0.948) within the limits of experimental observation.

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GPS derived ionospheric TEC variability with different solar indices over Saudi Arab region

et al. 2020

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Assessment of ionospheric variability from IRI-2016, SPIM-2017, and IGS-GIM using Digisonde and GPS observations over Cyprus

Cited by 13 publications

References 101 publications

Total Electron Content Variations at a Low Latitude East African Station and Its Comparison with IRI-2016, IRI-Plas2017 and NeQuick-2 Models during Solar Cycle 24

Total Electron Content Variations at a Low Latitude East African Station and Its Comparison with IRI-2016, IRI-Plas2017 and NeQuick-2 Models during Solar Cycle 24

Regional ionospheric total electron content over Africa from ground-based GNSS observations

GPS derived ionospheric TEC variability with different solar indices over Saudi Arab region

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