Comparison of IRI_PLAS and IRI_2012 Model Predictions with GPS-TEC Measurements in Different Latitude Regions

Alçay, Salih; Öztan, Gürkan; Selvi, Hüseyin Zahit

doi:10.4401/ag-7311

Cited by 20 publications

(9 citation statements)

References 26 publications

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“…Of particular concern to Kumar (2016) is the difference between EUV (particularly 26–34 nm) and the solar flux parameters used in the IRI model; in IRI‐2012, the TEC output depends on N m F 2 and h m F 2 , which depend on IG12 and Rz12, respectively. Many sources cite that differences between IRI‐TEC and TEC data tend to be less significant at midlatitudes than low and high latitudes (Alcay et al., 2017; Kumar, 2016; Kumar et al., 2015).…”

Section: Evaluation Of Model Performancementioning

confidence: 99%

A New Model for Ionospheric Total Electron Content: The Impact of Solar Flux Proxies and Indices

et al. 2021

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We present a new high‐resolution empirical model for the ionospheric total electron content (TEC). TEC data are obtained from the global navigation satellite system (GNSS) receivers with a 1° × 1° spatial resolution and 5‐min temporal resolution. The linear regression model is developed at 45°N, 0°E for the years 2000–2019 with 30‐min temporal resolution, unprecedented for typical empirical ionospheric models. The model describes dependency of TEC on solar flux, season, geomagnetic activity, and local time. Parameters describing solar and geomagnetic activity are evaluated. In particular, several options for solar flux input to the model are compared, including the 10.7 cm solar radio flux (F10.7), the Mg II core‐to‐wing ratio, and formulations of the solar extreme ultraviolet flux (EUV). Ultimately, the extreme ultraviolet flux presented by the Flare Irradiance Spectral Model, integrated from 0.05 to 105.05 nm, best represents the solar flux input to the model. TEC time delays to this solar parameter on the order of several days as well as seasonal modulation of the solar flux terms are included. The Ap3 index and its history are used to reflect the influence of geomagnetic activity. The root mean squared error of the model (relative to the mean TEC observed in the 30‐min window) is 1.9539 TECu. A validation of this model for the first 3 months of 2020 shows excellent agreement with data. The new model shows significant improvement over the International Reference Ionosphere 2016 (IRI‐2016) when the two are compared during 2008 and 2012.

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Section: Evaluation Of Model Performancementioning

confidence: 99%

A New Model for Ionospheric Total Electron Content: The Impact of Solar Flux Proxies and Indices

et al. 2021

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“…Of particular concern to Kumar (2016) is the difference between EUV (particularly 26 -34 nm) and the solar flux parameters used in the IRI model; in IRI-2012, the TEC output depends on N m f 2 and h m f 2 , which depend on IG12 and Rz12 respectively. Many sources cite that differences between IRI-TEC and TEC data tend to be less significant at mid-latitudes than low and high latitudes (Kumar, 2016;Kumar et al, 2015;Alcay et al, 2017).…”

Section: Comparison With International Reference Ionospherementioning

confidence: 99%

A new model for ionospheric total electron content: the impact of solar flux proxies and indices

Tamburri

Гончаренко

Tobiska

et al. 2020

Preprint

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We present a new high resolution empirical model for the ionospheric total electron content (TEC). TEC data are obtained from the global navigation satellite system (GNSS) receivers with a 1 o x 1 o spatial resolution and 5 minute temporal resolution. The linear regression model is developed at 45 o N, 0 o E for the years 2000 -2019 with 30 minute temporal resolution, unprecedented for typical empirical ionospheric models. The model describes dependency of TEC on solar flux, season, geomagnetic activity, and local time. Parameters describing solar and geomagnetic activity are evaluated. In particular, several options for solar flux input to the model are compared, including the 10.7cm solar radio flux (F 10.7 ), the Mg II core-to-wing ratio, and formulations of the solar extreme ultraviolet flux (EUV). Ultimately, the extreme ultraviolet flux presented by the Flare Irradiance Spectral Model, integrated from 0.05 to 105.05 nm, best represents the solar flux input to the model. TEC time delays to this solar parameter on the order of several days as well as seasonal modulation of the solar flux terms are included. The Ap 3 index and its history are used to reflect the influence of geomagnetic activity. The root mean squared error of the model (relative to the mean TEC observed in the 30-min window) is 1.9539 TECu. A validation of this model for the first three months of 2020 shows excellent agreement with data. The new model shows significant improvement over the

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“…Since IRI-model provides the ionospheric parameters as much as 2000 km, it will not longer correctly predict the the ionospheric parameters up to GPS satellites located in altitude of 20,200 km. It is critical to extrapolate the ionosphere as much as the GPS satellite height of the IRI-model to overcome this situation (Alçay et al 2017). The IRI-Plas model provides many ionospheric parameters with an internet interface presented with the aid of the IOBOLAB group at www.ionolab.org.…”

Section: Introductionmentioning

confidence: 99%

Performance Evaluation of IRI-Plas 2017 model with Ionosonde Data Measurements of Ionospheric Parameters

Endeshaw

Seyoum

2022

Preprint

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This study presents the performance evaluation of International Reference Ionosphere extended to the plasmasphere (IRI-Plas 2017) model from the Addis Ababa ionosonde station, Ethiopia ionospheric parameters measurement with geographic latitude 9.00o N and longitude 38.70o E; geomagnetic latitude 0.16, geomagnetic longitude 110.44) in selected days of the year 2014. During comparison, hourly and day-to-day variability of ionospheric parameters of the electron density profile, peak electron density (NmF2), peak height (hmF2) and critical frequency (foF2) measurements are consider. In the evaluation of the IRI-Plas 2017 model with the ionosonde data, the percentage deviation and the correlation coefficient (R) is used as the measure of the performance of the IRI-Plas 2017 model. The overall results, show that the IRI-Plas 2017 model mostly overestimates in most altitudes and hours of electron density measurements. The IRI-Plas 2017 model has a good agreement with the ionosonde electron density measurement from 100 km to 200 km altitude and mostly during in between 0:00-06:00 UT and 12:00-18:00 UT hours, while the model biases in other altitudes and hours with overestimate or underestimate in the ionosonde electron density measurements. The IRI-Plas 2017 model has a good correlation during after midnight and around midday hours with about ±2 percentage deviation from the ionosonde electron density measurement. The model has high percentage deviation value of electron density measurements mostly in between altitudes from 200 km to 450 km and during early nighttime and before midnight hours. The IRI-Plas 2017 model measurements of the NmF2, hmF2 and foF2 mostly underestimates from the ionosonde data during the night-time (18:00 UT- 06:00 UT) and overestimates during day-time (06:00 UT-18:00 UT). The IRI-Plas 2017 model measurement of the foF2 values are in a good agreement with the ionosonde result than in hmF2 and NmF2 and the model measurement of the NmF2 values are closer than hmF2.

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Comparison of IRI_PLAS and IRI_2012 Model Predictions with GPS-TEC Measurements in Different Latitude Regions

Abstract: ABSTRACT

Cited by 20 publications

References 26 publications

A New Model for Ionospheric Total Electron Content: The Impact of Solar Flux Proxies and Indices

A New Model for Ionospheric Total Electron Content: The Impact of Solar Flux Proxies and Indices

A new model for ionospheric total electron content: the impact of solar flux proxies and indices

Performance Evaluation of IRI-Plas 2017 model with Ionosonde Data Measurements of Ionospheric Parameters

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