IRI the International Standard for the Ionosphere
George Mason University, Department of Physics and Astronomy, Fairfax,
Virginia, USA
NASA, Goddard Space Flight Center, Heliospheric Laboratory, Greenbelt,
Maryland, USA
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197 citations as recorded by crossref.
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- An Investigation of Ionospheric TEC Prediction Maps Over China Using Bidirectional Long Short‐Term Memory Method S. Shi et al. 10.1029/2022SW003103
- Machine learning modeling of pavement performance and IRI prediction in flexible pavement A. Alnaqbi et al. 10.1007/s41062-024-01688-y
- Empirical Data Assimilation for Merging Total Electron Content Data with Empirical and Physical Models E. Forootan et al. 10.1007/s10712-023-09788-7
- A Combination Prediction Model of Long-Term Ionospheric foF2 Based on Entropy Weight Method H. Bai et al. 10.3390/e22040442
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- Ionospheric Variability over the Brazilian Equatorial Region during the Minima Solar Cycles 1996 and 2009: Comparison between Observational Data and the IRI Model Â. Santos et al. 10.3390/atmos14010087
- A Review on CubeSat Missions for Ionospheric Science C. Francisco et al. 10.3390/aerospace10070622
- Magnetic Conjugacy of Pc1 Waves and Isolated Proton Precipitation at Subauroral Latitudes: Importance of Ionosphere as Intensity Modulation Region M. Ozaki et al. 10.1029/2020GL091384
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- Scale‐Separated Dynamic Mode Decomposition and Ionospheric Forecasting D. Alford‐Lago et al. 10.1029/2022RS007637
- Improving forecasting accuracy the F2-layer peak characteristics using artificial neural network K. Sidorenko et al. 10.1016/j.asr.2022.12.006
- AIM-E: E-Region Auroral Ionosphere Model V. Nikolaeva et al. 10.3390/atmos12060748
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- Adaptation of the bottomside electron density profile of the IRI model to data of topside radiosounding P. Denisenko et al. 10.1016/j.asr.2021.02.030
- Performance of IRI 2016 model in predicting total electron content (TEC) compared with GPS-TEC over East Africa during 2019–2021 E. Sulungu 10.1038/s41598-024-59624-0
- Trends in Ionospheric Solar Activity Indices M. Deminov 10.1134/S0016793224600589
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- Possibilities of Estimating F2 Layer Peak Plasma Frequency Using HF Radiation from High Apogee Satellites over Arctic Region I. Krasheninnikov & G. Givishvili 10.3390/rs13214225
- Towards Millimeter-Level Accuracy in GNSS-Based Space Geodesy: A Review of Error Budget for GNSS Precise Point Positioning X. Li et al. 10.1007/s10712-023-09785-w
- Modeling the dominance of the gradient drift or Kelvin–Helmholtz instability in sheared ionospheric E × B flows C. Rathod et al. 10.1063/5.0047807
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- Evaluation of the Mid-Latitude Ionospheric trough Using GRACE Data K. Lubyk et al. 10.3390/rs14174384
- Climatological study of the ion temperature in the ionosphere as recorded by Millstone Hill incoherent scatter radar and comparison with the IRI model A. Pignalberi et al. 10.1016/j.asr.2020.10.025
- A sequential calibration approach based on the ensemble Kalman filter (C-EnKF) for forecasting total electron content (TEC) M. Kosary et al. 10.1007/s00190-022-01623-y
- Estimating Ionospheric Height From Amplitude Scintillation Signatures in SAR Images F. Betancourt-Payan et al. 10.1109/LGRS.2024.3431023
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- On the variations in equatorial and low-latitude GPS-TEC and assessment of NeQuick-2, IRI-2016 and IRI-2020 models in the African longitude during solar cycle 24–25 A. Ogwala et al. 10.1016/j.asr.2024.05.031
- Low‐Latitude Plasma Drifts From the Horizontal Neutral Wind Model and a Coupled Ionosphere‐Electric Field Model J. Eccles & C. Valladares 10.1029/2020JA029056
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- Forecasting ionospheric TEC using least squares support vector machine and moth-flame optimization methods in China J. Tang et al. 10.1016/j.asr.2024.04.053
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- MaxEnt SeismoSense Model: Ionospheric Earthquake Anomaly Detection Based on the Maximum Entropy Principle L. Wang et al. 10.3390/atmos15040419
- Initial orbit determination with the multibeam radar sensor BIRALES M. Losacco et al. 10.1016/j.actaastro.2019.10.043
- Towards a Real-Time Description of the Ionosphere: A Comparison between International Reference Ionosphere (IRI) and IRI Real-Time Assimilative Mapping (IRTAM) Models A. Pignalberi et al. 10.3390/atmos12081003
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- Dependence of annual asymmetry in <i>NmF2</i> on local time V. Shubin et al. 10.31857/S0016794024010091
- Comparison of IRI‐2016 F2 Layer Model Parameters with Ionosonde Measurements F. Arıkan et al. 10.1029/2019JA027048
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- Comparison of VTEC from GPS and IRI-2007, IRI-2012 and IRI-2016 over Sukkur Pakistan R. Shahzad et al. 10.1007/s10509-021-03947-1
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- A Global Empirical Model of Electron Density Profile in the F Region Ionosphere Basing on COSMIC Measurements Q. Li et al. 10.1029/2020SW002642
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- A height-dependent climatological model of the equatorial ionospheric zonal plasma drifts (EZDrifts): Description and application to an analysis of the longitudinal variations of the zonal drifts A. Massoud et al. 10.1051/swsc/2023006
- CLIMF2: A climatological model of the ionospheric F2 layer. Part 1: Model methodology D. Edwards et al. 10.1016/j.asr.2023.12.021
- Localized total electron content enhancements in the Southern Hemisphere I. Edemskiy 10.5194/angeo-38-591-2020
- The Potential for a Networked Ionospheric Sounding Constellation A. Chartier 10.1029/2022SW003089
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Latest update: 22 Nov 2024
Short summary
This paper gives a brief overview over the International Reference Ionosphere (IRI) project and model. IRI is recognized as the official standard for the ionosphere by the International Standardization Organization (ISO). Of great importance are the external drivers of the model that help IRI to represent ionospheric conditions as realistically as possible. The paper discusses the solar and ionospheric measurements that are used as drivers and presents recent improvements and changes.
This paper gives a brief overview over the International Reference Ionosphere (IRI) project and...