scholarly journals International Reference Ionosphere 2016: From ionospheric climate to real-time weather predictions

Space Weather ◽  
2017 ◽  
Vol 15 (2) ◽  
pp. 418-429 ◽  
Author(s):  
D. Bilitza ◽  
D. Altadill ◽  
V. Truhlik ◽  
V. Shubin ◽  
I. Galkin ◽  
...  
Atmosphere ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 1003
Author(s):  
Alessio Pignalberi ◽  
Marco Pietrella ◽  
Michael Pezzopane

This paper focuses on a detailed comparison, based on the F2-layer peak characteristics foF2 and hmF2, between the International Reference Ionosphere (IRI), which is a climatological empirical model of the terrestrial ionosphere, and the IRI Real-Time Assimilative Mapping (IRTAM) procedure, which is a real-time version of IRI based on data assimilation from a global network of ionosondes. To perform such a comparison, two different kinds of datasets have been considered: (1) foF2 and hmF2 as recorded by 40 ground-based ionosondes spread all over the world from 2000 to 2019; (2) foF2 and hmF2 from space-based COSMIC/FORMOSAT-3 radio occultation measurements recorded from 2006 to 2018. The aim of the paper is to understand whether and how much IRTAM improves IRI foF2 and hmF2 outputs for different locations and under different diurnal, seasonal, solar and magnetic activity conditions. The main outcomes of the study are: (1) when ionosonde observations are considered for validation, IRTAM significantly improves the IRI foF2 modeling both in accuracy and precision, while a slight improvement in the IRI hmF2 modeling is observed for specific locations and conditions; (2) when COSMIC observations are considered for validation, no noticeable improvement is observed from the IRTAM side for both foF2 and hmF2. Indeed, IRTAM can improve the IRI foF2 description only nearby the assimilated ionosonde locations, while the IRI hmF2 description is always more accurate and precise than IRTAM one.


2021 ◽  
Author(s):  
Ivan Galkin ◽  
Artem Vesnin ◽  
Bodo Reinisch ◽  
Dieter Bilitza

<p>Real-time assimilative <em>empirical </em>models based on the International Reference Ionosphere (IRI) [1], a 3D quiet-time climatology model of the ionospheric plasma density, provide prompt weather specification by adjusting IRI definitions into a better match with the available measurements and geospace activity indicators [2]. The IRI-based Real-Time Assimilative Model (IRTAM) [3] is one of such Real-Time IRI operational ionospheric weather models based on the low-latency sensor inputs from the Global Ionosphere Radio Observatory (GIRO) [4].</p><p>IRTAM leverages predictive properties of the underlying IRI expansion basis formalism [5] that treats dynamics of the ionospheric plasma in terms of its harmonics, both temporal and spatial. It uses Non-linear Error Compensation Technique with Associative Restoration (NECTAR) technique [6] to first detect multi-scale inherent diurnal periodicity of the differences between GIRO measurements and the underlying IRI climatology. Then, under the assumption that variations in time at periodic, planetary-scale <em>Eigen</em> scales (diurnal, half-diurnal, 8-hour, etc.) translate to their spatial properties, it globally interpolates and extrapolates each diurnal harmonic individually. This approach allowed NECTAR to associate observed fragments of the activity at GIRO locations with the unveiling grand-scale weather processes of the matching variability scales, as the ground observatories co-rotate with the Earth.</p><p>Predictive properties of IRTAM are discussed in order to establish the baseline predictability of the ionospheric dynamics that analyzes only the latest 24-hour history of its deviation from the expected behavior. Concepts for the next generation empirical forecast models are outlined that would leverage the same principle of associative restoration to evaluate the geospace activity timeline and its subtle associations with subsequent storm-time behavior of the ionosphere.</p><p><strong>References</strong></p><p>[1] Bilitza, D. (ed.) (1990), International Reference Ionosphere 1990, 155 pages, National Space Science Data Center, NSSDC/WDC-A-R&S 90-22, Greenbelt, Maryland, November 1990.</p><p>[2] Bilitza, D., D. Altadill, V. Truhlik, V. Shubin, I. Galkin, B. Reinisch, and X. Huang (2017), International Reference Ionosphere 2016: From ionospheric climate to real-time weather predictions, Space Weather, 15, 418-429, doi:10.1002/2016SW001593.</p><p>[3] Galkin, I. A., B. W. Reinisch, X. Huang, and D. Bilitza (2012), Assimilation of GIRO Data into a Real-Time IRI, Radio Sci., 47, RS0L07, doi:10.1029/2011RS004952.</p><p>[4] Reinisch, B.W. and I.A. Galkin (2011), Global Ionospheric Radio Observatory (GIRO), Earth Planets Space, vol. 63 no. 4 pp. 377-381, doi:10.5047/eps.2011.03.001</p><p>[5] International Telecommunications Union (2009), ITU-R reference ionospheric characteristics, Recommendation P.1239-2 (10/2009). Retrieved from http://www.itu.int/rec/R-REC-P.1239/en.</p><p>[6] Galkin, I. A., B. W. Reinisch, A. Vesnin, et al., (2020) Assimilation of Sparse Continuous Near-Earth Weather Measurements by NECTAR Model Morphing, Space Weather, 18, e2020SW002463, doi:10.1029/2020SW002463.</p>


Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1551
Author(s):  
Zihuai Guo ◽  
Yibin Yao ◽  
Jian Kong ◽  
Gang Chen ◽  
Chen Zhou ◽  
...  

Global navigation satellite system (GNSS) can provide dual-frequency observation data, which can be used to effectively calculate total electron content (TEC). Numerical studies have utilized GNSS-derived TEC to evaluate the accuracy of ionospheric empirical models, such as the International Reference Ionosphere model (IRI) and the NeQuick model. However, most studies have evaluated vertical TEC rather than slant TEC (STEC), which resulted in the introduction of projection error. Furthermore, since there are few GNSS observation stations available in the Antarctic region and most are concentrated in the Antarctic continent edge, it is difficult to evaluate modeling accuracy within the entire Antarctic range. Considering these problems, in this study, GNSS STEC was calculated using dual-frequency observation data from stations that almost covered the Antarctic continent. By comparison with GNSS STEC, the accuracy of IRI-2016 and NeQuick2 at different latitudes and different solar radiation was evaluated during 2016–2017. The numerical results showed the following. (1) Both IRI-2016 and NeQuick2 underestimated the STEC. Since IRI-2016 utilizes new models to represent the F2-peak height (hmF2) directly, the IRI-2016 STEC is closer to GNSS STEC than NeQuick2. This conclusion was also confirmed by the Constellation Observing System for Meteorology Ionosphere and Climate (COSMIC) occultation data. (2) The differences in STEC of the two models are both normally distributed, and the NeQuick2 STEC is systematically biased as solar radiation increases. (3) The root mean square error (RMSE) of the IRI-2016 STEC is smaller than that of the NeQuick2 model, and the RMSE of the two modeling STEC increases with solar radiation intensity. Since IRI-2016 relies on new hmF2 models, it is more stable than NeQuick2.


2015 ◽  
Vol 21 (3) ◽  
pp. 706-711
Author(s):  
Simona Miclaus ◽  
Paul Bechet ◽  
Mircea Stanic ◽  
Cora Iftode

Abstract Radiocommunications in the HF band depend on the ionospheric parameters of radiowaves reflexion, though the quality of a radio link depends on: the time of day; season; solar cycle; geographical position. Taking into account the ionosphere characteristics over Romania, a forecasting is made over four cities in our country in order to provide the values of the critical frequency foF2 of the F2 ionospheric layer over a 24 hours cycle. A comparative analysis of this parameter is applied by using the International Reference Ionosphere model and interpolated experimental data collected from the European Ionosonde Service. Results show that the f0F2 values are slightly underestimated in all four locations in the model versus measurements, sustaining the necessity of own measurements in order to prepare quality data links in Romania if HF band is to be used for emergency data communications.


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