Global median model of the F2-layer peak height based on ionospheric radio-occultation and ground-based Digisonde observations

Шубин, В.Н.

doi:10.1016/j.asr.2015.05.029

Cited by 94 publications

(83 citation statements)

References 36 publications

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“…This model is based on COSMIC radio-occultation observations and digisonde h m F 2 data. Figure 3 (upper panel) shows that the empirical model by Shubin (2015) perfectly coincides with our theoretical h m F 2 variations even in details (cf. the period 1971-1972 or 2012-2015).…”

Section: F-layer Parameter Long-term Variationsmentioning

confidence: 53%

“…Although this analytical expression was obtained for a daytime mid-latitude stationary F 2 -layer, without including the thermospheric wind effects, it gives reasonable h m F 2 values. This is confirmed by a comparison with a modern empirical monthly median h m F 2 model by Shubin (2015) included to the last version of IRI (Bilitza et al, 2017). To check this result we have used the MSIS-86 monthly median values of the thermospheric parameters in equation (3).…”

Section: Discussionmentioning

confidence: 82%

“…The difference with the Shimazaki (1955) h m F 2 values reaches 50-70 km rather than 20 ± 10 km (Ulich, 2000). A new global monthly median h m F 2 empirical model by Shubin (2015) was used as a reference to compare with the theoretically calculated h m F 2 variation (Fig. 3).…”

Section: F-layer Parameter Long-term Variationsmentioning

confidence: 99%

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Long-term variations of the upper atmosphere parameters on Rome ionosonde observations and their interpretation

Perrone

Mikhailov

Cesaroni

et al. 2017

J. Space Weather Space Clim.

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-A recently proposed self-consistent approach to the analysis of thermospheric and ionospheric long-term trends has been applied to Rome ionosonde summer noontime observations for the period. This approach includes: (i) a method to extract ionospheric parameter long-term variations; (ii) a method to retrieve from observed f o F 1 neutral composition (O, O 2 , N 2 ), exospheric temperature, Tex and the total solar EUV flux with l < 1050 Å; and (iii) a combined analysis of the ionospheric and thermospheric parameter long-term variations using the theory of ionospheric F-layer formation. Atomic oxygen, [O] period which is mainly due to atomic oxygen decrease after ∼1990. A linear trend in (dh m F 2 ) 11y estimated over the period is very small and insignificant reflecting the absence of any significant trend in neutral temperature. The retrieved neutral gas density, r atomic oxygen, [O] and exospheric temperature, Tex long-term variations are controlled by solar and geomagnetic activity, i.e. they have a natural origin. The residual trends estimated over the period of ∼5 solar cycles are very small (<0.5% per decade) and statistically.

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Section: F-layer Parameter Long-term Variationsmentioning

confidence: 53%

Section: Discussionmentioning

confidence: 82%

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Long-term variations of the upper atmosphere parameters on Rome ionosonde observations and their interpretation

Perrone

Mikhailov

Cesaroni

et al. 2017

J. Space Weather Space Clim.

View full text Add to dashboard Cite

show abstract

“…[] used ionosonde data with a spherical harmonic expansion in local time and modified dip angle to create a new bottomside thickness representation, which was later included in IRI2012. Shubin [] used radio occultation, ionosonde, and topside sounder data to create a new global h m F 2 model, which is slated to replace the IRI's traditional h m F 2 model in IRI2016 [ Bilitza et al ., ]. Other global models include the nonlinear models of Hoque and Jakowski [, ], which provide h m F 2 and N m F 2 , respectively.…”

Section: Introductionmentioning

confidence: 99%

The Empirical Canadian High Arctic Ionospheric Model (E‐CHAIM): N_mF₂ and h_mF₂

et al. 2017

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We present here the Empirical Canadian High Arctic Ionospheric Model (E‐CHAIM) quiet NmF2, perturbation NmF2, and quiet hmF2 models. These models provide peak ionospheric characteristics for a domain above 50°N geomagnetic latitude. Model fitting is undertaken using all available ionosonde and radio occultation electron density data, constituting a data set of over 28 million observations. A comprehensive validation of the model is undertaken, and performance is compared to that of the International Reference Ionosphere (IRI). In the case of the quiet NmF2 model, the E‐CHAIM model provides a systematic improvement over the IRI Union Radio Scientifique Internationale maps. At all stations within the polar cap, we see drastic RMS error improvements over the IRI by up to 1.3 MHz in critical frequency (up to 60% in NmF2). These improvements occur primarily during equinox periods and at low solar activities, decreasing somewhat as one tends to lower latitudes. Qualitatively, the E‐CHAIM is capable of representing auroral enhancements in NmF2, as well as the location and extent of the main ionospheric trough, not reproduced by the IRI. The included NmF2 storm model demonstrates improvements over the IRI by up to 35% and over the quiet time E‐CHAIM model by up to 30%. In terms of hmF2, over the validation periods used in this study, we found overall RMS errors of ~13 km for E‐CHAIM, with IRI2007 overall hmF2 errors ranging between 16 km and 22 km. The E‐CHAIM performs comparably to or slightly better than the IRI within the polar cap; however, significant improvements are found within the auroral oval.

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“…where is total number of voxels, indicates a length along which -th GPS ray passes through -t electron density at -th voxel and is the error of measurement and approximation (Das & Shukla 20112015. The matrix, , is commonly called as a geometry matrix since it contains geometric information o defined voxels.…”

Section: Geometry Matrixmentioning

confidence: 99%

Tomography Reconstruction of Ionospheric Electron Density with Empirical Orthonormal Functions Using Korea GNSS Network

Hong¹,

Kim²,

Chung³

et al. 2017

Journal of Astronomy and Space Sciences

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In South Korea, there are about 80 Global Positioning System (GPS) monitoring stations providing total electron content (TEC) every 10 min, which can be accessed through Korea Astronomy and Space Science Institute (KASI) for scientific use. We applied the computerized ionospheric tomography (CIT) algorithm to the TEC dataset from this GPS network for monitoring the regional ionosphere over South Korea. The algorithm utilizes multiplicative algebraic reconstruction technique (MART) with an initial condition of the latest International Reference Ionosphere-2016 model (IRI-2016). In order to reduce the number of unknown variables, the vertical profiles of electron density are expressed with a linear combination of empirical orthonormal functions (EOFs) that were derived from the IRI empirical profiles. Although the number of receiver sites is much smaller than that of Japan, the CIT algorithm yielded reasonable structure of the ionosphere over South Korea. We verified the CIT results with NmF2 from ionosondes in Icheon and Jeju and also with GPS TEC at the center of South Korea. In addition, the total time required for CIT calculation was only about 5 min, enabling the exploration of the vertical ionospheric structure in near real time.

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Global median model of the F2-layer peak height based on ionospheric radio-occultation and ground-based Digisonde observations

Cited by 94 publications

References 36 publications

Long-term variations of the upper atmosphere parameters on Rome ionosonde observations and their interpretation

Long-term variations of the upper atmosphere parameters on Rome ionosonde observations and their interpretation

The Empirical Canadian High Arctic Ionospheric Model (E‐CHAIM): N_mF₂ and h_mF₂

Tomography Reconstruction of Ionospheric Electron Density with Empirical Orthonormal Functions Using Korea GNSS Network

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Global median model of the F2-layer peak height based on ionospheric radio-occultation and ground-based Digisonde observations

Cited by 94 publications

References 36 publications

Long-term variations of the upper atmosphere parameters on Rome ionosonde observations and their interpretation

Long-term variations of the upper atmosphere parameters on Rome ionosonde observations and their interpretation

The Empirical Canadian High Arctic Ionospheric Model (E‐CHAIM): NmF2 and hmF2

Tomography Reconstruction of Ionospheric Electron Density with Empirical Orthonormal Functions Using Korea GNSS Network

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Product

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The Empirical Canadian High Arctic Ionospheric Model (E‐CHAIM): N_mF₂ and h_mF₂