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Neural network based model for global Total Electron Content forecasting

Papers from SWICo members

Claudio Cesaroni, Luca Spogli, Angela Aragon-Angel, Michele Fiocca, Varuliator Dear, Giorgiana De Franceschi, Vincenzo Romano

We describe a novel empirical model to forecast, one day in advance, the Total Electron Content (TEC) at global scale. The technique is based on the Global Ionospheric Map (GIM), provided by the International GNSS Service (IGS), and exploits a nonlinear autoregressive neural network with external input (NARX) applied to selected TEC time series for soma particular GIM grid points (24 h single-point TEC forecasting), taking into account the actual and forecasted geomagnetic conditions. To extend the forecasting at a global scale, the technique leverages of the NeQuick2 Model fed by an effective sunspot number R12 (R12eff), calculated by minimizing the root mean square error (RMSE) between NARX output and NeQuick2 applied at the same GIM grid points. This new approach is able to reproduce the behavior of the ionosphere especially during disturbed periods.

Validation by using Final Global TEC product provided by the Universitat Politècnica de Catalunya (UPC) for the geomagnetic storm occurred 7–11 September 2017: (a) distribution of TEC difference (forecast-actual), statistical parameters are reported together with a red line indicating the mean; (c) map of the mean values of the TEC difference (forecast-actual); (b) time profile of the RGEC parameter (right y axis) and Dst (left y axis), the black dashed line indicates the zero reference value; (d) map of the standard deviation of the TEC difference (forecast-actual).

The performance of the forecasting model is extensively validated under different geospatial conditions, against both TEC maps products by UPC (Universitat Politècnica de Catalunya) and independent TEC data from Jason-3 spacecraft. The validation gives very satisfactory results in terms of RMSE, as it has been found to range between 3 and 5 TECu. RMSE depend on the latitude sectors, time of the day, geomagnetic conditions, and provide a statistical estimation of the accuracy of the 24-h forecasting technique even over the areas poorly covered by GNSS receivers (i.e. the oceans). The validation of the forecasting during five geomagnetic storms reveals that the model performance is not deteriorated during disturbed periods. This 24-h empirical approach is currently implemented on the Ionosphere Prediction Service (IPS), a prototype platform to support different classes of GNSS users in order to support the mitigation of the ionospheric effects on GNSS based technologies.

Publication: Cesaroni, C., Spogli, L., Aragon-Angel, A., Fiocca, M., Dear, V., De Franceschi, G., & Romano, V. (2020). Neural network based model for global Total Electron Content forecasting. Journal of Space Weather and Space Climate, 10, 11.
https://www.swsc-journal.org/articles/swsc/abs/2020/01/swsc190061/swsc190061.html

On the Analytical Description of the Topside Ionosphere by NeQuick: Modeling the Scale Height through COSMIC/FORMOSAT-3 Selected Data

Papers from SWICo members

Alessio Pignalberi, Michael Pezzopane, David R. Themens, Haris Haralambous, Bruno Nava, Pierdavide Coïsson

The topside part of the ionosphere extends from the F2-layer peak, corresponding to the ionospheric electron density maximum, to the plasmasphere. Developing a reliable model of the topside ionosphere is one of the most difficult tasks because instruments commonly used to probe the ionosphere, namely ionosondes, are only capable of sounding the region below the F2-layer peak. The topside ionosphere is characterized by a monotonic decrease of the electron density as the ion population smoothly transitions from the heavy O+ ions to the lighter H+ and He+ ions. This behavior is described by means of monotonically decreasing analytical functions dependent on a parameter called topside scale height whose exact description is the most challenging task for the topside ionosphere modeling.

In this paper, the analytical description of the topside ionosphere included in the NeQuick model is deeply analyzed. The NeQuick modeled scale height behavior is first studied at infinity and then for the lowest part of the topside region through an expansion in Taylor series near the F2-layer peak. The significant influence of the NeQuick topside parameters in the modeling of the topside profile is investigated in detail and, in particular, it is shown that for the lowest part of the topside the model assumes a linearly increasing trend of the topside scale height. Afterwards, the NeQuick topside formulation is inverted to derive a fully analytical expression of the topside scale height as a function of the electron density and F2-layer peak parameters. This expression has been applied to a selected and very reliable dataset of COSMIC/FORMOSAT-3 Radio Occultation profiles. The performed statistical analyses strongly support the supposed linear trend of the topside scale height for the lowest part of the topside ionosphere, as embedded in NeQuick; thus, the developed technique might be relevant for Space weather modeling purposes.

Publication: A. Pignalberi, M. Pezzopane, D. R. Themens, H. Haralambous, B. Nava and P. Coïsson, “On the Analytical Description of the Topside Ionosphere by NeQuick: Modeling the Scale Height Through COSMIC/FORMOSAT-3 Selected Data,” in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 13, pp. 1867-1878, 2020, doi: 10.1109/JSTARS.2020.2986683.
https://ieeexplore.ieee.org/document/9072529

The ionospheric irregularities climatology over Svalbard from solar cycle 23

Papers from SWICo members

Giorgiana De Franceschi, Luca Spogli, Lucilla Alfonsi, Vincenzo Romano, Claudio Cesaroni, Ingrid Hunstad

An unprecedented climatology of the ionospheric irregularities over the Svalbard (NO) derived from the longest Global Navigation Satellite Systems (GNSS) scintillation data series ever collected. Two receivers for scintillation monitoring are working at Ny-Ålesund, the first of which has been installed in late September 2003.

Climatological maps of occurrence of sigma_phi and S4 above the moderate to strong scintillation threshold. Maps are sorted according different level of Kp: quiet (left plots), minor/moderate G1-G2 (middle plots) and strong/severe/extreme G3-G4-G5 (right plots).

They are able to investigate auroral and cusp/cap regions and the length of the data series allows describing the Arctic ionosphere along about two solar cycles, from the descending phase of cycle 23 to almost the end of cycle 24. A detailed assessment of the long-term behaviour of the ionosphere under solar maximum and solar minimum conditions is provided including several periods of perturbed ionospheric weather caused by unfavourable heliogeophysical conditions. Since November 2015, a multi-constellation GNSS receiver has been deployed in Ny-Ålesund, providing the opportunity to perform the ionospheric climatology from Galileo signals. The results offer realistic features of the high latitude ionosphere, providing a broad spectrum of ionospheric reactions to different space weather conditions.

Publication: De Franceschi, G., Spogli, L., Alfonsi, L., Romano, V., Cesaroni, C., & Hunstad, I. (2019). The ionospheric irregularities climatology over Svalbard from solar cycle 23. Scientific reports, 9(1), 1-14.
https://www.nature.com/articles/s41598-019-44829-5

Role of the external drivers in the occurrence of low-latitude ionospheric scintillation revealed by multi-scale analysis

Papers from SWICo members

Luca Spogli, Mirko Piersanti, Claudio Cesaroni, Massimo Materassi, Antonio Cicone, Lucilla Alfonsi, Vincenzo Romano, and Rodolfo Gerardo Ezquer

By leveraging on the modal analysis provided by the Adaptive Local Iterative Filtering (ALIF) technique, this study focuses on the multi-scale variability of the amplitude scintillation on Global Navigation Satellite Systems (GNSSs) recorded over San Miguel de Tucumán (Argentina).

Relative energy of each intrinsic mode function as a function of the period (in days) calculated for (a) S4, (b) Equatorial Electrojet,(c) AL index, (d) AE index, (e) IMF-Bz, (f) IEF-Ex and (g) epsilon parameter. Red curves are for 1–15 March 2011, while green curves for the period 16–31 March 2011. Shaded colors (yellow, red, green) indicate three different intervals of periods: low periods (yellow), middle periods (red) and high periods (green). Black dashed box indicates the range of scales in which correspondence between S4 and epsilon parameter is found.

The site is nominally located below the expected position of the southern crest of the Equatorial Ionospheric Anomaly (EIA). The considered period is 1–31 March 2011, during which one minor and one moderate storm characterize the first half of the month, while generally quiet conditions of the geospace stand for the second half. The multiscale analysis is extended to helio-geophysical parameters to speculate on the possible relationship between forcing factors from the geospace and the ionospheric response. Resonant modes in the Akasofu (e) parameter are identified as likely related to the frequency components in the time evolution found for the amplitude scintillation index, hence modulating the scintillation itself. The analysis shows how the time-frequency structure of the amplitude scintillation can be characterized in terms of the resonant modes found in the combination of the Akasofu parameter. When assessed statistically, the proposed study can support models driven by interplanetary parameters aimed at characterizing the low latitude scintillation. The detection of resonant modes in the identified parameters can be used to define the Space Weather impact on GNSS signals recorded at ground.

Publication: Spogli, L., Piersanti, M., Cesaroni, C., Materassi, M., Cicone, A., Alfonsi, L., … & Ezquer, R. G. (2019). Role of the external drivers in the occurrence of low-latitude ionospheric scintillation revealed by multi-scale analysis. Journal of Space Weather and Space Climate9, A35
https://www.swsc-journal.org/articles/swsc/abs/2019/01/swsc180047/swsc180047.html