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We develop a climatological model for the Northern Hemisphere based on a long-term dataset (2010-2021) of the rate of change of the total electron content (TEC) index (ROTI) maps from the International GNSS Service (IGS). The IGS ROTI maps are daily averaged in magnetic latitude and local time coordinates. To develop a climatological model, the ROTI maps are decomposed into a few base functions and coefficients using the empirical orthogonal function (EOF) method. The EOF method converges very quickly, and the first four EOFs reflect the majority (96%) of the total data variability. Furthermore, different EOF components can reflect different drivers of ionospheric irregularities. The first EOF reflects the averaged ROTI activity and the impact of the solar radiation and geomagnetic activity; the 2nd EOF reflects the impact of the interplanetary magnetic field (IMF) Bz and electric field; the 3rd and 4th EOFs reflect the dawn-dusk asymmetry around the auroral oval and polar cap, and they can be related to the IMF By. To build an empirical model, we fit the EOF coefficients using helio-geophysical indices from four different categories (solar activity; geomagnetic indices; IMF; the solar wind coupling function). The final EOF model is dependent on seven selected indices (F10.7P, Kp, Dst, Bt, By, Bz and Ekl). The statistical data-model comparisons show satisfactory results with a good correlation coefficient. However, the model cannot capture the significant expansion of the dayside ROTI activity during strong geomagnetic storms. Future effort is needed to provide corrections to the model for severe storms.

International audience; A model forecasting ionospheric disturbances and its impact on GNSS positioning is proposed, called HAPEE (High lAtitude disturbances Positioning Error Estimator). It allows predicting ROTI index and corresponding Precise Point Positioning (PPP) error in Arctic region (i.e. latitudes > 50°). The model is forecasting for the next hour a probability of a disturbance index or PPP error to exceed a given threshold, from solar wind conditions measured at L1 Lagrange point. Or alternatively, it is forecasting a disturbance index level that is exceeded during the next hour for a given percentage of the time. The ROTI model has been derived from NMA network measurements, considering a database covering the years 2007 up to 2019. It is demonstrated that the statistical variability of the ROTI index is mainly following a lognormal distribution. The proposed model has been tested favorably on measurements performed using measurements from stations of the NMA network that were not used for the model derivation. It is also shown that the statistics of PPP error conditioned by ROTI is following a Laplace distribution. Then a new compound model has been proposed, based on a conditional probability combining ROTI distribution conditioned by solar wind conditions and error distributions conditioned by ROTI index level.

Interplanetary coronal mass ejections (ICMEs) compounded by high-speed plasma streams from coronal holes caused two intense geomagnetic storms on March 17–18, 2013 and 2015 during the current solar cycle. Ionospheric responses to the storms in the northern and southern hemispheres are compared in the context of solar wind coupling to the magnetosphere-ionosphere system. Phase scintillation is observed at high latitudes by arrays of high-rate GNSS Ionospheric Scintillation and TEC Monitors (GISTMs) and geodetic-quality GPS receivers sampling at 1 Hz. The high-rate GPS receivers are distributed in the northern and in the southern high latitudes with sparser coverage. In addition to GPS receivers, the high-latitude ionosphere dynamics is studied using arrays of ground-based instruments including HF radars, ionosondes, riometers, magnetometers, optical imagers as well as particle detectors and ultraviolet scanning imagers onboard the DMSP satellites.

The geomagnetic storm of 17–18 March 2015 was caused by the impacts of a coronal mass ejection and a high-speed plasma stream from a coronal hole. The high-latitude ionosphere dynamics is studied using arrays of ground-based instruments including GPS receivers, HF radars, ionosondes, riometers, and magnetometers. The phase scintillation index is computed for signals sampled at a rate of up to 100 Hz by specialized GPS scintillation receivers supplemented by the phase scintillation proxy index obtained from geodetic-quality GPS data sampled at 1 Hz. In the context of solar wind coupling to the magnetosphere-ionosphere system, it is shown that GPS phase scintillation is primarily enhanced in the cusp, the tongue of ionization that is broken into patches drawn into the polar cap from the dayside storm-enhanced plasma density, and in the auroral oval. In this paper we examine the relation between the scintillation and auroral electrojet currents observed by arrays of ground-based magnetometers as well as energetic particle precipitation observed by the DMSP satellites. Equivalent ionospheric currents are obtained from ground magnetometer data using the spherical elementary currents systems technique that has been applied over the ground magnetometer networks in North America and North Europe. The GPS phase scintillation is mapped to the poleward side of strong westward electrojet and to the edge of the eastward electrojet region. Also, the scintillation was generally collocated with fluxes of energetic electron precipitation observed by DMSP satellites with the exception of a period of pulsating aurora when only very weak currents were observed.

We present a comparative study of computational methods for estimation of ionospheric scintillation indices. First, we review the conventional approaches based on Fourier transformation and low-pass/high-pass frequency filtration. Next, we introduce a novel method based on nonparametric local regression with bias Corrected Akaike Information Criteria (AICC). All methods are then applied to data from the Norwegian Regional Ionospheric Scintillation Network (NRISN), which is shown to be dominated by phase scintillation and not amplitude scintillation. We find that all methods provide highly correlated results, demonstrating the validity of the new approach to this problem. All methods are shown to be very sensitive to filter characteristics and the averaging interval. Finally, we find that the new method is more robust to discontinuous phase observations than conventional methods. Copyright © 2016 Mohammed Ouassou et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Severe geomagnetic storms have a strong impact on space communication and satellite navigation systems. Forecasting the appearance of geomagnetically induced disturbances in the ionosphere is one of the urgent goals of the space weather community. The challenge is that the processes governing the distribution of the crucial ionospheric parameters have a rather poor quantitative description, and the models, built using the empirical parameterizations, have limited capabilities for operational purposes. On the other hand, data assimilation techniques are becoming more and more popular for nowcasting the state of the large-scale geophysical systems. We present an example of an ionospheric data assimilation system performance assessment during a strong geomagnetic event, which took place on 26 September 2011. The first-principle model has assimilated slant total electron content measurements from a dense network of ground stations, provided by the Norwegian Mapping Authority. The results have shown satisfactory agreement with independent data and demonstrate that the assimilation model is accurate to about 2–4 total electron content units and can be used for operational purposes in high-latitude regions. The operational system performance assessment is the subject of future work.

The Rate Of TEC Index (ROTI) is a commonly used measure of ionospheric activity. ROTI values have been computed every 5 min for the year 2012, for 10 receivers at latitudes from 59° to 79° North. We present the results in geomagnetic coordinates, showing that elevated ROTI values occur mainly in the cusp and nightside auroral oval regions. Elevated ROTI values are more common in the cusp, but in the nightside auroral oval they are stronger. To investigate the relation to positioning errors, receiver coordinates were computed using the GIPSY software, for the same receivers and time resolution. We found that there is a strong positive correlation between Precise Point Positioning (PPP) error and ROTI for receivers that are affected by space weather. The 3D position error increases exponentially with increasing ROTI. A statistical analysis presents also the risk of having several satellites observing enhanced ROTI values simultaneously, showing that this risk is greater at high latitudes.

The 2015 St. Patrick’s day storm was the first storm of solar cycle 24 to reach a level of “Severe” on the NOAA geomagnetic storm scale. The Norwegian Mapping Authority is operating a national real-time kinematic (RTK) positioning network and has in recent years developed software and services and deployed instrumentation to monitor space weather disturbances. Here, we report on our observations during this event. Strong GNSS (Global Navigation Satellite System) disturbances, measured by the rate-of-TEC index (ROTI), were observed at all latitudes in Norway on March 17th and early on March 18th. Late on the 18th, strong disturbances were only observed in northern parts of Norway. We study the ionospheric disturbances in relation to the auroral electrojet currents, showing that the most intense disturbances of GNSS signals occur on the poleward side of poleward-moving current regions. This indicates a possible connection to ionospheric polar cap plasma patches and/or particle precipitation caused by magnetic reconnection in the magnetosphere tail. We also study the impact of the disturbances on the network RTK and Precise Point Positioning (PPP) techniques. The vertical position errors increase rapidly with increasing ROTI for both techniques, but PPP is more precise than RTK at all disturbance levels.

The ROTI (Rate of TEC index) is a commonly used measure of ionospheric irregularities level. The algorithm to calculate ROTI is easily implemented, and is the same from paper to paper. However, the sample rate of the GNSS data used, and the time interval over which a value of ROTI is calculated, varies from paper to paper. When comparing ROTI values from different studies, this must be taken into account. This paper aims to show what these differences are, to increase the awareness of this issue. We have investigated the effect of different parameters for the calculation of ROTI values, using one year of data from 8 receivers at latitudes ranging from 59° N to 79° N. We have found that the ROTI values calculated using different parameter choices are strongly positively correlated. However, the ROTI values are quite different. The effect of a lower sample rate is to lower the ROTI value, due to the loss of high-frequency parts of the ROT spectrum, while the effect of a longer calculation time interval is to remove or reduce short-lived peaks due to the inherent smoothing effect. The ratio of ROTI values based on data of different sampling rate is examined in relation to the ROT power spectrum. Of relevance to statistical studies, we find that the median level of ROTI depends strongly on sample rate, strongly on latitude at auroral latitudes, and weakly on time interval. Thus, a baseline “quiet” or “noisy” level for one location or choice or parameters may not be valid for another location or choice of parameters.

The paper reviews the current state of GNSS-based detection, monitoring and forecasting of ionospheric perturbations in Europe in relation to the COST action ES0803 ‘‘Developing Space Weather Products and Services in Europe’’. Space weather research and related ionospheric studies require broad international collaboration in sharing databases, developing analysis software and models and providing services. Reviewed is the European GNSS data basis including ionospheric services providing derived data products such as the Total Electron Content (TEC) and radio scintillation indices. Fundamental ionospheric perturbation phenomena covering quite different scales in time and space are discussed in the light of recent achievements in GNSS-based ionospheric monitoring. Thus, large-scale perturbation processes characterized by moving ionization fronts, wave-like travelling ionospheric disturbances and finally small-scale irregularities causing radio scintillations are considered. Whereas ground and space-based GNSS monitoring techniques are well developed, forecasting of ionospheric perturbations needs much more work to become attractive for users who might be interested in condensed information on the perturbation degree of the ionosphere by robust indices. Finally, we have briefly presented a few samples illustrating the space weather impact on GNSS applications thus encouraging the scientific community to enhance space weather research in upcoming years.