Global Navigation Satellite Systems (GNSS) are subject to disturbances caused by plasma irregularities in the ionosphere. Studies have suggested that in addition to the gradient drift and Kelvin‐Helmholtz instabilities, electron precipitation may be important for phase scintillations in the dayside auroral region. This study combines in situ Swarm data with ground GNSS observations to investigate the potential role of filamentary field‐aligned currents (FACs) on phase scintillations in the dayside auroral region by analyzing 22 events with phase scintillations exceeding 0.45 radians. We observe colocation between regions of severe phase scintillations and highly filamented FACs with fluctuations measured in the spacecraft frame of the order of 20 Hz. The observations indicate that filamentary FACs are crucial drivers for irregularities responsible for creating severe phase scintillations measured in the dayside auroral region and are thus of significant importance in the context of space weather impact on satellite communication.

Space weather phenomena such as scintillations of Global Navigation Satellite Systems (GNSS) signals are of increasing importance for aviation, the maritime, and civil engineering industries. The ionospheric plasma irregularities causing scintillations are associated with strong gradients in ionospheric plasma density. To provide nowcasts and forecasts of space weather effects, it is vital to monitor the ionosphere and detect strong density variations. To reconstruct plasma density variations in the polar cap ionosphere, we use total electron content (TEC) estimates from the Swarm satellites' GPS receivers. By considering events where the Swarm satellites are in close proximity, we obtain plasma density variations by inverting TEC measurements on a two-dimensional grid. We first demonstrate the method using synthetic test data, before applying it to real data. The method is validated using in situ Langmuir probe measurements and ground-based TEC observations. We find that the new method can reproduce density variations, although it is sensitive to the geometry of the Swarm satellite constellation and to the calculated plasma temperature. Our proposed method opens new possibilities for ionospheric plasma monitoring that uses GPS receivers aboard low Earth orbit (LEO) satellites.

The Norwegian Mapping Authority operates a network real time kinematic (RTK) system called CPOS, a positioning service providing centimeter level accuracy aimed at commercial users, for example, in civil engineering, excavation, and surveying. CPOS is based on multiple Global Navigation Satellite Systems (multi‐GNSS) in addition to base stations to provide correction data. CPOS position accuracy is subject to disturbances arising from space weather phenomena, which can disturb and disrupt GNSS signals. Studies have shown that CPOS performance is sensitive to the presence of plasma irregularities, usually quantified by the rate of change of total electron content index (ROTI). This study investigates the performance of CPOS over a 3‐year period, and its relationship with ionospheric irregularities. In a statistical analysis, we observe that CPOS position errors have seasonal, diurnal, and latitudinal variations. The most frequent position errors occur around magnetic noon and are of moderate severity, while the largest position errors occur around night‐time, agreeing well with climatology studies on GNSS scintillations. Additionally, we investigate ionospheric irregularities as characterized by the rate of TEC index (ROTI). We find that there is a significant correlation between CPOS accuracy and ROTI, but that there are also other contributing factors.

Space weather can cause serious disturbances of global navigation satellite systems (GNSS) used for positioning and navigation purposes. This paper describes a new method to forecast space weather disturbances on GNSS at high latitudes, in which we describe the formation and propagation of polar cap patches and predict their arrival at the nightside auroral oval. The space weather prediction model builds on the expanding/contracting polar cap (ECPC) paradigm and total electron content (TEC) observations from the Global Positioning System (GPS) network. The input parameter is satellite observations of the interplanetary magnetic field at the first Lagrange point. To validate our prediction model, we perform a case study in which we compare the results from our prediction model to observations from the GPS TEC data from the MIT's Madrigal database, convection data from Super Dual Auroral radar network, and scintillation data from Svalbard. Our results show that the ECPC paradigm describes the polar cap patch motion well and can be used to predict scintillations of GPS signals at high latitudes.

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