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Inverse modeling has become one of the primary methods for studying ionospheric electrodynamics, especially when using magnetic field measurements from below the ionosphere. We present a method for quantifying the spatial resolution in an inverse model for non-uniformly sampled spatial data. This method provides a tool for assessing if a model can resolve the physical phenomena of interest. We quantify the spatial resolution for the Spherical Elementary Current System basis functions to model the ionospheric dynamics. Our results apply to models with spatially confined model parameters, unlike spherical harmonics where the model parameters describe the amplitude of global surface functions. The method is demonstrated for the upcoming Electrojet Zeeman Imaging Explorer cubesat mission which will provide spatially distributed remote sensing measurements of the magnetic field in the mesosphere. We show that, including measurements from a single ground magnetometer can significantly improve the spatial resolution. However, the impact of including a ground magnetometer depends on the relative position of the station with respect to the mesospheric measurements. In addition, a method for reducing two regularization parameters to one is presented. Reducing the amount of regularization parameters simplifies the optimization problem and facilitates a fair comparison between the models with and without a ground magnetometer.

A digital society is fragile and vulnerable to space-originated electromagnetic disturbances. Global geomagnetic conditions have been actively monitored since the invention of the magnetometer in 1833. However, regional changes in the magnetic environment have been widely left unstudied because of the sparsity of the observing networks. The Scandinavian Magnetometer Array (SMA) was the densest magnetometer network in history, and it was in operation in Fennoscandia during the International Magnetospheric Study (IMS) in 1976–1979. The data has been left mainly unstudied because it was recorded on 35 mm films, which are difficult to use for scientific studies. We used the DigiMAG digitization method to digitize magnetic data from all 32 SMA stations for a geomagnetic storm on 10–12 December 1977. Using these digitized values and modern magnetic data, we found large regional differences about up to 2 nT/km during strong geomagnetic storms (Dst 100–200 nT) and 7 nT/km for major scale Halloween geomagnetic storm, which correspond to 400 and 1400 nT difference for a typical 200 km station separation, respectively. The average size of substorms is 400 nT in the auroral zone. We conclude that the sparse magnetometer network can cause an underestimation of the regional magnetic disturbances and their effects. Misestimation of regional disturbances during extreme storms like the Carrington event may lead to insufficient planning of mitigation procedures and strategies.

The behaviour of the ionospheric and field-aligned currents (FACs) during geomagnetic storms are poorly understood, partly because the main focus of research concerning the ionospheric currents have been on time-scales of substorms and because geomagnetic storms exhibit large variations from one storm to another. To address this issue, this thesis studies the temporal and spatial development of ionospheric horizontal currents and FACs during 73 geomagnetic storms (Dstmin≤ −50 nT) from 2010 to 2017 driven by high-speed streams and associated stream interaction regions (HSS/SIRs), or sheaths and magnetic clouds (MC) associated with interplanetary coronal mass ejections (ICME). The development of the horizontal equivalent currents (Jeq) and FACs were studied using a superposed epoch analysis (SEA) of SuperMAG and AMPERE data, respectively. The zero epoch time, t0, was set to the main phase onset, defined as the time the SYM-H index in each storm crossed to less than −15 nT. Storms driven by HSS/SIR tend to begin during the dense SIR ahead of the HSS. Those storms have total FAC and Jeq that begins to slowly increase 3 hr before t0 and reach maximum at t0 + 40 min and t0 + 58 min, respectively, with total downward FAC of 8.1 MA. By separating the HSS/SIR storms into those with low and high solar wind dynamic pressure, pdyn, around t0, the total FAC, Jeq and number of substorm onsets are clearly higher for high pdyn compared to low pdyn storms for the first 6 hours after main phase onset. This situation reversed in the storm recovery phase, when after t0 + 2 days the currents and number of substorms for low pdyn storms decay slower and become larger than for high pdyn storms. This might be due to the higher solar wind velocity for low pdyn storms at this time. The ICME storms were separated into those driven by sheaths and MCs. Sheath-driven storms have shorter main phase durations and larger currents for the first 4 hr of the storm main phase than MC-driven s

Ion drag associated with the ionospheric plasma convection plays an important role in the high-latitude thermospheric dynamics, yet changes in the thermospheric wind with geomagnetic activity are not fully understood. We performed a statistical analysis of the thermospheric wind measurements with a Fabry–Perot interferometer (FPI; 630 nm wavelength) in Tromsø, Norway, in the winter months for 9 years. The measurements were sorted by a SuperMAG (SME) index, and a quiet-time wind pattern was defined as an hourly mean under SME ≤ 40 nT. The quiet-time wind pattern can be expected to be represented by a pressure gradient associated with the solar radiation and a geostrophic force balance. With an increase in the geomagnetic activity level, the thermospheric wind turned over from eastward to westward at dusk and increased the equatorward magnitude from midnight to dawn. Deviations from the quiet-time wind presented similar patterns in the direction with the ionospheric plasma convection but were larger in magnitude at dusk than at dawn. This is the first study to report a dawn-dusk asymmetry of the thermospheric wind acceleration feature and signatures of the eastward wind acceleration at dawn by ion drag.

The thermospheric wind response to a sudden westward turning of the ion velocity at a high latitude was studied by analyzing data obtained with a Fabry–Perot interferometer (FPI; 630 nm), Dynasonde, and Swarm A & C satellites during a conjunction event. The event occurred during a geomagnetically quiet period (Kp = 0 +) through the night, but some auroral activity occurred in the north. The collocated FPI and Dynasonde measured the thermospheric wind (U) and ionospheric plasma velocity (V), respectively, in the F region at the equatorward trough edge. A notable scientific message from this study is the possible role of thermospheric wind in the energy dissipation process at F-region altitude. The FPI thermospheric wind did not instantly follow a sudden V change due to thermospheric inertia in the F region. At a pseudo-breakup during the event, V suddenly changed direction from eastward to westward within 10 min. U was concurrently accelerated westward, but its development was more gradual than that of V, with U remaining eastward for a while after the pseudo-breakup. The delay of U is attributed to the thermospheric inertia. During this transition interval, U∙V was negative, which would result in more efficient generation of frictional heating than the positive U∙V case. The sign of U∙V, which is related to the relative directions of the neutral wind and plasma drift, is important because of its direct impact on ion-neutral energy exchange during collisions. This becomes especially important during substorm events, where rapid plasma velocity changes are common. The sign of U∙V may be used as an indicator to find the times and locations where thermospheric inertia plays a role in the energy dissipation process.

In the space physics community, processing and combining observational and modeling data from various sources is a demanding task because they often have different formats and use different coordinate systems. The Python package GeospaceLAB has been developed to provide a unified, standardized framework to process data. The package is composed of six core modules, including DataHub as the data manager, Visualization for generating publication quality figures, Express for higher-level interfaces of DataHub and Visualization, SpaceCoordinateSystem for coordinate system transformations, Toolbox for various utilities, and Configuration for preferences. The core modules form a standardized framework for downloading, storing, post-processing and visualizing data in space physics. The object-oriented design makes the core modules of GeospaceLAB easy to modify and extend. So far, GeospaceLAB can process more than twenty kinds of data products from nine databases, and the number will increase in the future. The data sources include, e.g., measurements by EISCAT incoherent scatter radars, DMSP, SWARM, and Grace satellites, OMNI solar wind data, and GITM simulations. In addition, the package provides an interface for the users to add their own data products. Hence, researchers can easily collect, combine, and view multiple kinds of data for their work using GeospaceLAB. Combining data from different sources will lead to a better understanding of the physics of the studied phenomena and may lead to new discoveries. GeospaceLAB is an open source software, which is hosted on GitHub. We welcome everyone in the community to contribute to its future development.

Radio waves provide a useful diagnostic tool to investigate the properties of the ionosphere because the ionosphere affects the transmission and properties of high frequency (HF) electromagnetic waves. We have conducted a transionospheric HF-propagation research campaign with a nanosatellite on a low-Earth polar orbit and the EISCAT HF transmitter facility in Tromsø, Norway, in December 2020. In the active measurement, the EISCAT HF facility transmitted sinusoidal 7.953 MHz signal which was received with the High frEquency rAdio spectRomEteR (HEARER) onboard 1 Unit (size: 10 × 10 × 10 cm) Suomi 100 space weather nanosatellite. Data analysis showed that the EISCAT HF signal was detected with the satellite’s radio spectrometer when the satellite was the closest to the heater along its orbit. Part of the observed variations seen in the signal was identified to be related to the heater’s antenna pattern and to the transmitted pulse shapes. Other observed variations can be related to the spatial and temporal variations of the ionosphere and its different responses to the used transmission frequencies and to the transmitted O- and X-wave modes. Some trends in the observed signal may also be associated to changes in the properties of ionospheric plasma resulting from the heater’s electromagnetic wave energy. This paper is, to authors’ best knowledge, the first observation of this kind of “self-absorption” measured from the transionospheric signal path from a powerful radio source on the ground to the satellite-borne receiver.

The work presented in this thesis studies the high-latitude ionospheric current systems in the North Hemisphere (NH) and South Hemisphere (SH). The main objective has been to statistically investigate the effect of geomagnetic activity, season and IMF directions on the currents, giving special emphasis on hemispheric asymmetry. The thesis makes use of magnetic field data measured by the European Space Agency (ESA) Swarm-A and -C satellites from both hemispheres. Based on the magnetic data, ionospheric currents have been estimated using the spherical elementary current system (SECS) method. The bootstrap statistical method was used to normalize the data from the two hemispheres as far as possible. The detailed results are as follows. On average, the currents are larger in the NH than in the SH. Hemispheric asymmetry in the high-latitude ionospheric currents is larger during low geomagnetic activity (Kp < 2) than high geomagnetic activity (Kp ≥ 2), with NH/SH field-aligned current (FAC) ratio of 1.12 and 1.02. Asymmetry is also larger during local winter and autumn than local summer and spring, with stronger currents in the NH than in the SH. The role of background ionospheric conductances on the hemispheric asymmetry in currents was studied. However, it does not show similar hemispheric asymmetry as the high-latitude ionospheric currents, indicating that solar illumination difference does not seem to be the reason for the asymmetry. It was also found that the ionospheric conductivity calculation using the IRI and MSISE models did not show the auroral oval, so the role of auroral precipitation could not be determined. When making the statistical analysis for different IMF directions, it was found that the orientation of IMF has strong influence on the hemispheric asymmetry in the high-latitude currents, but this influence depends on local season. Hemispheric asymmetry in the high-latitude currents is larger for IMF By⁺ in NH (By⁻ in SH) than vice versa dur, Notice Printed version has incorrect ISBN: ISBN (PDF) 978-952-62-3047-1 it should be 978-952-62-3048-1., Huomautus Painetussa virheellinen ISBN-tunnus: ISBN (PDF) 978-952-62-3047-1 pitäisi olla 978-952-62-3048-1.

The technique of spherical elementary current systems (SECS) is a powerful way to determine ionospheric and field-aligned currents (FAC) from magnetic field measurements made by low-Earth-orbiting satellites, possibly in combination with magnetometer arrays on the ground. The SECS method consists of two sets of basis functions for the ionospheric currents: divergence-free (DF) and curl-free (CF) components, which produce poloidal and toroidal magnetic fields, respectively. The original CF SECS are only applicable at high latitudes, as they build on the assumption that the FAC flow radially into or out of the ionosphere. The FAC at low and middle latitudes are far from radial, which renders the method inapplicable at these latitudes. In this study, we modify the original CF SECS by including FAC that flow along dipolar field lines. This allows the method to be applied at all latitudes. We name this method dipolar elementary current systems (DECS). Application of the DECS to synthetic data, as well as Swarm satellite measurements are carried out, demonstrating the good performance of this method, and its applicability to studies of ionospheric current systems at low and middle latitudes.

Geomagnetically induced currents (GICs) are directly described by ground electric fields, but estimating them is time-consuming and requires knowledge of the ionospheric currents and the three-dimensional (3D) distribution of the electrical conductivity of the Earth. The time derivative of the horizontal component of the ground magnetic field (dH∕dt) is closely related to the electric field via Faraday‘s law and provides a convenient proxy for the GIC risk. However, forecasting dH∕dt still remains a challenge. We use 25 years of 10 s data from the northern European International Monitor for Auroral Geomagnetic Effects (IMAGE) magnetometer network to show that part of this problem stems from the fact that, instead of the primary ionospheric currents, the measured dH∕dt is dominated by the signature from the secondary induced telluric currents at nearly all IMAGE stations. The largest effects due to telluric currents occur at coastal sites close to high-conducting ocean water and close to near-surface conductivity anomalies. The secondary magnetic field contribution to the total field is a few tens of percent, in accordance with earlier studies. Our results have been derived using IMAGE data and are thus only valid for the stations involved. However, it is likely that the main principle also applies to other areas. Consequently, it is recommended that the field separation into internal (telluric) and external (ionospheric and magnetospheric) parts is performed whenever feasible (i.e., a dense observation network is available).

We propose stochastic processes to be used to model the total electron content (TEC) observation. Based on this, we model the rate of change of TEC (ROT) variation during ionospheric quiet conditions with stationary processes. During ionospheric disturbed conditions, for example, when irregularity in ionospheric electron density distribution occurs, stationarity assumption over long time periods is no longer valid. In these cases, we make the parameter estimation for short time scales, during which we can assume stationarity. We show the relationship between the new method and commonly used TEC characterization parameters ROT and the ROT Index (ROTI). We construct our parametric model within the framework of Bayesian statistical inverse problems and hence give the solution as an a posteriori probability distribution. Bayesian framework allows us to model measurement errors systematically. Similarly, we mitigate variation of TEC due to factors which are not of ionospheric origin, like due to the motion of satellites relative to the receiver, by incorporating a priori knowledge in the Bayesian model. In practical computations, we draw the so-called maximum a posteriori estimates, which are our ROT and ROTI estimates, from the posterior distribution. Because the algorithm allows to estimate ROTI at each observation time, the estimator does not depend on the period of time for ROTI computation. We verify the method by analyzing TEC data recorded by GPS receiver located in Ethiopia (11.6∘N, 37.4∘E). The results indicate that the TEC fluctuations caused by the ionospheric irregularity can be effectively detected and quantified from the estimated ROT and ROTI values.