Spatial statistics and analysis of earth's ionosphere

Thesis (Ph.D.)--Boston UniversityThe ionosphere, a layer of Earths upper atmosphere characterized by energetic charged particles, serves as a natural plasma laboratory and supplies proxy diagnostics of space weather drivers in the magnetosphere and the solar wind. The ionosphere is a highly dynamic medium, and the spatial structure of observed features (such as auroral light emissions, charge density, temperature, etc.) is rich with information when analyzed in the context of fluid, electromagnetic, and chemical models. Obtaining measurements with higher spatial and temporal resolution is clearly advantageous. For instance, measurements obtained with a new electronically-steerable incoherent scatter radar (ISR) present a unique space-time perspective compared to those of a dish-based ISR. However, there are unique ambiguities for this modality which must be carefully considered. The ISR target is stochastic, and the fidelity of fitted parameters (ionospheric densities and temperatures) requires integrated sampling, creating a tradeoff between measurement uncertainty and spatio-temporal resolution. Spatial statistics formalizes the relationship between spatially dispersed observations and the underlying process(es) they represent. A spatial process is regarded as a random field with its distribution structured (e.g., through a correlation function) such that data, sampled over a spatial domain, support inference or prediction of the process. Quantification of uncertainty, an important component of scientific data analysis, is a core value of spatial statistics. This research applies the formalism of spatial statistics to the analysis of Earth's ionosphere using remote sensing diagnostics. In the first part, we consider the problem of volumetric imaging using phased-array ISR based on optimal spatial prediction ("kriging"). In the second part, we develop a technique for reconstructing two-dimensional ion flow fields from line-of-sight projections using Tikhonov regularization. In the third part, we adapt our spatial statistical approach to global ionospheric imaging using total electron content (TEC) measurements derived from navigation satellite signals

Studies of the Ionosphere-Thermosphere Responses to Multi-Scale Energy Deposition Processes

The Ionosphere-Thermosphere (I-T) system is greatly affected by the magnetospheric energy deposition from above and subjected to forcing from the lower atmosphere simultaneously. A central problem in studying the coupled I-T system is to analyze the multi-scale processes naturally embedded in both ways. Magnetospheric energy input such as auroral precipitation and electric field demonstrates multi-scale structures during magnetic storms, resulting in multi-scale I-T responses when deposited into the I-T system. To better quantify the multi-scale aurora and electric field, we developed a new data assimilation model based on a multi-resolution Gaussian process model to synthesize empirical models and observational data from various sources and provide estimates in regions without observations. The new method mitigates the discrepancy between empirical models and observations by successfully capturing the dynamic evolutions of large-scale and mesoscale auroral and electric field structures. By further incorporating the assimilated aurora and electric fields into Thermosphere Ionosphere Electrodynamics General Circulation Model (TIEGCM) during the 2015 St. Patrick\u27s Day storm, we significantly elevate Joule heating and largely reproduce the global and local I-T responses as observed, including the enhanced electron density and vertical wind. Data assimilation also helps introduce more spatial and temporal variabilities in TIEGCM, which propagate to low-latitude regions through Traveling Atmospheric Disturbance (TAD). In the other direction, to study the atmospheric wave forcing from below and how it impacts the I-T system, we develop a nested-grid extension to TIEGCM to study the Gravity Wave (GW) propagation process and its ionospheric effect during the 2022 Tonga volcano eruption. Such a hybrid-grid design helps to better simulate the variations of a smaller scale than the standard model resolution while reducing computation costs at the same time. With proper seeding at the lower boundary, GW propagation in the thermosphere is successfully reproduced. The resulting Traveling Ionospheric Disturbance (TID) in the ionosphere has a similar speed to observations. The wave spectrum at different altitudes also indicates that the dominant GW has a shorter period and horizontal wavelength at higher altitudes. This dissertation discusses the detailed tool development, including data assimilation and TIEGCM-NG, which enables a better understanding of the influences of multi-scale magnetospheric forcing and lower-atmosphere wave forcing on the I-T system. This work provides a powerful set of tools for a better simulation of space weather

Simultaneous multiplicative column normalized method (SMART) for the 3D ionosphere tomography in comparison with other algebraic methods

The accuracy and availability of satellite-based applications like GNSS positioning and remote sensing crucially depends on the knowledge of the ionospheric electron density distribution. The tomography of the ionosphere is one of the major tools to provide link specific ionospheric corrections as well as to study and monitor physical processes in the ionosphere. In this paper, we introduce a simultaneous multiplicative column-normalized method (SMART) for electron density reconstruction. Further, SMART+ is developed by combining SMART with a successive correction method. In this way, a balancing between the measurements of intersected and not intersected voxels is realised. The methods are compared with the well-known algebraic reconstruction techniques ART and SART. All the four methods are applied to reconstruct the 3-D electron density distribution by ingestion of ground-based GNSS TEC data into the NeQuick model. The comparative case study is implemented over Europe during two periods of the year 2011 covering quiet to disturbed ionospheric conditions. In particular, the performance of the methods is compared in terms of the convergence behaviour and the capability to reproduce sTEC and electron density profiles. For this purpose, independent sTEC data of four IGS stations and electron density profiles of four ionosonde stations are taken as reference. The results indicate that SMART significantly reduces the number of iterations necessary to achieve a predefined accuracy level. Further, SMART+ decreases the median of the absolute sTEC error up to 15, 22, 46 and 67% compared to SMART, SART, ART and NeQuick respectively

Spatial Resolution in Inverse Problems: The EZIE Satellite Mission

Under embargo until: 2023-11-16Inverse 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.publishedVersio

GNSS-based global ionospheric maps : real-time combination, time resolution and applications on space weather monitoring

Tesi amb una secció retallada per drets d'editor.The research of this paper-based dissertation is focused on the Global Ionospheric Maps (GIMs) based on Global Navigation Satellite System (GNSS) including real-time combination, validation, time resolution and applications. The novelty of these works can be summarized as follows: The first contribution is to connect GIM assessment methods in post-processing and real-time mode including Jason-altimeter Vertical Total Electron Content (VTEC) assessment, GNSS differences of Slant Total Electron Content (dSTEC) assessment and real-time dSTEC (RT-dSTEC) assessment. With the RT-dSTEC assessment, we can assess the accuracy and calculate the weight of different real-time GIMs for combination in real-time mode. The Jason-altimeter VTEC assessment and dSTEC assessment can be used for evaluating GIMs over oceans and continental regions, respectively. In addition, the accurate GIMs shown in the GIM assessment methods can be regarded as reliable representations of global VTEC. The second contribution is to apply the RT-dSTEC assessment in real-time mode for the combination of different International GNSS Service (IGS) real-time GIMs. The IGS combined real-time GIM is generated to provide robust ionospheric corrections for real-time GNSS positioning and reliable global VTEC distribution for earth observations. The current status of IGS real-time GIMs from different centers is summarized and compared. The Jason-altimeter VTEC assessment and dSTEC assessment in post-processing mode are used for the validation of IGS real-time GIMs. The sensibility of real-time weighting technique by RT-dSTEC assessment is also verified. The third contribution is to investigate the influence of temporal resolution on the performance of GIMs. The variation of ionosphere is typically assumed as linear between two consecutive GIM TEC maps in a sun-fixed reference frame for up to few hours. However, the variation of ionospheric TEC is irregular due to the occurrence of space weather events. One and a half solar cycle of the IGS GIM with higher time resolution and accuracy (the UPC-IonSAT Quarter-of-an-hour time resolution Rapid GIM, UQRG) has been taken as a baseline to downsample them to all possible sub-daily temporal resolutions. The performance of the resulting GIMs has been evaluated taking into account the geographical position, solar and geomagnetic activity by Jason-altimeter VTEC assessment and dSTEC assessment. The fourth contribution is to propose a new way of estimating the spatial and temporal components of the VTEC gradient. The determination of ionospheric perturbation degrees can be helpful for guaranteeing the safety level of Satellite-Based Augmentation System (SBAS) and Ground-Based Augmentation System (GBAS) services. In order to estimate the spatial and temporal components of the VTEC gradient on a global scale, the accurate UQRG is selected. The VTEC gradient indices derived from UQRG GIMs (VgUG) allow users to obtain full (non-relative) values of TEC spatial gradients and temporal variations separately. The Regional VTEC spatial Gradient indices, based on UQRG (RVGU) and the Regional Ionospheric Disturbance index based on UQRG (RIDU), are proposed to estimate the regional ionospheric perturbation degree over selected regions. In addition, the spatial and temporal components of VTEC gradient at grid points of UQRG on a global scale are also introduced. The fifth contribution is to define a new ionospheric storm scale. The ionospheric response to high geomagnetic activity, ionospheric storm, can enlarge GNSS positioning errors by the increase of ionospheric electron density and disable high-frequency communications by the decrease of ionospheric electron density. To characterize the ionospheric state on a global scale, reliable global VTEC distribution is essential. According to previous studies, UQRG is one of the most accurate GIM. In this regard, the new Ionospheric storm Scale based on UQRG, IsUG, is proposed.La investigación de esta tesis doctoral se centra en los Mapas Ionosféricos Globales (GIMs) basados en el Sistema Global de Navegación por Satélite (GNSS), incluyendo la combinación en tiempo real, la validación, la resolución temporal y su aplicación. La novedad de los trabajos presentados puede resumirse como sigue: La primera contribución consiste en conectar los métodos de evaluación de los GIM en modo de posprocesamiento y en tiempo real, incluyendo la evaluación VTEC gracias a las medidas de los altímetros Jason, la evaluación del contenido total de electrones diferencial (dSTEC) y la evaluación dSTEC en tiempo real (RT-dSTEC). Con la evaluación RT-dSTEC, podemos evaluar la precisión y calcular el peso de diferentes GIM en tiempo real para su combinación también en tiempo real. La evaluación VTEC del altímetro Jason y la evaluación dSTEC pueden utilizarse para evaluar los GIM sobre los océanos y las regiones continentales, respectivamente. Además, los GIM precisos mostrados en los métodos de evaluación de GIM pueden considerarse como representaciones fiables del contenido total de electrones vertical global (VTEC). La segunda contribución consiste en aplicar la evaluación RT-dSTEC en tiempo real para la combinación de diferentes GIM del Servicio Internacional GNSS (IGS), todo ello en tiempo real. El GIM IGS combinado resultante proporciona correcciones ionosféricas robustas para el posicionamiento GNSS en tiempo real y una distribución global de VTEC fiable para las observaciones terrestres. Se resume y compara el estado actual de los GIM en tiempo real de diferentes centros IGS. La evaluación de VTEC respecto de los altímetros Jason y la evaluación de dSTEC en modo de posprocesamiento también se utilizan para la validación de los GIM en tiempo real del IGS. Y se verifica la sensibilidad de la técnica de ponderación en tiempo real mediante la evaluación RT-dSTEC. La tercera contribución consiste en proponer una nueva forma de estimar las componentes espaciales y temporales del gradiente VTEC. La determinación de los grados de perturbación ionosférica puede ser útil para garantizar el nivel de seguridad de los servicios del Sistema de Aumento Basado en Satélites (SBAS) y del Sistema de Aumento Basado en Tierra (GBAS). Para estimar los componentes espaciales y temporales del gradiente de VTEC a escala global, se selecciona el GIM UQRG debido a su exactitud y resolución temporal. Los índices de gradiente VTEC derivados de los GIM de UQRG (VgUG) permiten a los usuarios obtener valores completos (no relativos) de gradientes espaciales de VTEC y de las variaciones temporales por separado. Los índices de gradiente espacial VTEC regional, basados en UQRG (RVGU) y el índice de perturbación ionosférica regional basado en UQRG (RIDU), se proponen para estimar el grado de perturbación ionosférica regional sobre zonas de interés. Además también se introducen los componentes espaciales y temporales del gradiente VTEC en los puntos de la cuadrícula con valores proporcionados por UQRG a escala global. La cuarta contribución consiste en definir una nueva escala de tormentas ionosféricas. La respuesta ionosférica a la alta actividad geomagnética, la tormenta ionosférica, puede aumentar los errores de posicionamiento del GNSS por el aumento de la densidad de electrones ionosféricos e inhabilitar las comunicaciones de alta frecuencia por la disminución y en general rápida variación de la densidad de electrones ionosféricos. Para caracterizar el estado de la ionosfera a escala global, es esencial contar con una distribución global fiable de VTEC. Según estudios anteriores, el UQRG es uno de los GIM más precisos. En este sentido se propone la nueva Escala de tormentas ionosféricas basada en UQRG, IsUG.Postprint (published version

A-CHAIM: Near-Real-Time Data Assimilation of the High Latitude Ionosphere With a Particle Filter

The Assimilative Canadian High Arctic Ionospheric Model (A-CHAIM) is an operational ionospheric data assimilation model that provides a 3D representation of the high latitude ionosphere in Near-Real-Time (NRT). A-CHAIM uses low-latency observations of slant Total Electron Content (sTEC) from ground-based Global Navigation Satellite System (GNSS) receivers, ionosondes, and vertical TEC from the JASON-3 altimeter satellite to produce an updated electron density model above 45° geomagnetic latitude. A-CHAIM is the first operational use of a particle filter data assimilation for space environment modeling, to account for the nonlinear nature of sTEC observations. The large number (>104 ) of simultaneous observations creates significant problems with particle weight degeneracy, which is addressed by combining measurements to form new composite observables. The performance of A-CHAIM is assessed by comparing the model outputs to unassimilated ionosonde observations, as well as to in-situ electron density observations from the SWARM and DMSP satellites. During moderately disturbed conditions from 21 September 2021 through 29 September 2021, A-CHAIM demonstrates a 40%–50% reduction in error relative to the background model in the F2-layer critical frequency (foF2) at midlatitude and auroral reference stations, and little change at higher latitudes. The height of the F2-layer (hmF2) shows a small 5%–15% improvement at all latitudes. In the topside, A-CHAIM demonstrates a 15%–20% reduction in error for the Swarm satellites, and a 23%–28% reduction in error for the DMSP satellites. The reduction in error is distributed evenly over the assimilation region, including in data-sparse regions

Constructing water vapor maps by fusing InSAR, GNSS and WRF data

The work aims at constructing maps of the total water vapor in the atmosphere by fusing InSAR, GNSS, and WRF data

A three-dimensional regional assimilative model of the ionospheric electron density

The focus of this thesis is on the development, implementation, and validation of a three-dimensional regional assimilative model of the ionospheric electron density. Empirical climatological models, like the International Reference Ionosphere (IRI) model (Bilitza et al. 2017), cannot predict the whole ionospheric variability, specifically under disturbed magnetic conditions. The model presented in this work has the purpose to improve the IRI description by implementing a data assimilation procedure, based on ionospheric measurements collected by several ground-based or satellite-based instruments. The first phase of the development of the model, called IRI UPdate (IRI UP), is devoted to update the IRI model by ingesting effective indices (IG12eff and R12eff) calculated after assimilating F2 layer characteristics values, measured by a network of ionosondes or derived by vertical total electron content values measured by a network of Global Navigational Satellite Systems receivers. The ingestion of effective indices in the IRI model allows to significantly improve the F2 layer peak density and height description. Being the F2 layer peak an anchor point for the whole IRI’s vertical electron density profile, such procedure allows to update the whole profile. The second phase of the development of the model is devoted to improve the modeling of the topside part of the ionospheric vertical electron density profile by making use of the IRI UP method and in-situ measurements collected by Swarm satellites. Finally, a procedure called IonoPy, embedding the two aforementioned steps, assimilates the whole bottomside electron density profile measured by an ionosonde, thus further improving the ionospheric plasma description in the bottomside ionosphere. All the procedures described in this thesis have been tested and validated by comparing them with other similar models or with independent datasets, for both quiet and disturbed conditions

Robust and Flexible Persistent Scatterer Interferometry for Long-Term and Large-Scale Displacement Monitoring

Die Persistent Scatterer Interferometrie (PSI) ist eine Methode zur Überwachung von Verschiebungen der Erdoberfläche aus dem Weltraum. Sie basiert auf der Identifizierung und Analyse von stabilen Punktstreuern (sog. Persistent Scatterer, PS) durch die Anwendung von Ansätzen der Zeitreihenanalyse auf Stapel von SAR-Interferogrammen. PS Punkte dominieren die Rückstreuung der Auflösungszellen, in denen sie sich befinden, und werden durch geringfügige Dekorrelation charakterisiert. Verschiebungen solcher PS Punkte können mit einer potenziellen Submillimetergenauigkeit überwacht werden, wenn Störquellen effektiv minimiert werden. Im Laufe der Zeit hat sich die PSI in bestimmten Anwendungen zu einer operationellen Technologie entwickelt. Es gibt jedoch immer noch herausfordernde Anwendungen für die Methode. Physische Veränderungen der Landoberfläche und Änderungen in der Aufnahmegeometrie können dazu führen, dass PS Punkte im Laufe der Zeit erscheinen oder verschwinden. Die Anzahl der kontinuierlich kohärenten PS Punkte nimmt mit zunehmender Länge der Zeitreihen ab, während die Anzahl der TPS Punkte zunimmt, die nur während eines oder mehrerer getrennter Segmente der analysierten Zeitreihe kohärent sind. Daher ist es wünschenswert, die Analyse solcher TPS Punkte in die PSI zu integrieren, um ein flexibles PSI-System zu entwickeln, das in der Lage ist mit dynamischen Veränderungen der Landoberfläche umzugehen und somit ein kontinuierliches Verschiebungsmonitoring ermöglicht. Eine weitere Herausforderung der PSI besteht darin, großflächiges Monitoring in Regionen mit komplexen atmosphärischen Bedingungen durchzuführen. Letztere führen zu hoher Unsicherheit in den Verschiebungszeitreihen bei großen Abständen zur räumlichen Referenz. Diese Arbeit befasst sich mit Modifikationen und Erweiterungen, die auf der Grund lage eines bestehenden PSI-Algorithmus realisiert wurden, um einen robusten und flexiblen PSI-Ansatz zu entwickeln, der mit den oben genannten Herausforderungen umgehen kann. Als erster Hauptbeitrag wird eine Methode präsentiert, die TPS Punkte vollständig in die PSI integriert. In Evaluierungsstudien mit echten SAR Daten wird gezeigt, dass die Integration von TPS Punkten tatsächlich die Bewältigung dynamischer Veränderungen der Landoberfläche ermöglicht und mit zunehmender Zeitreihenlänge zunehmende Relevanz für PSI-basierte Beobachtungsnetzwerke hat. Der zweite Hauptbeitrag ist die Vorstellung einer Methode zur kovarianzbasierten Referenzintegration in großflächige PSI-Anwendungen zur Schätzung von räumlich korreliertem Rauschen. Die Methode basiert auf der Abtastung des Rauschens an Referenzpixeln mit bekannten Verschiebungszeitreihen und anschließender Interpolation auf die restlichen PS Pixel unter Berücksichtigung der räumlichen Statistik des Rauschens. Es wird in einer Simulationsstudie sowie einer Studie mit realen Daten gezeigt, dass die Methode überlegene Leistung im Vergleich zu alternativen Methoden zur Reduktion von räumlich korreliertem Rauschen in Interferogrammen mittels Referenzintegration zeigt. Die entwickelte PSI-Methode wird schließlich zur Untersuchung von Landsenkung im Vietnamesischen Teil des Mekong Deltas eingesetzt, das seit einigen Jahrzehnten von Landsenkung und verschiedenen anderen Umweltproblemen betroffen ist. Die geschätzten Landsenkungsraten zeigen eine hohe Variabilität auf kurzen sowie großen räumlichen Skalen. Die höchsten Senkungsraten von bis zu 6 cm pro Jahr treten hauptsächlich in städtischen Gebieten auf. Es kann gezeigt werden, dass der größte Teil der Landsenkung ihren Ursprung im oberflächennahen Untergrund hat. Die präsentierte Methode zur Reduzierung von räumlich korreliertem Rauschen verbessert die Ergebnisse signifikant, wenn eine angemessene räumliche Verteilung von Referenzgebieten verfügbar ist. In diesem Fall wird das Rauschen effektiv reduziert und unabhängige Ergebnisse von zwei Interferogrammstapeln, die aus unterschiedlichen Orbits aufgenommen wurden, zeigen große Übereinstimmung. Die Integration von TPS Punkten führt für die analysierte Zeitreihe von sechs Jahren zu einer deutlich größeren Anzahl an identifizierten TPS als PS Punkten im gesamten Untersuchungsgebiet und verbessert damit das Beobachtungsnetzwerk erheblich. Ein spezieller Anwendungsfall der TPS Integration wird vorgestellt, der auf der Clusterung von TPS Punkten basiert, die innerhalb der analysierten Zeitreihe erschienen, um neue Konstruktionen systematisch zu identifizieren und ihre anfängliche Bewegungszeitreihen zu analysieren