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The ionosphere critically influences Global Navigation Satellite Systems (GNSS), satellite communications, and Low Earth Orbit (LEO) operations, yet accurate prediction of its variability remains challenging due to nonlinear couplings…
The ionosphere is a critical component of near-Earth space, shaping GNSS accuracy, high-frequency communications, and aviation operations. For these reasons, accurate forecasting and modeling of ionospheric variability has become…
The ionosphere electromagnetic activity is a major factor of the quality of satellite telecommunications, Global Navigation Satellite Systems (GNSS) and other vital space applications. Being able to forecast globally the Total Electron…
Many aspects of our societies now depend upon satellite telecommunications, such as those requiring Global Navigation Satellite Systems (GNSS). GNSS is based on radio waves that propagate through the ionosphere and experience complicated…
In this dissertation is provided a comparative analysis that evaluates the performance of several deep learning (DL) architectures on a large number of time series datasets of different nature and for different applications. Two main…
This paper introduces a high resolution, machine learning-ready heliophysics dataset derived from NASA's Solar Dynamics Observatory (SDO), specifically designed to advance machine learning (ML) applications in solar physics and space…
The weakly ionized plasma in the Earth's ionosphere is controlled by a complex interplay between solar and magnetospheric inputs from above, atmospheric processes from below, and plasma electrodynamics from within. This interaction results…
With the rise of electronic data, particularly Earth observation data, data-based geospatial modelling using machine learning (ML) has gained popularity in environmental research. Accurate geospatial predictions are vital for domain…
The development of regional services able to provide ionospheric vertical totalelectron content (VTEC) maps and ionospheric indexes with a high spatialresolution, and in near-real-time, are of great importance for both civilianapplications…
Subseasonal forecasting of the weather two to six weeks in advance is critical for resource allocation and advance disaster notice but poses many challenges for the forecasting community. At this forecast horizon, physics-based dynamical…
The ionosphere is a vitally dynamic charged particle region in the Earth's upper atmosphere, playing a crucial role in applications such as radio communication and satellite navigation. The Slant Total Electron Contents (STEC) is an…
Most data-driven ionospheric forecasting models operate on gridded products, which do not preserve the time-varying sampling structure of satellite-based sensing. We instead model the ionosphere as a dynamic graph over ionospheric pierce…
Precipitation plays a critical role in the Earth's hydrological cycle, directly affecting ecosystems, agriculture, and water resource management. Accurate precipitation estimation and prediction are crucial for understanding climate…
We present a Python tool to generate a standard dataset from solar images that allows for user-defined selection criteria and a range of pre-processing steps. Our Python tool works with all image products from both the Solar and…
Data-driven approaches, most prominently deep learning, have become powerful tools for prediction in many domains. A natural question to ask is whether data-driven methods could also be used to predict global weather patterns days in…
Solar and Heliosphere physics are areas of remarkable data-driven discoveries. Recent advances in high-cadence, high-resolution multiwavelength observations, growing amounts of data from realistic modeling, and operational needs for…
This paper presents the storm time comparative analysis of the performances of latest versions of global ionospheric models: International Reference Ionosphere (IRI) 2016, NeQuick 2 (NeQ) and the IRI extended to Plasmasphere (IRI-P) 2017…
Although vital for life on Earth, solar activity poses questions and increasing threats to humanity due to the Sun's unknown dynamics, intensified by our dependence on terrestrial and space-based infrastructure. This situation is compounded…
Geomagnetic storms drive complex ionospheric responses through coupled electrodynamic and thermospheric processes, yet attributing storm-time TEC perturbations to specific mechanisms remains challenging. We investigate the ionospheric…
The total ionospheric content (TEC) over the Iberian Peninsula was studied using data from two locations obtained both by GNSS receivers and an ionosonde. The principal component analysis applied to the TEC data allowed us to extract two…