Related papers: Ionospheric activity prediction using convolutiona…
Radio interferometers, which are designed to observe astrophysical objects in the universe, can also be used to study the Earth's ionosphere. Radio interferometers like the Giant Metrewave Radio Telescope (GMRT) detect variations in…
Deep learning-based models have recently outperformed state-of-the-art seasonal forecasting models, such as for predicting El Ni\~no-Southern Oscillation (ENSO). However, current deep learning models are based on convolutional neural…
In this report we analyze the feasibility of ionospheric monitoring using GNSS technology. The focus will be on the use of LEO GNSS data, exploiting GNSS Reflections, Navigation and Occultation TEC measurements. In order to attack this…
Tsunamis can trigger internal gravity waves (IGWs) in the ionosphere, perturbing the Total Electron Content (TEC) - referred to as Traveling Ionospheric Disturbances (TIDs) that are detectable through the Global Navigation Satellite System…
We present a statistical framework for estimating global navigation satellite system (GNSS) non-ionospheric differential time delay bias. The biases are estimated by examining differences of measured line integrated electron densities (TEC)…
Message-passing neural networks (MPNN) have shown extremely high efficiency and accuracy in predicting the physical properties of molecules and crystals, and are expected to become the next-generation material simulation tool after the…
On April 15, 2016, the Kumamoto earthquake (Mw 7.3) occurred in Japan with no warning signals. Global Navigation Satellite System (GNSS) receivers provide useful information on disturbances in ionosphere by calculating the changes in Total…
This study investigates the impact of the G5 geomagnetic storm on Total Electron Content (TEC) derived from the Global Positioning System (GPS) in Gal\'apagos, Ecuador (geographic latitude 0.1807{\deg} S, longitude 78.4678{\deg} W) during…
We present a significantly-improved data-driven global weather forecasting framework using a deep convolutional neural network (CNN) to forecast several basic atmospheric variables on a global grid. New developments in this framework…
In this paper an attempt is made to verify the hypothesis on the role of geomagnetic disturbances as a factor determining the intensity of traveling ionospheric disturbances (TIDs). To improve the statistical validity of the data, we have…
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…
Many systems used by society are extremely vulnerable to space weather events such as solar flares and geomagnetic storms which could potentially cause catastrophic damage. In recent years, many works have emerged to provide early warning…
Cyber-physical systems often consist of entities that interact with each other over time. Meanwhile, as part of the continued digitization of industrial processes, various sensor technologies are deployed that enable us to record…
We developed a new technology for global detection of atmospheric disturbances, on the basis of phase measurements of the total electron content (TEC) using an international GPS networks. Temporal dependencies of TEC are obtained for a set…
The ionospheric scattering of pulses emitted by PSR B0950+08 is measured using the 10-m RadioAstron Space Radio Telescope, the 300-m Arecibo Radio Telescope and the 14x25-m Westerbork Synthesis Radio Telescope (WSRT) at a frequency band…
The present investigation is directed at exploring southern polar ionospheric responses to intense space weather events and their correlations with plasma convection and auroral precipitation. The main phases of six geomagnetic storms…
A universal interatomic potential for an arbitrary set of chemical elements is urgently needed in computational materials science. Graph convolution neural network (GCN) has rich expressive power, but previously was mainly employed to…
Phase stability at low radio frequencies is severely impacted by ionospheric propagation delays. Radio interferometers such as the Giant Metrewave Radio Telescope (GMRT) are capable of detecting changes in the ionosphere's total electron…
We demonstrate a machine learning based approach which can learn the time-dependent electronic excitation dynamics of small molecules subjected to ion irradiation. Ensembles of recurrent neural networks are trained on data generated by…
Although space weather events may not directly affect human life, they have the potential to inflict significant harm upon our communities. Harmful space weather events can trigger atmospheric changes that result in physical and economic…