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Large solar eruptive events, including solar flares and coronal mass ejections (CMEs), can lead to solar energetic particle (SEP) events. During these events, protons are accelerated up to several GeV and pose numerous space weather risks.…

Forecasting technological advancement in complex domains such as space exploration presents significant challenges due to the intricate interaction of technical, economic, and policy-related factors. The field of technology forecasting has…

The forecasting of solar energetic particles (SEPs) is a prominent area of space weather research. Numerous forecasting models exist that predict SEP event properties at proton energies <100MeV. One of these models is the SPARX system, a…

We study the large solar energetic particle (SEP) events that were detected by GOES in the $>$ 10 MeV energy channel during December 2006 to March 2014. We derive and compare solar particle release (SPR) times for the 0.25--10.4 MeV…

This study addresses the prediction of geomagnetic disturbances by exploiting machine learning techniques. Specifically, the Long-Short Term Memory recurrent neural network, which is particularly suited for application over long time…

The Sun continuously affects the interplanetary environment through a host of interconnected and dynamic physical processes. Solar flares, Coronal Mass Ejections (CMEs), and Solar Energetic Particles (SEPs) are among the key drivers of…

Gradual solar energetic particle (SEP) events, usually attributed to shock waves driven by coronal mass ejections (CMEs), show a wide variety of temporal behaviors. For example, TO, the >10 MeV proton onset time with respect to the launch…

A convolutional neural network (CNN) is used to construct a new catalog for solar flares based on high resolution (1-s cadence) Geostationary Operational Environmental Satellites (GOES) soft X-ray data. The CNN is trained to identify flare…

Solar Energetic Particle (SEPs) with energies ranging from tens of keV to a few GeV, are a significant component in the description of the space environment. In this work, the HESPERIA REleASE product is emphasized, which, based on the…

The solar wind, a stream of charged particles originating from the Sun and transcending interplanetary space, poses risks to technology and astronauts. In this work, we develop a prediction model to forecast the solar wind speed at the…

Optical turbulence, driven by fluctuations of the atmospheric refractive index, poses a significant challenge to ground-based optical systems, as it distorts the propagation of light. This degradation affects both astronomical observations…

Predictions on subseasonal-to-seasonal (S2S) timescales--ranging from two weeks to two month--are crucial for early warning systems but remain challenging owing to chaos in the climate system. Teleconnections, such as the stratospheric…

A deep learning network, Long-Short Term Memory (LSTM) network, is used in this work to predict whether the maximum flare class an active region (AR) will produce in the next 24 hours is class $\Gamma$. We considered $\Gamma$ are $\ge M$,…

We develop a mixed Long Short Term Memory (LSTM) regression model to predict the maximum solar flare intensity within a 24-hour time window 0$\sim$24, 6$\sim$30, 12$\sim$36 and 24$\sim$48 hours ahead of time using 6, 12, 24 and 48 hours of…

Extended human presence beyond low-Earth orbit (BLEO) during missions to the Moon and Mars will pose significant challenges in the near future. A primary health risk associated with these missions is radiation exposure, primarily from…

Geomagnetic storms (GSTs) driven by solar wind-magnetosphere coupling can severely disrupt technological systems, motivating the need for improved prediction accuracy and longer warning times. In this study, we develop a physics-informed…

We summarize observations of around a thousand solar energetic particle (SEP) events since 1967 that include ~25 MeV protons, made by various near-Earth spacecraft (IMPs 4, 5, 7, 8, ISEE 3, SOHO), that encompass Solar Cycle 20 to the…

The limits of previous methods promote us to design a new approach (named PRESTAGE) to predict proton single event effect (SEE) cross-sections using heavy-ion test data. To more realistically simulate the SEE mechanisms, we adopt Geant4 and…

An indirect proton flux measuring tool based on discrimination of the energy deposited by protons in 128 x 128 pixel EIT CCD areas outside the solar disk images is presented. Single pixel intensity events are converted into proton incident…

Predictive queries over spatiotemporal (ST) stream data pose significant data processing and analysis challenges. ST data streams involve a set of time series whose data distributions may vary in space and time, exhibiting multiple distinct…