1 citations · 2 across the 8 of their papers we have counts for
10 papers
SWAN-SF-V2: A Multivariate Time Series Dataset for Space Weather Data Analytics; Now with AIA and Weighted SHARP Parameters
Dustin Kempton, Griffin Goodwin, Reet Gupta +4
Since its original publication in 2020, the SWAN-SF dataset has been cited in over 300 research publications. Here we describe a comprehensive update to the original multivariate t…
Developing Machine Learning Models of Subgrid Turbulent Transport for Quiet Sun 3D Radiative Hydrodynamic Simulations
Rimsha Hameed Syeda, Dustin Kempton, Viacheslav Sadykov +2
Numerical modeling of solar plasma dynamics is affected by the resolution of the computational grid. This often requires the estimation of subgrid processes related to the small-sc…
Review of Machine Learning Models for Solar Energetic Particle Prediction
Spiridon Kasapis, Pouya Hosseinzadeh, Kathryn Whitman +73
Solar energetic particle (SEP) events have attracted increasing attention due to their significant radiation hazards for aviation, spacecraft electronics, and human missions beyond…
Describing the swdatatoolkit: A Space Weather Data Analysis Library
Dustin Kempton, Griffin Goodwin, Tarun Kumar Reddy Thippareddy +3
swdatatoolkit is a Python-based scientific software library designed to support the acquisition, preprocessing, and analysis of solar and space weather data. The toolkit consolidat…
Improving Solar Flare Soft X-ray Classification With FOXES: A Framework For Operational X-ray Emission Synthesis
Griffin T. Goodwin, Alison J. March, Jayant Biradar +5
The Geostationary Operational Environmental Satellite (GOES) solar soft X-ray (SXR) irradiance in the 1-8Å wavelength range is a long-standing measure of solar activity, used to de…
Machine Learning-Ready Data Sets for the Analysis and Nowcasting of Atmospheric Radiation at Aviation Altitudes
Viacheslav M Sadykov, Zachary M Watkins, Dustin Kempton +10
Nowcasting and forecasting of the radiation environment in the Earth's lower atmosphere are critical for the safety of aircraft and spacecraft crews and passengers. Currently, this…
Nowcasting of Aviation Radiation Using Geospace Environment Properties: A Machine Learning Approach
Sanjib K C, Viacheslav M Sadykov, Dustin Kempton
Radiation exposure at aviation altitudes presents significant health risks to aircrews due to the cumulative effects of ionizing radiation. Physics-based models estimate radiation…
Using ML-based Regression Techniques to Mitigate GOES Energetic Proton Flux Data Contamination and Magnetospheric Effects
Aatiya Ali, Viacheslav Sadykov
Positioned at geostationary orbit (GEO) ~36,000 km above Earth, NOAA's GOES series has recorded real-time energetic proton flux measurements crucial for space weather monitoring fo…
Comparative Analysis of 10 - 50 MeV Solar Proton Events at Lagrange Point 1 and the Geostationary Orbit
Aatiya Ali, Viacheslav Sadykov
Solar proton events (SPEs) pose radiation hazards, disrupt technology, and impact operations on Earth and in space, making continuous monitoring essential. We compare 10-50 MeV pro…
Operational and Exploration Requirements and Research Capabilities for SEP Environment Monitoring and Forecasting
Viacheslav Sadykov, Petrus Martens, Dustin Kempton +15
Mitigating risks posed by solar energetic particles (SEPs) to operations and exploration in space and Earth's atmosphere motivates the development of advanced, synergistic approach…