415 citations · 1.2k across the 34 of their papers we have counts for
15 papers · 1 filter
Bayesian Inference and Global Sensitivity Analysis for Ambient Solar Wind Prediction
Opal Issan, Pete Riley, Enrico Camporeale +1
The ambient solar wind plays a significant role in propagating interplanetary coronal mass ejections and is an important driver of space weather geomagnetic storms. A computational…
Multi-Hour Ahead Dst Index Prediction Using Multi-Fidelity Boosted Neural Networks
A. Hu, E. Camporeale, B. Swiger
The Disturbance storm time (Dst) index has been widely used as a proxy for the ring current intensity, and therefore as a measure of geomagnetic activity. It is derived by measurem…
Probabilistic prediction of Dst storms one-day-ahead using Full-Disk SoHO Images
A. Hu, C. Shneider, A. Tiwari +1
We present a new model for the probability that the Disturbance storm time (Dst) index exceeds -100 nT, with a lead time between 1 and 3 days. provides essential information…
Parameter Distributions for the Drag-Based Modeling of CME Propagation
Gianluca Napoletano, Raffaello Foldes, Enrico Camporeale +7
In recent years, ensemble modeling has been widely employed in space weather to estimate uncertainties in forecasts. We here focus on the ensemble modeling of CME arrival times and…
Machine-learning based discovery of missing physical processes in radiation belt modeling
Enrico Camporeale, George J. Wilkie, Alexander Drozdov +1
Real-time prediction of the dynamics of energetic electrons in Earth's radiation belts incorporating incomplete observation data is important to protect valuable artificial satelli…
Toward a Next Generation Particle Precipitation Model: Mesoscale Prediction Through Machine Learning (a Case Study and Framework for Progress)
Ryan M. McGranaghan, Jack Ziegler, Téo Bloch +7
We advance the modeling capability of electron particle precipitation from the magnetosphere to the ionosphere through a new database and use of machine learning (ML) tools to gain…