422 citations
- National Oceanic and Atmospheric AdministrationUS28 papers
- University of Colorado BoulderUS17 papers
- Cooperative Institute for Research in Environmental SciencesUS16 papers
- Goddard Space Flight CenterUS10 papers
- Centre National de la Recherche ScientifiqueFR7 papers
- Catholic University of AmericaUS6 papers
- Centrum Wiskunde & InformaticaNL5 papers
- George Mason UniversityUS5 papers
- Royal Observatory of BelgiumBE5 papers
- Academy of AthensGR4 papers
- HeliophysicsUS4 papers
- KU LeuvenBE4 papers
30 papers
Advancing Heliophysics and Space Weather Modeling through Open Science
C. Corti, M. M. Kuznetsova, M. A. Reiss +85
We present a community-wide effort to develop a strategy and action plan to advance heliophysics and space weather modeling through open science. While open science has the potenti…
Simulated Operational Testing of the Prototype Implementation of the SOFIE Model: The 2025 Space Weather Prediction Testbed Exercise
Weihao Liu, Lulu Zhao, Igor V. Sokolov +29
The CLEAR Space Weather Center of Excellence's solar energetic particle (SEP) model, SOlar wind with FIeld lines and Energetic particles (SOFIE), was run and evaluated on-site duri…
Polarimeter to Unify the Corona and Heliosphere (PUNCH)
Craig E. DeForest, Sarah E. Gibson, Ronnie Killough +74
The Polarimeter to Unify the Corona and Heliosphere (PUNCH) mission is a NASA Small Explorer to determine the cross-scale processes that unify the solar corona and heliosphere. PUN…
Evidence of dual energy transfer driven by magnetic reconnection at sub-ion scales
Raffaello Foldes, Silvio Sergio Cerri, Raffaele Marino +1
The properties of energy transfer in the kinetic range of plasma turbulence have fundamental implications on the turbulent heating of space and astrophysical plasmas. It was recent…
A catalogue of observed geo-effective CME/ICME characteristics
R. Mugatwala, S. Chierichini, G. Francisco +7
One of the goals of Space Weather studies is to achieve a better understanding of impulsive phenomena, such as Coronal Mass Ejections (CMEs), in order to improve our ability to for…
Low-dimensional representation of intermittent geophysical turbulence with High-Order Statistics-informed Neural Networks (H-SiNN)
Raffaello Foldes, Enrico Camporeale, Raffaele Marino
We present a novel machine learning approach to reduce the dimensionality of state variables in stratified turbulent flows governed by the Navier-Stokes equations in the Boussinesq…