How open data and interdisciplinary collaboration improve our understanding of space weather: A risk and resiliency perspective

Space weather refers to conditions around a star, like our Sun, and its interplanetary space that may affect space- and ground-based assets as well as human life. Space weather can manifest as many different phenomena, often simultaneously, and can create complex and sometimes dangerous conditions. The study of space weather is inherently trans-disciplinary, including subfields of solar, magnetospheric, ionospheric, and atmospheric research communities, but benefiting from collaborations with policymakers, industry, astrophysics, software engineering, and many more. Effective communication is required between scientists, the end-user community, and government organizations to ensure that we are prepared for any adverse space weather effects. With the rapid growth of the field in recent years, the current Solar Cycle 25 maximum, and the evolution of research-ready technologies, we believe that space weather deserves a reexamination in terms of a “risk and resiliency” framework. By utilizing open data science, cross-disciplinary collaborations, information systems, and citizen science, we can forge stronger partnerships between science, industry, and the public and improve our readiness as a society to mitigate space weather impacts. The objective of this talk is to raise awareness of these concepts as the solar maximum peaks, coinciding with an increasingly technology-dependent society, and introduce a unique way of approaching space weather through the lens of a risk and resiliency framework that can be used to further assess areas of improvement in the field.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-08-08
DOI
https://doi.org/10.5281/zenodo.13265272
Primary Topic
Ionosphere and magnetosphere dynamics
Type
article
Field-Weighted Citation Impact
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article

How open data and interdisciplinary collaboration improve our understanding of space weather: A risk and resiliency perspective

Zenodo (CERN European Organization for Nuclear Research)
Ionosphere and magnetosphere dynamics
article

How open data and interdisciplinary collaboration improve our understanding of space weather: A risk and resiliency perspective

article en

Abstract

Space weather refers to conditions around a star, like our Sun, and its interplanetary space that may affect space- and ground-based assets as well as human life. Space weather can manifest as many different phenomena, often simultaneously, and can create complex and sometimes dangerous conditions. The study of space weather is inherently trans-disciplinary, including subfields of solar, magnetospheric, ionospheric, and atmospheric research communities, but benefiting from collaborations with policymakers, industry, astrophysics, software engineering, and many more. Effective communication is required between scientists, the end-user community, and government organizations to ensure that we are prepared for any adverse space weather effects. With the rapid growth of the field in recent years, the current Solar Cycle 25 maximum, and the evolution of research-ready technologies, we believe that space weather deserves a reexamination in terms of a “risk and resiliency” framework. By utilizing open data science, cross-disciplinary collaborations, information systems, and citizen science, we can forge stronger partnerships between science, industry, and the public and improve our readiness as a society to mitigate space weather impacts. The objective of this talk is to raise awareness of these concepts as the solar maximum peaks, coinciding with an increasingly technology-dependent society, and introduce a unique way of approaching space weather through the lens of a risk and resiliency framework that can be used to further assess areas of improvement in the field.

Zenodo (CERN European Organization for Nuclear Research)
New Jersey Institute of Technology (US), Goddard Space Flight Center (US), Jet Propulsion Laboratory (US), University of Alaska Fairbanks (US), Predictive Science (United States) (US)
Openalex Percentile: Top 69%
Ionosphere and magnetosphere dynamics
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