Variability and Predictability of Space Weather and the Ionosphere: Recent Advances
A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Upper Atmosphere".
Deadline for manuscript submissions: 15 May 2024 | Viewed by 708
Special Issue Editor
Interests: ionospheric and space weather research and applications; GNSS science and technology
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Studying complex systems such as Space Weather and the Ionosphere is relevant to understanding the physical processes involved (Knowledge) and society’s use of such systems (Applications). New approaches, including the chaotic description of such systems and the development of advanced machine learning algorithms, make it possible to advance in the ability to model and predict the time evolution of their variables. It is of particular importance to have an updated view of these new approaches and their current or potential use to study and model Space Weather and Ionosphere variability and predictability. This Special Issue aims to provide a comprehensive view of the advancements in this field. Particular emphasis, though not exclusive, should be given to approaches that combine chaos theoretical descriptions and advanced machine learning algorithms when applied to Ionosphere and Space Weather basic modelling and society-oriented research. For this reason, we encourage colleagues to submit papers with this perspective to provide, in this Special Issue, an updated view on the subject.
Prof. Dr. Sandro Radicella
Guest Editor
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Atmosphere is an international peer-reviewed open access monthly journal published by MDPI.
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Keywords
- space weather modelling
- Ionosphere modelling
- chaos
- machine learning
