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Global Space Weather Variability with a Specific Focus on Ionospheric Climatological Forecasting and Predictive Modelling

This special issue belongs to the section “Upper Atmosphere“.

Special Issue Information

Dear Colleagues,

We are excited to invite you to submit your manuscript to our Special Issue in the open access journal Atmosphere, titled “Global Space Weather Variability with a Specific Focus on Ionospheric Climatological Forecasting and Predictive Modelling”. This Special Issue aims to highlight recent advancements in the study of global ionospheric variability, particularly regarding geophysical parameters and space weather, with a specific focus on ionospheric climatological forecasting and predictive modelling.

The ionosphere, a dynamic region of Earth's upper atmosphere, exhibits significant variability driven by solar radiation, geomagnetic activity, and atmospheric dynamics. This variability can be categorized into climatological patterns, which follow predictable long-term trends, and more rapid, unpredictable disturbances caused by space weather events. Space weather, influenced primarily by solar activity such as solar flares, coronal mass ejections (CMEs), and high-speed solar wind streams, can trigger geomagnetic variabilities that lead to substantial ionospheric disturbances, including irregularities in electron density, travelling ionospheric disturbances (TIDs), and disruptions to communication and navigation systems. Ionospheric climatological forecasting focuses on understanding and predicting long-term trends based on factors such as the solar cycle, seasonal variations, and diurnal changes. Observations from multi-instrument networks have been crucial in characterizing the ionosphere at various altitudes and across both regional and global scales. The integration of data from ground-based and space-based platforms has facilitated the investigation of ionospheric dynamics over extensive spatial ranges, from low to high latitudes and across different longitudinal sectors, under both quiet and disturbed geomagnetic conditions. Predictive models, including empirical models (e.g., IRI (International Reference Ionosphere), NeQuick-G, etc.), physics-based models (e.g., TIE-GCM), and data-assimilative models, combine theoretical understanding with observational data to provide reliable estimates of ionospheric conditions. These models are crucial for identifying baseline climatological behaviour and distinguishing it from space weather-related anomalies. Predictive modelling for space weather-induced ionospheric variability leverages real-time data sources, including GNSS-based total electron content (TEC), ionosonde measurements, and satellite observations, to capture rapid changes during adverse geomagnetic conditions. Advanced tools such as machine learning algorithms and ensemble modelling are increasingly employed to improve forecasts of ionospheric responses to space weather events. For instance, models can predict ionospheric disturbances like TIDs, TEC enhancements, ionospheric scintillations, and shifts in the midlatitude ionospheric trough, which impact critical technologies like satellite-based communication and GNSS navigations.

We welcome contributions that explore ionospheric variability across wide spatial and temporal scales, influenced by different geophysical aspects and varying geomagnetic conditions, with a particular emphasis on ionospheric climatological forecasting and predictive models. Understanding ionospheric characteristics is vital for climatology and forecasting, aiding in the mitigation of challenges faced by modern technologies reliant on radio communication and navigation systems.

Regards, 

Dr. Krishnendu Sekhar Paul
Prof. Dr. Stelios M. Potirakis
Guest Editors

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.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • global ionospheric dynamics
  • global ionospheric irregularity distribution
  • detection and characterization of ionospheric irregularities via multi-instrument methods
  • ionospheric variability during quiet and disturbed geomagnetic conditions
  • climatological forecasting of ionosphere
  • ionospheric irregularity prediction models

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Atmosphere - ISSN 2073-4433