Ionospheric Nowcasting Over Italy Through Data Assimilation: A Synergy Between IRI UP and IONORING
Abstract An accurate modeling of the ionosphere electron density is pivotal to guarantee the effective operation of communication and navigation systems, particularly during Space Weather events. Despite the crucial contribution of empirical models like the International Reference Ionosphere (IRI),...
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| Format: | Article |
| Language: | English |
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Wiley
2024-05-01
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| Series: | Space Weather |
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| Online Access: | https://doi.org/10.1029/2023SW003838 |
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| author | Alessio Pignalberi Claudio Cesaroni Marco Pietrella Michael Pezzopane Luca Spogli Carlo Marcocci Emanuele Pica |
| author_facet | Alessio Pignalberi Claudio Cesaroni Marco Pietrella Michael Pezzopane Luca Spogli Carlo Marcocci Emanuele Pica |
| author_sort | Alessio Pignalberi |
| collection | DOAJ |
| description | Abstract An accurate modeling of the ionosphere electron density is pivotal to guarantee the effective operation of communication and navigation systems, particularly during Space Weather events. Despite the crucial contribution of empirical models like the International Reference Ionosphere (IRI), their limitations in predicting ionospheric variability, especially under geomagnetically disturbed conditions, are acknowledged. The solution proposed in this work involves integrating real‐time, spatially distributed ionospheric measurements into climatological models through data assimilation. To enhance our predictive capabilities, we present an upgrade of the IRI UP data‐assimilation method, incorporating real‐time vertical total electron content (vTEC) maps from the IONORING algorithm for nowcasting ionospheric conditions over Italy. This approach involves updating the IRI F2‐layer peak electron density description through ionospheric indices, to finally produce real‐time maps over Italy of the ordinary critical frequency of the F2‐layer, foF2, which is crucial for radio‐propagation applications. The IRI UP–IONORING method performance has been evaluated against different climatological and nowcasting models, and under different Space Weather conditions, by showing promising outcomes which encourages its inclusion in the portfolio of ionospheric real‐time products available over Italy. The validation analysis highlighted also what are the current limitations of the IRI UP–IONORING method, particularly during nighttime for severely disturbed conditions, suggesting avenues for future enhancements. |
| format | Article |
| id | doaj-art-a36bd9ff8bdd45c88f52a4c508843696 |
| institution | Kabale University |
| issn | 1542-7390 |
| language | English |
| publishDate | 2024-05-01 |
| publisher | Wiley |
| record_format | Article |
| series | Space Weather |
| spelling | doaj-art-a36bd9ff8bdd45c88f52a4c5088436962025-01-14T16:27:30ZengWileySpace Weather1542-73902024-05-01225n/an/a10.1029/2023SW003838Ionospheric Nowcasting Over Italy Through Data Assimilation: A Synergy Between IRI UP and IONORINGAlessio Pignalberi0Claudio Cesaroni1Marco Pietrella2Michael Pezzopane3Luca Spogli4Carlo Marcocci5Emanuele Pica6Istituto Nazionale di Geofisica e Vulcanologia Rome ItalyIstituto Nazionale di Geofisica e Vulcanologia Rome ItalyIstituto Nazionale di Geofisica e Vulcanologia Rome ItalyIstituto Nazionale di Geofisica e Vulcanologia Rome ItalyIstituto Nazionale di Geofisica e Vulcanologia Rome ItalyIstituto Nazionale di Geofisica e Vulcanologia Rome ItalyIstituto Nazionale di Geofisica e Vulcanologia Rome ItalyAbstract An accurate modeling of the ionosphere electron density is pivotal to guarantee the effective operation of communication and navigation systems, particularly during Space Weather events. Despite the crucial contribution of empirical models like the International Reference Ionosphere (IRI), their limitations in predicting ionospheric variability, especially under geomagnetically disturbed conditions, are acknowledged. The solution proposed in this work involves integrating real‐time, spatially distributed ionospheric measurements into climatological models through data assimilation. To enhance our predictive capabilities, we present an upgrade of the IRI UP data‐assimilation method, incorporating real‐time vertical total electron content (vTEC) maps from the IONORING algorithm for nowcasting ionospheric conditions over Italy. This approach involves updating the IRI F2‐layer peak electron density description through ionospheric indices, to finally produce real‐time maps over Italy of the ordinary critical frequency of the F2‐layer, foF2, which is crucial for radio‐propagation applications. The IRI UP–IONORING method performance has been evaluated against different climatological and nowcasting models, and under different Space Weather conditions, by showing promising outcomes which encourages its inclusion in the portfolio of ionospheric real‐time products available over Italy. The validation analysis highlighted also what are the current limitations of the IRI UP–IONORING method, particularly during nighttime for severely disturbed conditions, suggesting avenues for future enhancements.https://doi.org/10.1029/2023SW003838IRI UPIONORINGspace weatherionosphere modelingdata assimilationnowcasting |
| spellingShingle | Alessio Pignalberi Claudio Cesaroni Marco Pietrella Michael Pezzopane Luca Spogli Carlo Marcocci Emanuele Pica Ionospheric Nowcasting Over Italy Through Data Assimilation: A Synergy Between IRI UP and IONORING Space Weather IRI UP IONORING space weather ionosphere modeling data assimilation nowcasting |
| title | Ionospheric Nowcasting Over Italy Through Data Assimilation: A Synergy Between IRI UP and IONORING |
| title_full | Ionospheric Nowcasting Over Italy Through Data Assimilation: A Synergy Between IRI UP and IONORING |
| title_fullStr | Ionospheric Nowcasting Over Italy Through Data Assimilation: A Synergy Between IRI UP and IONORING |
| title_full_unstemmed | Ionospheric Nowcasting Over Italy Through Data Assimilation: A Synergy Between IRI UP and IONORING |
| title_short | Ionospheric Nowcasting Over Italy Through Data Assimilation: A Synergy Between IRI UP and IONORING |
| title_sort | ionospheric nowcasting over italy through data assimilation a synergy between iri up and ionoring |
| topic | IRI UP IONORING space weather ionosphere modeling data assimilation nowcasting |
| url | https://doi.org/10.1029/2023SW003838 |
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